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Sample records for adaptor proteins networks

  1. The fifth adaptor protein complex.

    Directory of Open Access Journals (Sweden)

    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.

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

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    Mathilde L Bonnemaison

    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.

  3. XB130: A novel adaptor protein in cancer signal transduction

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    ZHANG, RUIYAO; ZHANG, JINGYAO; WU, QIFEI; MENG, FANDI; LIU, CHANG

    2016-01-01

    Adaptor proteins are functional proteins that contain two or more protein-binding modules to link signaling proteins together, which affect cell growth and shape and have no enzymatic activity. The actin filament-associated protein (AFAP) family is an important member of the adaptor proteins, including AFAP1, AFAP1L1 and AFAP1L2/XB130. AFAP1 and AFAP1L1 share certain common characteristics and function as an actin-binding protein and a cSrc-activating protein. XB130 exhibits certain unique features in structure and function. The mRNA of XB130 is expressed in human spleen, thyroid, kidney, brain, lung, pancreas, liver, colon and stomach, and the most prominent disease associated with XB130 is cancer. XB130 has a controversial effect on cancer. Studies have shown that XB130 can promote cancer progression and downregulation of XB130-reduced growth of tumors derived from certain cell lines. A higher mRNA level of XB130 was shown to be associated with a better survival in non-small cell lung cancer. Previous studies have shown that XB130 can regulate cell growth, migration and invasion and possibly has the effect through the cAMP-cSrc-phosphoinositide 3-kinase/Akt pathway. Except for cancer, XB130 is also associated with other pathological or physiological procedures, such as airway repair and regeneration. PMID:26998266

  4. Modulation of lipoprotein receptor functions by intracellular adaptor proteins.

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    Stolt, Peggy C; Bock, Hans H

    2006-10-01

    Members of the low density lipoprotein (LDL) receptor gene family are critically involved in a wide range of physiological processes including lipid and vitamin homeostasis, cellular migration, neurodevelopment, and synaptic plasticity, to name a few. Lipoprotein receptors exert these diverse biological functions by acting as cellular uptake receptors or by inducing intracellular signaling cascades. It was discovered that a short sequence in the intracellular region of all lipoprotein receptors, Asn-Pro-X-Tyr (NPXY) is important for mediating either endocytosis or signal transduction events, and that this motif serves as a binding site for phosphotyrosine-binding (PTB) domain containing scaffold proteins. These molecular adaptors connect the transmembrane receptors with the endocytosis machinery and regulate cellular trafficking, or function as assembly sites for dynamic multi-protein signaling complexes. Whereas the LDL receptor represents the archetype of an endocytic lipoprotein receptor, the structurally closely related apolipoprotein E receptor 2 (apoER2) and very low density lipoprotein (VLDL) receptor activate a kinase-dependent intracellular signaling cascade after binding to the neuronal signaling molecule Reelin. This review focuses on two related PTB domain containing adaptor proteins that mediate these divergent lipoprotein receptor responses, ARH (autosomal recessive hypercholesterolemia protein) and Dab1 (disabled-1), and discusses the structural and molecular basis of this different behaviour.

  5. Negative regulation of lymphocyte activation by the adaptor protein LAX.

    Science.gov (United States)

    Zhu, Minghua; Granillo, Olivia; Wen, Renren; Yang, Kaiyong; Dai, Xuezhi; Wang, Demin; Zhang, Weiguo

    2005-05-01

    The membrane-associated adaptor protein LAX is a linker for activation of T cells (LAT)-like molecule that is expressed in lymphoid tissues. Upon stimulation of T or B cells, it is phosphorylated and interacts with Grb2 and the p85 subunit of PI3K. LAX, however, is not capable of replacing LAT in the TCR signaling pathway. In this study we report that upon T or B cell activation, the LAX protein was up-regulated dramatically. Although disruption of the LAX gene by homologous recombination had no major impact on lymphocyte development, it caused a significant reduction in CD23 expression on mature B cells. Interestingly, naive LAX(-/-) mice had spontaneous germinal center formation. Compared with normal T and B cells, LAX(-/-) T and B cells were hyperresponsive and had enhanced calcium flux, protein tyrosine phosphorylation, MAPK and Akt activation, and cell survival upon engagement of the T or B AgRs. Our data demonstrate that LAX functions as a negative regulator in lymphocyte signaling.

  6. Exploring structure and interactions of the bacterial adaptor protein YjbH by crosslinking mass spectrometry

    DEFF Research Database (Denmark)

    Al-Eryani, Yusra; Ib Rasmussen, Morten; Kjellström, Sven;

    2016-01-01

    Adaptor proteins assist proteases in degrading specific proteins under appropriate conditions. The adaptor protein YjbH promotes the degradation of an important global transcriptional regulator Spx, which controls the expression of hundreds of genes and operons in response to thiol-specific oxida......Adaptor proteins assist proteases in degrading specific proteins under appropriate conditions. The adaptor protein YjbH promotes the degradation of an important global transcriptional regulator Spx, which controls the expression of hundreds of genes and operons in response to thiol......-specific oxidative stress in Bacillus subtilis. Under normal growth conditions, the transcription factor is bound to the adaptor protein and therefore degraded by the AAA+ protease ClpXP. If this binding is alleviated during stress, the transcription factor accumulates and turns on genes encoding stress...... and validate a structure model of YjbH and then to probe its interactions with other proteins. The core structure of YjbH is reminiscent of DsbA family proteins. One lysine residue in YjbH (K177), located in one of the α-helices outside the thioredoxin fold, crosslinked to both Spx K99 and Spx K117, thereby...

  7. The Emerging and Diverse Roles of Src-Like Adaptor Proteins in Health and Disease

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    Nikolett Marton

    2015-01-01

    Full Text Available Although Src-like adaptor proteins (SLAP-1 and SLAP-2 were mainly studied in lymphocytes, where they act as negative regulators and provide fine control of receptor signaling, recently, several other functions of these proteins were discovered. In addition to the well-characterized immunoregulatory functions, SLAP proteins appear to have an essential role in the pathogenesis of type I hypersensitivity, osteoporosis, and numerous malignant diseases. Both adaptor proteins are expressed in a wide variety of tissues, where they have mostly inhibitory effects on multiple intracellular signaling pathways. In this review, we summarize the diverse effects of SLAP proteins.

  8. Distinct adaptor proteins assist exit of Kre2-family proteins from the yeast ER

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    Yoichi Noda

    2014-07-01

    Full Text Available The Svp26 protein of S. cerevisiae is an ER- and Golgi-localized integral membrane protein with 4 potential membrane-spanning domains. It functions as an adaptor protein that facilitates the ER exit of Ktr3, a mannosyltransferase required for biosynthesis of O-linked oligosaccharides, and the ER exit of Mnn2 and Mnn5, mannosyltransferases, which participate in the biosynthesis of N-linked oligosaccharides. Ktr3 belongs to the Kre2 family, which consists of 9 members of type-II membrane proteins sharing sequence similarities. In this report, we examined all Kre2 family members and found that the Golgi localizations of two others, Kre2 and Ktr1, were dependent on Svp26 by immunofluorescence microscopy and cell fractionations in sucrose density gradients. We show that Svp26 functions in facilitating the ER exit of Kre2 and Ktr1 by an in vitro COPII budding assay. Golgi localization of Ktr4 was not dependent on Svp26. Screening null mutants of the genes encoding abundant COPII membrane proteins for those showing mislocalization of Ktr4 in the ER revealed that Erv41 and Erv46 are required for the correct Golgi localization of Ktr4. We provide biochemical evidence that the Erv41-Erv46 complex functions as an adaptor protein for ER exit of Ktr4. This is the first demonstration of the molecular function of this evolutionally conserved protein complex. The domain switching experiments show that the lumenal domain of Ktr4 is responsible for recognition by the Erv41-Erv46 complex. Thus, ER exit of Kre2-family proteins is dependent on distinct adaptor proteins and our results provide new insights into the traffic of Kre2-family mannosyltransferases.

  9. The clathrin adaptor Dab2 recruits EH domain scaffold proteins to regulate integrin β1 endocytosis.

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    Teckchandani, Anjali; Mulkearns, Erin E; Randolph, Timothy W; Toida, Natalie; Cooper, Jonathan A

    2012-08-01

    Endocytic adaptor proteins facilitate cargo recruitment and clathrin-coated pit nucleation. The prototypical clathrin adaptor AP2 mediates cargo recruitment, maturation, and scission of the pit by binding cargo, clathrin, and accessory proteins, including the Eps-homology (EH) domain proteins Eps15 and intersectin. However, clathrin-mediated endocytosis of some cargoes proceeds efficiently in AP2-depleted cells. We found that Dab2, another endocytic adaptor, also binds to Eps15 and intersectin. Depletion of EH domain proteins altered the number and size of clathrin structures and impaired the endocytosis of the Dab2- and AP2-dependent cargoes, integrin β1 and transferrin receptor, respectively. To test the importance of Dab2 binding to EH domain proteins for endocytosis, we mutated the EH domain-binding sites. This mutant localized to clathrin structures with integrin β1, AP2, and reduced amounts of Eps15. Of interest, although integrin β1 endocytosis was impaired, transferrin receptor internalization was unaffected. Surprisingly, whereas clathrin structures contain both Dab2 and AP2, integrin β1 and transferrin localize in separate pits. These data suggest that Dab2-mediated recruitment of EH domain proteins selectively drives the internalization of the Dab2 cargo, integrin β1. We propose that adaptors may need to be bound to their cargo to regulate EH domain proteins and internalize efficiently.

  10. Identification of Cargo for Adaptor Protein (AP) Complexes 3 and 4 by Sucrose Gradient Profiling.

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    Pertl-Obermeyer, Heidi; Wu, Xu Na; Schrodt, Jens; Müdsam, Christina; Obermeyer, Gerhard; Schulze, Waltraud X

    2016-09-01

    Intracellular vesicle trafficking is a fundamental process in eukaryotic cells. It enables cellular polarity and exchange of proteins between subcellular compartments such as the plasma membrane or the vacuole. Adaptor protein complexes participate in the vesicle formation by specific selection of the transported cargo. We investigated the role of the adaptor protein complex 3 (AP-3) and adaptor protein complex 4 (AP-4) in this selection process by screening for AP-3 and AP-4 dependent cargo proteins. Specific cargo proteins are expected to be mis-targeted in knock-out mutants of adaptor protein complex components. Thus, we screened for altered distribution profiles across a density gradient of membrane proteins in wild type versus ap-3β and ap-4β knock-out mutants. In ap-3β mutants, especially proteins with transport functions, such as aquaporins and plasma membrane ATPase, as well as vesicle trafficking proteins showed differential protein distribution profiles across the density gradient. In the ap-4β mutant aquaporins but also proteins from lipid metabolism were differentially distributed. These proteins also showed differential phosphorylation patterns in ap-3β and ap-4β compared with wild type. Other proteins, such as receptor kinases were depleted from the AP-3 mutant membrane system, possibly because of degradation after mis-targeting. In AP-4 mutants, membrane fractions were depleted for cytochrome P450 proteins, cell wall proteins and receptor kinases. Analysis of water transport capacity in wild type and mutant mesophyll cells confirmed aquaporins as cargo proteins of AP-3 and AP-4. The combination of organelle density gradients with proteome analysis turned out as a suitable experimental strategy for large-scale analyses of protein trafficking.

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

    Lifescience Database Archive (English)

    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

  12. Exploring structure and interactions of the bacterial adaptor protein YjbH by crosslinking mass spectrometry.

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    Al-Eryani, Yusra; Ib Rasmussen, Morten; Kjellström, Sven; Højrup, Peter; Emanuelsson, Cecilia; von Wachenfeldt, Claes

    2016-09-01

    Adaptor proteins assist proteases in degrading specific proteins under appropriate conditions. The adaptor protein YjbH promotes the degradation of an important global transcriptional regulator Spx, which controls the expression of hundreds of genes and operons in response to thiol-specific oxidative stress in Bacillus subtilis. Under normal growth conditions, the transcription factor is bound to the adaptor protein and therefore degraded by the AAA+ protease ClpXP. If this binding is alleviated during stress, the transcription factor accumulates and turns on genes encoding stress-alleviating proteins. The adaptor protein YjbH is thus a key player involved in these interactions but its structure is unknown. To gain insight into its structure and interactions we have used chemical crosslinking mass spectrometry. Distance constraints obtained from the crosslinked monomer were used to select and validate a structure model of YjbH and then to probe its interactions with other proteins. The core structure of YjbH is reminiscent of DsbA family proteins. One lysine residue in YjbH (K177), located in one of the α-helices outside the thioredoxin fold, crosslinked to both Spx K99 and Spx K117, thereby suggesting one side of the YjbH for the interaction with Spx. Another lysine residue that crosslinked to Spx was YjbH K5, located in the long and presumably very flexible N-terminal arm of YjbH. Our crosslinking data lend support to a model proposed based on site-directed mutagenesis where the YjbH interaction with Spx can stabilize and present the C-terminal region of Spx for protease recognition and proteolysis. Proteins 2016; 84:1234-1245. © 2016 Wiley Periodicals, Inc.

  13. Role of SRC-like adaptor protein (SLAP) in immune and malignant cell signaling.

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    Kazi, Julhash U; Kabir, Nuzhat N; Rönnstrand, Lars

    2015-07-01

    SRC-like adaptor protein (SLAP) is an adaptor protein structurally similar to the SRC family protein kinases. Like SRC, SLAP contains an SH3 domain followed by an SH2 domain but the kinase domain has been replaced by a unique C-terminal region. SLAP is expressed in a variety of cell types. Current studies suggest that it regulates signaling of various cell surface receptors including the B cell receptor, the T cell receptor, cytokine receptors and receptor tyrosine kinases which are important regulator of immune and cancer cell signaling. SLAP targets receptors, or its associated components, by recruiting the ubiquitin machinery and thereby destabilizing signaling. SLAP directs receptors to ubiquitination-mediated degradation and controls receptors turnover as well as signaling. Thus, SLAP appears to be an important component in regulating signal transduction required for immune and malignant cells.

  14. The Lnk adaptor protein: a key regulator of normal and pathological hematopoiesis.

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    Velazquez, Laura

    2012-12-01

    The development and function of blood cells are regulated by specific growth factors/cytokines and their receptors' signaling pathways. In this way, these factors influence cell survival, proliferation and differentiation of hematopoietic cells. Central to this positive and/or negative control are the adaptor proteins. Since their identification 10 years ago, members of the Lnk adaptor protein family have proved to be important activators and/or inhibitors in the hematopoietic, immune and vascular system. In particular, the generation of animal and cellular models for the Lnk and APS proteins has helped establish the physiological role of these molecules through the identification of their specific signaling pathways and the characterization of their binding partners. Moreover, the recent identification of mutations in the LNK gene in myeloproliferative disorders, as well as the correlation of a single nucleotide polymorphism on LNK with hematological, immune and vascular diseases have suggested its involvement in the pathophysiology of these malignancies. The latter findings have thus raised the possibility of addressing Lnk signaling for the treatment of certain human diseases. This review therefore describes the pathophysiological role of this adaptor protein in hematological malignancies and the potential benefits of Lnk therapeutic targeting.

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

    Science.gov (United States)

    Wiley, H Steven; VanHook, Annalisa M

    2016-07-12

    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.

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

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    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.

  17. Versatile modes of peptide recognition by the AAA+ adaptor protein SspB

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    Levchenko, Igor; Grant, Robert A.; Flynn, Julia M.; Sauer, Robert T.; Baker, Tania A. (MIT)

    2010-07-19

    Energy-dependent proteases often rely on adaptor proteins to modulate substrate recognition. The SspB adaptor binds peptide sequences in the stress-response regulator RseA and in ssrA-tagged proteins and delivers these molecules to the AAA+ ClpXP protease for degradation. The structure of SspB bound to an ssrA peptide is known. Here, we report the crystal structure of a complex between SspB and its recognition peptide in RseA. Notably, the RseA sequence is positioned in the peptide-binding groove of SspB in a direction opposite to the ssrA peptide, the two peptides share only one common interaction with the adaptor, and the RseA interaction site is substantially larger than the overlapping ssrA site. This marked diversity in SspB recognition of different target proteins indicates that it is capable of highly flexible and dynamic substrate delivery.

  18. Identification of actin binding protein, ABP-280, as a binding partner of human Lnk adaptor protein.

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    He, X; Li, Y; Schembri-King, J; Jakes, S; Hayashi, J

    2000-08-01

    Human Lnk (hLnk) is an adaptor protein with multiple functional domains that regulates T cell activation signaling. In order to identify cellular Lnk binding partners, a yeast two-hybrid screening of human spleen cDNA library was carried out using human hLnk as bait. A polypeptide sequence identical to the C-terminal segment of the actin binding protein (ABP-280) was identified as a hLnk binding protein. The expressed hLnk and the FLAG tagged C-terminal 673 amino acid residues of ABP-280 or the endogenous ABP-280 in COS-7 cells could be co-immunoprecipitated using antibodies either to hLnk, FLAG or ABP-280, respectively. Furthermore, immunofluorescence confocal microscope showed that hLnk and ABP-280 co-localized at the plasma membrane and at juxtanuclear region of COS-7 cells. In Jurkat cells, the endogenous hLnk also associates with the endogenous ABP-280 indicating that the association of these two proteins is physiological. The interacting domains of both proteins were mapped using yeast two-hybrid assays. Our results indicate that hLnk binds to the residues 2006-2454 (repeats 19-23C) of ABP-280. The domain in hLnk that associates with ABP-280 was mapped to an interdomain region of 56 amino acids between pleckstrin homology and Src homology 2 domains. These results suggest that hLnk may exert its regulatory role through its association with ABP-280.

  19. Role of adaptor proteins in motor regulation and membrane transport

    NARCIS (Netherlands)

    M.A. Schlager (Max)

    2010-01-01

    markdownabstract__Abstract__ Active transport along the cytoskeleton is a process essential for proper cellular function. Although much is known about the motor proteins that generate the necessary force and the cytoskeleton that provides the cellular infrastructure, many questions still remain. Fo

  20. The polarity protein Par3 regulates APP trafficking and processing through the endocytic adaptor protein Numb.

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    Sun, Miao; Asghar, Suwaiba Z; Zhang, Huaye

    2016-09-01

    The processing of amyloid precursor protein (APP) into β-amyloid peptide (Aβ) is a key step in the pathogenesis of Alzheimer's disease (AD), and trafficking dysregulations of APP and its secretases contribute significantly to altered APP processing. Here we show that the cell polarity protein Par3 plays an important role in APP processing and trafficking. We found that the expression of full length Par3 is significantly decreased in AD patients. Overexpression of Par3 promotes non-amyloidogenic APP processing, while depletion of Par3 induces intracellular accumulation of Aβ. We further show that Par3 functions by regulating APP trafficking. Loss of Par3 decreases surface expression of APP by targeting APP to the late endosome/lysosome pathway. Finally, we show that the effects of Par3 are mediated through the endocytic adaptor protein Numb, and Par3 functions by interfering with the interaction between Numb and APP. Together, our studies show a novel role for Par3 in regulating APP processing and trafficking.

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

    DEFF Research Database (Denmark)

    Barres, Romain; Gonzalez, Teresa; Le Marchand-Brustel, Yannick

    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 modify the actin...

  2. Chimeric adaptor proteins translocate diverse type VI secretion system effectors in Vibrio cholerae.

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    Unterweger, Daniel; Kostiuk, Benjamin; Ötjengerdes, Rina; Wilton, Ashley; Diaz-Satizabal, Laura; Pukatzki, Stefan

    2015-08-13

    Vibrio cholerae is a diverse species of Gram-negative bacteria, commonly found in the aquatic environment and the causative agent of the potentially deadly disease cholera. These bacteria employ a type VI secretion system (T6SS) when they encounter prokaryotic and eukaryotic competitors. This contractile puncturing device translocates a set of effector proteins into neighboring cells. Translocated effectors are toxic unless the targeted cell produces immunity proteins that bind and deactivate incoming effectors. Comparison of multiple V. cholerae strains indicates that effectors are encoded in T6SS effector modules on mobile genetic elements. We identified a diverse group of chimeric T6SS adaptor proteins required for the translocation of diverse effectors encoded in modules. An example for a T6SS effector that requires T6SS adaptor protein 1 (Tap-1) is TseL found in pandemic V. cholerae O1 serogroup strains and other clinical isolates. We propose a model in which Tap-1 is required for loading TseL onto the secretion apparatus. After T6SS-mediated TseL export is completed, Tap-1 is retained in the bacterial cell to load other T6SS machines.

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

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    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.

  4. Adaptor protein complexes 1 and 3 are essential for generation of synaptic vesicles from activity-dependent bulk endosomes.

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    Cheung, Giselle; Cousin, Michael A

    2012-04-25

    Activity-dependent bulk endocytosis is the dominant synaptic vesicle retrieval mode during high intensity stimulation in central nerve terminals. A key event in this endocytosis mode is the generation of new vesicles from bulk endosomes, which replenish the reserve vesicle pool. We have identified an essential requirement for both adaptor protein complexes 1 and 3 in this process by employing morphological and optical tracking of bulk endosome-derived synaptic vesicles in rat primary neuronal cultures. We show that brefeldin A inhibits synaptic vesicle generation from bulk endosomes and that both brefeldin A knockdown and shRNA knockdown of either adaptor protein 1 or 3 subunits inhibit reserve pool replenishment from bulk endosomes. Conversely, no plasma membrane function was found for adaptor protein 1 or 3 in either bulk endosome formation or clathrin-mediated endocytosis. Simultaneous knockdown of both adaptor proteins 1 and 3 indicated that they generated the same population of synaptic vesicles. Thus, adaptor protein complexes 1 and 3 play an essential dual role in generation of synaptic vesicles during activity-dependent bulk endocytosis.

  5. Structural basis for the interaction of the adaptor protein grb14 with activated ras.

    Directory of Open Access Journals (Sweden)

    Rohini Qamra

    Full Text Available Grb14, a member of the Grb7-10-14 family of cytoplasmic adaptor proteins, is a tissue-specific negative regulator of insulin signaling. Grb7-10-14 contain several signaling modules, including a Ras-associating (RA domain, a pleckstrin-homology (PH domain, a family-specific BPS (between PH and SH2 region, and a C-terminal Src-homology-2 (SH2 domain. We showed previously that the RA and PH domains, along with the BPS region and SH2 domain, are necessary for downregulation of insulin signaling. Here, we report the crystal structure at 2.4-Å resolution of the Grb14 RA and PH domains in complex with GTP-loaded H-Ras (G12V. The structure reveals that the Grb14 RA and PH domains form an integrated structural unit capable of binding simultaneously to small GTPases and phosphoinositide lipids. The overall mode of binding of the Grb14 RA domain to activated H-Ras is similar to that of the RA domains of RalGDS and Raf1 but with important distinctions. The integrated RA-PH structural unit in Grb7-10-14 is also found in a second adaptor family that includes Rap1-interacting adaptor molecule (RIAM and lamellipodin, proteins involved in actin-cytoskeleton rearrangement. The structure of Grb14 RA-PH in complex with H-Ras represents the first detailed molecular characterization of tandem RA-PH domains bound to a small GTPase and provides insights into the molecular basis for specificity.

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

    Directory of Open Access Journals (Sweden)

    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

  7. A highly versatile adaptor protein for the tethering of growth factors to gelatin-based biomaterials.

    Science.gov (United States)

    Addi, Cyril; Murschel, Frédéric; Liberelle, Benoît; Riahi, Nesrine; De Crescenzo, Gregory

    2017-03-01

    In the field of tissue engineering, the tethering of growth factors to tissue scaffolds in an oriented manner can enhance their activity and increase their half-life. We chose to investigate the capture of the basic Fibroblast Growth Factor (bFGF) and the Epidermal Growth Factor (EGF) on a gelatin layer, as a model for the functionalization of collagen-based biomaterials. Our strategy relies on the use of two high affinity interactions, that is, the one between two distinct coil peptides as well as the one occurring between a collagen-binding domain (CBD) and gelatin. We expressed a chimeric protein to be used as an adaptor that comprises one of the coil peptides and a CBD derived from the human fibronectin. We proved that it has the ability to bind simultaneously to a gelatin substrate and to form a heterodimeric coiled-coil domain with recombinant growth factors being tagged with the complementary coil peptide. The tethering of the growth factors was characterized by ELISA and surface plasmon resonance-based biosensing. The bioactivity of the immobilized bFGF and EGF was evaluated by a human umbilical vein endothelial cell proliferation assay and a vascular smooth muscle cell survival assay. We found that the tethering of EGF preserved its mitogenic and anti-apoptotic activity. In the case of bFGF, when captured via our adaptor protein, changes in its natural mode of interaction with gelatin were observed.

  8. Synthetic protein scaffolds based on peptide motifs and cognate adaptor domains for improving metabolic productivity

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    Anselm H.C. Horn

    2015-11-01

    Full Text Available The efficiency of many cellular processes relies on the defined interaction among different proteins within the same metabolic or signaling pathway. Consequently, a spatial colocalization of functionally interacting proteins has frequently emerged during evolution. This concept has been adapted within the synthetic biology community for the purpose of creating artificial scaffolds. A recent advancement of this concept is the use of peptide motifs and their cognate adaptor domains. SH2, SH3, GBD, and PDZ domains have been used most often in research studies to date. The approach has been successfully applied to the synthesis of a variety of target molecules including catechin, D-glucaric acid, H2, hydrochinone, resveratrol, butyrate, gamma-aminobutyric acid, and mevalonate. Increased production levels of up to 77-fold have been observed compared to non-scaffolded systems. A recent extension of this concept is the creation of a covalent linkage between peptide motifs and adaptor domains, which leads to a more stable association of the scaffolded systems and thus bears the potential to further enhance metabolic productivity.

  9. Src-like-adaptor protein (SLAP) differentially regulates normal and oncogenic c-Kit signaling.

    Science.gov (United States)

    Kazi, Julhash U; Agarwal, Shruti; Sun, Jianmin; Bracco, Enrico; Rönnstrand, Lars

    2014-02-01

    The Src-like-adaptor protein (SLAP) is an adaptor protein sharing considerable structural homology with Src. SLAP is expressed in a variety of cells and regulates receptor tyrosine kinase signaling by direct association. In this report, we show that SLAP associates with both wild-type and oncogenic c-Kit (c-Kit-D816V). The association involves the SLAP SH2 domain and receptor phosphotyrosine residues different from those mediating Src interaction. Association of SLAP triggers c-Kit ubiquitylation which, in turn, is followed by receptor degradation. Although SLAP depletion potentiates c-Kit downstream signaling by stabilizing the receptor, it remains non-functional in c-Kit-D816V signaling. Ligand-stimulated c-Kit or c-Kit-D816V did not alter membrane localization of SLAP. Interestingly oncogenic c-Kit-D816V, but not wild-type c-Kit, phosphorylates SLAP on residues Y120, Y258 and Y273. Physical interaction between c-Kit-D816V and SLAP is mandatory for the phosphorylation to take place. Although tyrosine-phosphorylated SLAP does not affect c-Kit-D816V signaling, mutation of these tyrosine sites to phenylalanine can restore SLAP activity. Taken together the data demonstrate that SLAP negatively regulates wild-type c-Kit signaling, but not its oncogenic counterpart, indicating a possible mechanism by which the oncogenic c-Kit bypasses the normal cellular negative feedback control.

  10. Molecular basis of substrate selection by the N-end rule adaptor protein ClpS

    Energy Technology Data Exchange (ETDEWEB)

    Román-Hernández, Giselle; Grant, Robert A.; Sauer, Robert T.; Baker, Tania A.; (HHMI)

    2009-06-19

    The N-end rule is a conserved degradation pathway that relates the stability of a protein to its N-terminal amino acid. Here, we present crystal structures of ClpS, the bacterial N-end rule adaptor, alone and engaged with peptides containing N-terminal phenylalanine, leucine, and tryptophan. These structures, together with a previous structure of ClpS bound to an N-terminal tyrosine, illustrate the molecular basis of recognition of the complete set of primary N-end rule amino acids. In each case, the alpha-amino group and side chain of the N-terminal residue are the major determinants of recognition. The binding pocket for the N-end residue is preformed in the free adaptor, and only small adjustments are needed to accommodate N-end rule residues having substantially different sizes and shapes. M53A ClpS is known to mediate degradation of an expanded repertoire of substrates, including those with N-terminal valine or isoleucine. A structure of Met53A ClpS engaged with an N-end rule tryptophan reveals an essentially wild-type mechanism of recognition, indicating that the Met(53) side chain directly enforces specificity by clashing with and excluding beta-branched side chains. Finally, experimental and structural data suggest mechanisms that make proteins with N-terminal methionine bind very poorly to ClpS, explaining why these high-abundance proteins are not degraded via the N-end rule pathway in the cell.

  11. Alternatively spliced short and long isoforms of adaptor protein intersectin 1 form complexes in mammalian cells

    Directory of Open Access Journals (Sweden)

    Rynditch A. V.

    2012-12-01

    Full Text Available Intersectin 1 (ITSN1 is an adaptor protein involved in membrane trafficking and cell signaling. Long and short isoforms of ITSN1 (ITSN1-L and ITSN1-S are produced by alternative splicing. The aim of our study was to investigate whether ITSN1-L and ITSN1-S could interact in mammalian cells. Methods. During this study we employed immunoprecipitation and confocal microscopy. Results. We have shown that endogenous ITSN1-S co-precipitates with overexpressed ITSN1-L in PC12, 293 and 293T cells. Long and short isoforms of ITSN1 also co-localize in 293T cells. Conclusions. ITSN1-L and ITSN1-S form complexes in mammalian cells.

  12. Unexpected diversity in Shisa-like proteins suggests the importance of their roles as transmembrane adaptors.

    Science.gov (United States)

    Pei, Jimin; Grishin, Nick V

    2012-03-01

    The Shisa family of single-transmembrane proteins is characterized by an N-terminal cysteine-rich domain and a proline-rich C-terminal region. Its founding member, Xenopus Shisa, promotes head development by antagonizing Wnt and FGF signaling. Recently, a mouse brain-specific Shisa protein CKAMP44 (Shisa9) was shown to play an important role in AMPA receptor desensitization. We used sequence similarity searches against protein, genome and EST databases to study the evolutionary origin and phylogenetic distribution of Shisa homologs. In addition to nine Shisa subfamilies in vertebrates, we detected distantly related Shisa homologs that possess an N-terminal domain with six conserved cysteines. These Shisa-like proteins include FAM159 and KIAA1644 mainly from vertebrates, and members from various bilaterian invertebrates and Porifera, suggesting their presence in the last common ancestor of Metazoa. Shisa-like genes have undergone large expansions in Branchiostoma floridae and Saccoglossus kowalevskii, and appear to have been lost in certain insects. Pattern-based searches against eukaryotic proteomes also uncovered several other families of predicted single-transmembrane proteins with a similar cysteine-rich domain. We refer to these proteins (Shisa/Shisa-like, WBP1/VOPP1, CX, DUF2650, TMEM92, and CYYR1) as STMC6 proteins (single-transmembrane proteins with conserved 6 cysteines). STMC6 genes are widespread in Metazoa, with the human genome containing 17 members. Frequent occurrences of PY motifs in STMC6 proteins suggest that most of them could interact with WW-domain-containing proteins, such as the NEDD4 family E3 ubiquitin ligases, and could play critical roles in protein degradation and sorting. STMC6 proteins are likely transmembrane adaptors that regulate membrane proteins such as cell surface receptors.

  13. Receptor tyrosine phosphatase R-PTP-alpha is tyrosine-phosphorylated and associated with the adaptor protein Grb2

    DEFF Research Database (Denmark)

    Su, J; Batzer, A; Sap, J

    1994-01-01

    Receptor tyrosine phosphatases (R-PTPases) have generated interest because of their suspected involvement in cellular signal transduction. The adaptor protein Grb2 has been implicated in coupling receptor tyrosine kinases to Ras. We report that a ubiquitous R-PTPase, R-PTP-alpha, is tyrosine-phos...

  14. PHF6 Degrees of Separation: The Multifaceted Roles of a Chromatin Adaptor Protein

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    Matthew A.M. Todd

    2015-06-01

    Full Text Available The importance of chromatin regulation to human disease is highlighted by the growing number of mutations identified in genes encoding chromatin remodeling proteins. While such mutations were first identified in severe developmental disorders, or in specific cancers, several genes have been implicated in both, including the plant homeodomain finger protein 6 (PHF6 gene. Indeed, germline mutations in PHF6 are the cause of the Börjeson–Forssman–Lehmann X-linked intellectual disability syndrome (BFLS, while somatic PHF6 mutations have been identified in T-cell acute lymphoblastic leukemia (T-ALL and acute myeloid leukemia (AML. Studies from different groups over the last few years have made a significant impact towards a functional understanding of PHF6 protein function. In this review, we summarize the current knowledge of PHF6 with particular emphasis on how it interfaces with a distinct set of interacting partners and its functional roles in the nucleoplasm and nucleolus. Overall, PHF6 is emerging as a key chromatin adaptor protein critical to the regulation of neurogenesis and hematopoiesis.

  15. Losses, Expansions, and Novel Subunit Discovery of Adaptor Protein Complexes in Haptophyte Algae.

    Science.gov (United States)

    Lee, Laura J Y; Klute, Mary J; Herman, Emily K; Read, Betsy; Dacks, Joel B

    2015-11-01

    The phylum Haptophyta (Diaphoratickes) contains marine algae that perform biomineralization, extruding large, distinctive calcium carbonate scales (coccoliths) that completely cover the cell. Coccolith production is an important part of global carbon cycling; however, the membrane trafficking pathway by which they are secreted has not yet been elucidated. In most eukaryotes, post-Golgi membrane trafficking involves five heterotetrameric adaptor protein (AP) complexes, which impart cargo selection specificity. To better understand coccolith secretion, we performed comparative genomic, phylogenetic, and transcriptomic analyses of the AP complexes in Emiliania huxleyi strains 92A, Van556, EH2, and CCMP1516, and related haptophytes Gephyrocapsa oceanica and Isochrysis galbana; the latter has lost the ability to biomineralize. We show that haptophytes have a modified membrane trafficking system (MTS), as we found both AP subunit losses and duplications. Additionally, we identified a single conserved subunit of the AP-related TSET complex, whose expression suggests a functional role in membrane trafficking. Finally, we detected novel alpha adaptin ear and gamma adaptin ear proteins, the first of their kind to be described outside of opisthokonts. These novel ear proteins and the sculpting of the MTS may support the capacity for biomineralization in haptophytes, enhancing their ability to perform this highly specialized form of secretion.

  16. Highly pathogenic avian influenza virus nucleoprotein interacts with TREX complex adaptor protein Aly/REF.

    Science.gov (United States)

    Balasubramaniam, Vinod R M T; Hong Wai, Tham; Ario Tejo, Bimo; Omar, Abdul Rahman; Syed Hassan, Sharifah

    2013-01-01

    We constructed a novel chicken (Gallus gallus) lung cDNA library fused inside yeast acting domain vector (pGADT7). Using yeast two-hybrid screening with highly pathogenic avian influenza (HPAI) nucleoprotein (NP) from the strain (A/chicken/Malaysia/5858/2004(H5N1)) as bait, and the Gallus gallus lung cDNA library as prey, a novel interaction between the Gallus gallus cellular RNA export adaptor protein Aly/REF and the viral NP was identified. This interaction was confirmed and validated with mammalian two hybrid studies and co-immunoprecipitation assay. Cellular localization studies using confocal microscopy showed that NP and Aly/REF co-localize primarily in the nucleus. Further investigations by mammalian two hybrid studies into the binding of NP of other subtypes of influenza virus such as the swine A/New Jersey/1976/H1N1 and pandemic A/Malaysia/854/2009(H1N1) to human Aly/REF, also showed that the NP of these viruses interacts with human Aly/REF. Our findings are also supported by docking studies which showed tight and favorable binding between H5N1 NP and human Aly/REF, using crystal structures from Protein Data Bank. siRNA knockdown of Aly/REF had little effect on the export of HPAI NP and other viral RNA as it showed no significant reduction in virus titer. However, UAP56, another component of the TREX complex, which recruits Aly/REF to mRNA was found to interact even better with H5N1 NP through molecular docking studies. Both these proteins also co-localizes in the nucleus at early infection similar to Aly/REF. Intriguingly, knockdown of UAP56 in A549 infected cells shows significant reduction in viral titer (close to 10 fold reduction). Conclusively, our study have opened new avenues for research of other cellular RNA export adaptors crucial in aiding viral RNA export such as the SRSF3, 9G8 and ASF/SF2 that may play role in influenza virus RNA nucleocytoplasmic transport.

  17. Novel isoform of adaptor protein ITSN1 forms homodimers via its C-terminus

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    Skrypkina I. Ya.

    2011-06-01

    Full Text Available Aim. Previously we have identified a novel isoform of endocytic adaptor protein ITSN1 designated as ITSN122a. Western blot revealed two immunoreactive bands of 120 and 250 kDa that corresponded to ITSN1-22a. The goal of this study was to investigate the possibility of dimer formation by the novel isoform. Methods. Dimerization ability of ITSN1-22a was tested by immunoprecipitation and subsequent Western blot analysis. To specify the region responsible for dimerization, site-directed mutagenesis and truncation analysis were carried out. Inhibition of endocytosis by potassium depletion and EGF stimulation of HEK293 were performed. Results. We have found that ITSN1-22a forms dimers in HEK293 cells. The dimerization of ITSN1-22a was mediated by C-terminal domain. We showed that cysteines C1016 and C1019 were involved in homodimerization. Inhibition of clathrin-mediated endocytosis and mitogen stimulation did not affect ITSN1-22a dimer formation. Conclusions. ITSN1-22a is the only one known ITSN1 isoform, which is capable to form homodimers via disulphide bonds. This could be important for the formation of protein complexes containing ITSN1 molecules.

  18. The adaptor protein FHL2 enhances the cellular innate immune response to influenza A virus infection.

    Science.gov (United States)

    Nordhoff, Carolin; Hillesheim, Andrea; Walter, Beate M; Haasbach, Emanuel; Planz, Oliver; Ehrhardt, Christina; Ludwig, Stephan; Wixler, Viktor

    2012-07-01

    The innate immune response of influenza A virus-infected cells is predominantly mediated by type I interferon-induced proteins. Expression of the interferon β (IFNβ) itself is initiated by accumulating viral RNA and is transmitted by different signalling cascades that feed into activation of the three transcriptional elements located in the IFNβ promoter, AP-1, IRF-3 and NF-κB. FHL2 (four-and-a-half LIM domain protein 2) is an adaptor molecule that shuttles between membrane and nucleus regulating signalling cascades and gene transcription. Here we describe FHL2 as a novel regulator of influenza A virus propagation. Using mouse FHL2 wild-type, knockout and rescued cells and human epithelial cells with different expression levels of FHL2 we showed that FHL2 decreases influenza A virus propagation by regulating the intrinsic cellular antiviral immune response. On virus infection FHL2 translocates into the nucleus, potentiating the IRF-3-dependent transcription of the IFNβ gene.

  19. The adaptor protein MITA links virus-sensing receptors to IRF3 transcription factor activation.

    Science.gov (United States)

    Zhong, Bo; Yang, Yan; Li, Shu; Wang, Yan-Yi; Li, Ying; Diao, Feici; Lei, Caoqi; He, Xiao; Zhang, Lu; Tien, Po; Shu, Hong-Bing

    2008-10-17

    Viral infection triggers activation of transcription factors such as NF-kappaB and IRF3, which collaborate to induce type I interferons (IFNs) and elicit innate antiviral response. Here, we identified MITA as a critical mediator of virus-triggered type I IFN signaling by expression cloning. Overexpression of MITA activated IRF3, whereas knockdown of MITA inhibited virus-triggered activation of IRF3, expression of type I IFNs, and cellular antiviral response. MITA was found to localize to the outer membrane of mitochondria and to be associated with VISA, a mitochondrial protein that acts as an adaptor in virus-triggered signaling. MITA also interacted with IRF3 and recruited the kinase TBK1 to the VISA-associated complex. MITA was phosphorylated by TBK1, which is required for MITA-mediated activation of IRF3. Our results suggest that MITA is a critical mediator of virus-triggered IRF3 activation and IFN expression and further demonstrate the importance of certain mitochondrial proteins in innate antiviral immunity.

  20. Dengue virus targets the adaptor protein MITA to subvert host innate immunity.

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    Chia-Yi Yu

    Full Text Available Dengue is one of the most important arboviral diseases caused by infection of four serotypes of dengue virus (DEN. We found that activation of interferon regulatory factor 3 (IRF3 triggered by viral infection and by foreign DNA and RNA stimulation was blocked by DEN-encoded NS2B3 through a protease-dependent mechanism. The key adaptor protein in type I interferon pathway, human mediator of IRF3 activation (MITA but not the murine homologue MPYS, was cleaved in cells infected with DEN-1 or DEN-2 and with expression of the enzymatically active protease NS2B3. The cleavage site of MITA was mapped to LRR↓(96G and the function of MITA was suppressed by dengue protease. DEN replication was reduced with overexpression of MPYS but not with MITA, while DEN replication was enhanced by MPYS knockdown, indicating an antiviral role of MITA/MPYS against DEN infection. The involvement of MITA in DEN-triggered innate immune response was evidenced by reduction of IRF3 activation and IFN induction in cells with MITA knockdown upon DEN-2 infection. NS2B3 physically interacted with MITA, and the interaction and cleavage of MITA could be further enhanced by poly(dA:dT stimulation. Thus, we identified MITA as a novel host target of DEN protease and provide the molecular mechanism of how DEN subverts the host innate immunity.

  1. Dengue virus targets the adaptor protein MITA to subvert host innate immunity.

    Science.gov (United States)

    Yu, Chia-Yi; Chang, Tsung-Hsien; Liang, Jian-Jong; Chiang, Ruei-Lin; Lee, Yi-Ling; Liao, Ching-Len; Lin, Yi-Ling

    2012-01-01

    Dengue is one of the most important arboviral diseases caused by infection of four serotypes of dengue virus (DEN). We found that activation of interferon regulatory factor 3 (IRF3) triggered by viral infection and by foreign DNA and RNA stimulation was blocked by DEN-encoded NS2B3 through a protease-dependent mechanism. The key adaptor protein in type I interferon pathway, human mediator of IRF3 activation (MITA) but not the murine homologue MPYS, was cleaved in cells infected with DEN-1 or DEN-2 and with expression of the enzymatically active protease NS2B3. The cleavage site of MITA was mapped to LRR↓(96)G and the function of MITA was suppressed by dengue protease. DEN replication was reduced with overexpression of MPYS but not with MITA, while DEN replication was enhanced by MPYS knockdown, indicating an antiviral role of MITA/MPYS against DEN infection. The involvement of MITA in DEN-triggered innate immune response was evidenced by reduction of IRF3 activation and IFN induction in cells with MITA knockdown upon DEN-2 infection. NS2B3 physically interacted with MITA, and the interaction and cleavage of MITA could be further enhanced by poly(dA:dT) stimulation. Thus, we identified MITA as a novel host target of DEN protease and provide the molecular mechanism of how DEN subverts the host innate immunity.

  2. The motogenic and mitogenic responses to HGF are amplified by the Shc adaptor protein

    DEFF Research Database (Denmark)

    Pelicci, G; Giordano, S; Zhen, Z

    1995-01-01

    The receptor of Hepatocyte Growth Factor-Scatter Factor (HGF) is a tyrosine kinase which regulates cell motility and growth. After ligand-induced tyrosine phosphorylation, the HGF receptor associates with the Shc adaptor, via the SH2 domain. Site-directed mutagenesis of the HGF receptor indicates...

  3. Molecular basis for the specific recognition of the metazoan cyclic GMP-AMP by the innate immune adaptor protein STING.

    Science.gov (United States)

    Shi, Heping; Wu, Jiaxi; Chen, Zhijian J; Chen, Chuo

    2015-07-21

    Cyclic GMP-AMP containing a unique combination of mixed phosphodiester linkages (2'3'-cGAMP) is an endogenous second messenger molecule that activates the type-I IFN pathway upon binding to the homodimer of the adaptor protein STING on the surface of endoplasmic reticulum membrane. However, the preferential binding of the asymmetric ligand 2'3'-cGAMP to the symmetric dimer of STING represents a physicochemical enigma. Here we show that 2'3'-cGAMP, but not its linkage isomers, adopts an organized free-ligand conformation that resembles the STING-bound conformation and pays low entropy and enthalpy costs in converting into the active conformation. Our results demonstrate that analyses of free-ligand conformations can be as important as analyses of protein conformations in understanding protein-ligand interactions.

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

    DEFF Research Database (Denmark)

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

    1996-01-01

    Receptor protein-tyrosine phosphatase RPTPalpha is found associated in vivo with the adaptor protein Grb2. Formation of this complex, which contains no detectable levels of Sos, is known to depend on a C-terminal phosphorylated tyrosine residue (Tyr798) in RPTPalpha and on the Src homology (SH) 2...

  5. Src-like adaptor protein (SLAP) is upregulated in antigen-stimulated mast cells and acts as a negative regulator.

    Science.gov (United States)

    Park, Seung-Kiel; Qiao, Huihong; Beaven, Michael A

    2009-06-01

    Our studies in the RBL-2H3 mast cell line suggest that responses to antigen (Ag) are negatively modulated through upregulation of Src-like adaptor protein (SLAP). Ag stimulation of RBL-2H3 cells leads to increased levels of SLAP (but not SLAP2) transcripts and protein over a period of several hours. The effects of pharmacologic inhibitors indicate that the upregulation of SLAP is dependent on multiple signaling pathways. Knockdown of SLAP with anti-SLAP siRNA is associated with enhanced phosphorylation of Syk, the linker for activation of T cells (LAT), phospholipase C gamma, MAP kinases, and various transcription factors. Production of IL-3 and MCP-1, but not degranulation, is also enhanced. The upregulation of SLAP may thus serve to limit the duration of cytokine production in Ag-stimulated cells.

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

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    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.

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

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    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

  8. Regulation of in vitro and in vivo immune functions by the cytosolic adaptor protein SKAP-HOM.

    Science.gov (United States)

    Togni, M; Swanson, K D; Reimann, S; Kliche, S; Pearce, A C; Simeoni, L; Reinhold, D; Wienands, J; Neel, B G; Schraven, B; Gerber, A

    2005-09-01

    SKAP-HOM is a cytosolic adaptor protein representing a specific substrate for the Src family protein tyrosine kinase Fyn. Previously, several groups have provided experimental evidence that SKAP-HOM (most likely in cooperation with the cytosolic adaptor protein ADAP) is involved in regulating leukocyte adhesion. To further assess the physiological role of SKAP-HOM, we investigated the immune system of SKAP-HOM-deficient mice. Our data show that T-cell responses towards a variety of stimuli are unaffected in the absence of SKAP-HOM. Similarly, B-cell receptor (BCR)-mediated total tyrosine phosphorylation and phosphorylation of Erk, p38, and JNK, as well as immunoreceptor-mediated Ca(2+) responses, are normal in SKAP-HOM(-/-) animals. However, despite apparently normal membrane-proximal signaling events, BCR-mediated proliferation is strongly attenuated in the absence of SKAP-HOM(-/-). In addition, adhesion of activated B cells to fibronectin (a ligand for beta1 integrins) as well as to ICAM-1 (a ligand for beta2 integrins) is strongly reduced. In vivo, the loss of SKAP-HOM results in a less severe clinical course of experimental autoimmune encephalomyelitis following immunization of mice with the encephalitogenic peptide of MOG (myelin oligodendrocyte glycoprotein). This is accompanied by strongly reduced serum levels of MOG-specific antibodies and lower MOG-specific T-cell responses. In summary, our data suggest that SKAP-HOM is required for proper activation of the immune system, likely by regulating the cross-talk between immunoreceptors and integrins.

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

    NARCIS (Netherlands)

    Hovens, Iris; Nyakas, Csaba; Schoemaker, Regina

    2014-01-01

    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 analy

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

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    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.

  11. The ubiquitin ligase RNF5 regulates antiviral responses by mediating degradation of the adaptor protein MITA.

    Science.gov (United States)

    Zhong, Bo; Zhang, Lu; Lei, Caoqi; Li, Ying; Mao, Ai-Ping; Yang, Yan; Wang, Yan-Yi; Zhang, Xiao-Lian; Shu, Hong-Bing

    2009-03-20

    Viral infection activates transcription factors NF-kappaB and IRF3, which collaborate to induce type I interferons (IFNs) and elicit innate antiviral response. MITA (also known as STING) has recently been identified as an adaptor that links virus-sensing receptors to IRF3 activation. Here, we showed that the E3 ubiquitin ligase RNF5 interacted with MITA in a viral-infection-dependent manner. Overexpression of RNF5 inhibited virus-triggered IRF3 activation, IFNB1 expression, and cellular antiviral response, whereas knockdown of RNF5 had opposite effects. RNF5 targeted MITA at Lys150 for ubiquitination and degradation after viral infection. Both MITA and RNF5 were located at the mitochondria and endoplasmic reticulum (ER) and viral infection caused their redistribution to the ER and mitochondria, respectively. We further found that virus-induced ubiquitination and degradation of MITA by RNF5 occurred at the mitochondria. These findings suggest that RNF5 negatively regulates virus-triggered signaling by targeting MITA for ubiquitination and degradation at the mitochondria.

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    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.

  14. Role of adaptor proteins and clathrin in the trafficking of human kidney anion exchanger 1 (kAE1) to the cell surface.

    Science.gov (United States)

    Junking, Mutita; Sawasdee, Nunghathai; Duangtum, Natapol; Cheunsuchon, Boonyarit; Limjindaporn, Thawornchai; Yenchitsomanus, Pa-thai

    2014-07-01

    Kidney anion exchanger 1 (kAE1) plays an important role in acid-base homeostasis by mediating chloride/bicarbornate (Cl-/HCO3-) exchange at the basolateral membrane of α-intercalated cells in the distal nephron. Impaired intracellular trafficking of kAE1 caused by mutations of SLC4A1 encoding kAE1 results in kidney disease - distal renal tubular acidosis (dRTA). However, it is not known how the intracellular sorting and trafficking of kAE1 from trans-Golgi network (TGN) to the basolateral membrane occurs. Here, we studied the role of basolateral-related sorting proteins, including the mu1 subunit of adaptor protein (AP) complexes, clathrin and protein kinase D, on kAE1 trafficking in polarized and non-polarized kidney cells. By using RNA interference, co-immunoprecipitation, yellow fluorescent protein-based protein fragment complementation assays and immunofluorescence staining, we demonstrated that AP-1 mu1A, AP-3 mu1, AP-4 mu1 and clathrin (but not AP-1 mu1B, PKD1 or PKD2) play crucial roles in intracellular sorting and trafficking of kAE1. We also demonstrated colocalization of kAE1 and basolateral-related sorting proteins in human kidney tissues by double immunofluorescence staining. These findings indicate that AP-1 mu1A, AP-3 mu1, AP-4 mu1 and clathrin are required for kAE1 sorting and trafficking from TGN to the basolateral membrane of acid-secreting α-intercalated cells.

  15. Rap1-GTP-interacting Adaptor Molecule (RIAM) Protein Controls Invasion and Growth of Melanoma Cells*

    Science.gov (United States)

    Hernández-Varas, Pablo; Coló, Georgina P.; Bartolomé, Ruben A.; Paterson, Andrew; Medraño-Fernández, Iria; Arellano-Sánchez, Nohemí; Cabañas, Carlos; Sánchez-Mateos, Paloma; Lafuente, Esther M.; Boussiotis, Vassiliki A.; Strömblad, Staffan; Teixidó, Joaquin

    2011-01-01

    The Mig-10/RIAM/lamellipodin (MRL) family member Rap1-GTP-interacting adaptor molecule (RIAM) interacts with active Rap1, a small GTPase that is frequently activated in tumors such as melanoma and prostate cancer. We show here that RIAM is expressed in metastatic human melanoma cells and that both RIAM and Rap1 are required for BLM melanoma cell invasion. RIAM silencing in melanoma cells led to inhibition of tumor growth and to delayed metastasis in a severe combined immunodeficiency xenograft model. Defective invasion of RIAM-silenced melanoma cells arose from impairment in persistent cell migration directionality, which was associated with deficient activation of a Vav2-RhoA-ROCK-myosin light chain pathway. Expression of constitutively active Vav2 and RhoA in cells depleted for RIAM partially rescued their invasion, indicating that Vav2 and RhoA mediate RIAM function. These results suggest that inhibition of cell invasion in RIAM-silenced melanoma cells is likely based on altered cell contractility and cell polarization. Furthermore, we show that RIAM depletion reduces β1 integrin-dependent melanoma cell adhesion, which correlates with decreased activation of both Erk1/2 MAPK and phosphatidylinositol 3-kinase, two central molecules controlling cell growth and cell survival. In addition to causing inhibition of cell proliferation, RIAM silencing led to higher susceptibility to cell apoptosis. Together, these data suggest that defective activation of these kinases in RIAM-silenced cells could account for inhibition of melanoma cell growth and that RIAM might contribute to the dissemination of melanoma cells. PMID:21454517

  16. Positive and negative regulation of FcepsilonRI-mediated signaling by the adaptor protein LAB/NTAL.

    Science.gov (United States)

    Zhu, Minghua; Liu, Yan; Koonpaew, Surapong; Granillo, Olivia; Zhang, Weiguo

    2004-10-18

    Linker for activation of B cells (LAB, also called NTAL; a product of wbscr5 gene) is a newly identified transmembrane adaptor protein that is expressed in B cells, NK cells, and mast cells. Upon BCR activation, LAB is phosphorylated and interacts with Grb2. LAB is capable of rescuing thymocyte development in LAT-deficient mice. To study the in vivo function of LAB, LAB-deficient mice were generated. Although disruption of the Lab gene did not affect lymphocyte development, it caused mast cells to be hyperresponsive to stimulation via the FcepsilonRI, evidenced by enhanced Erk activation, calcium mobilization, degranulation, and cytokine production. These data suggested that LAB negatively regulates mast cell function. However, mast cells that lacked both linker for activation of T cells (LAT) and LAB proteins had a more severe block in FcepsilonRI-mediated signaling than LAT(-/-) mast cells, demonstrating that LAB also shares a redundant function with LAT to play a positive role in FcepsilonRI-mediated signaling.

  17. The adaptor protein TRAF3 inhibits interleukin-6 receptor signaling in B cells to limit plasma cell development.

    Science.gov (United States)

    Lin, Wai W; Yi, Zuoan; Stunz, Laura L; Maine, Christian J; Sherman, Linda A; Bishop, Gail A

    2015-09-01

    Tumor necrosis factor receptor-associated factor 3 (TRAF3) is an adaptor protein that inhibits signaling by CD40 and by the receptor for B cell-activating factor (BAFF) and negatively regulates homeostatic B cell survival. Loss-of-function mutations in TRAF3 are associated with human B cell malignancies, in particular multiple myeloma. The cytokine interleukin-6 (IL-6) supports the differentiation and survival of normal and neoplastic plasma cells. We found that mice with a deficiency in TRAF3 specifically in B cells (B-Traf3(-/-) mice) had about twice as many plasma cells as did their littermate controls. TRAF3-deficient B cells had enhanced responsiveness to IL-6, and genetic loss of IL-6 in B-Traf3(-/-) mice restored their plasma cell numbers to normal. TRAF3 inhibited IL-6 receptor (IL-6R)-mediated signaling by facilitating the association of PTPN22 (a nonreceptor protein tyrosine phosphatase) with the kinase Janus-activated kinase 1 (Jak1), which in turn blocked phosphorylation of the transcription factor STAT3 (signal transducer and activator of transcription 3). Consistent with these results, the number of plasma cells in the PTPN22-deficient mice was increased compared to that in the wild-type mice. Our findings identify TRAF3 and PTPN22 as inhibitors of IL-6R signaling in B cells and reveal a previously uncharacterized role for TRAF3 in the regulation of plasma cell differentiation.

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

    Directory of Open Access Journals (Sweden)

    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.

  19. Downregulation of the NHE3-binding PDZ-adaptor protein PDZK1 expression during cytokine-induced inflammation in interleukin-10-deficient mice.

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    Henrike Lenzen

    Full Text Available BACKGROUND: Impaired salt and water absorption is an important feature in the pathogenesis of diarrhea in inflammatory bowel disease (IBD. We analyzed the expression of proinflammatory cytokines in the infiltrating immune cells and the function and expression of the Na(+/H(+ exchanger isoform 3 (NHE3 and its regulatory PDZ-adaptor proteins NHERF1, NHERF2, and PDZK1 in the colon of interleukin-10-deficient (IL-10(-/- mice. METHODOLOGY/PRINCIPAL FINDINGS: Gene and protein expression were analyzed by real-time reverse transcription polymerase chain reaction (qRT-PCR, in situ RT-PCR, and immunohistochemistry. NHE3 activity was measured fluorometrically in apical enterocytes within isolated colonic crypts. Mice developed chronic colitis characterized by a typical immune cell infiltration composed of T-lymphocytes and macrophages, with high levels of gene and protein expression of the proinflammatory cytokines interleukin-1β and tumor necrosis factor-α. In parallel, inducible nitric oxide synthase expression was increased while procaspase 3 expression was unaffected. Interferon-γ expression remained low. Although acid-activated NHE3 activity was significantly decreased, the inflammatory process did not affect its gene and protein expression or its abundance and localization in the apical membrane. However, expression of the PDZ-adaptor proteins NHERF2 and PDZK1 was downregulated. NHERF1 expression was unchanged. In a comparative analysis we observed the PDZK1 downregulation also in the DSS (dextran sulphate sodium model of colitis. CONCLUSIONS/SIGNIFICANCE: The impairment of the absorptive function of the inflamed colon in the IL-10(-/- mouse, in spite of unaltered NHE3 expression and localization, is accompanied by the downregulation of the NHE3-regulatory PDZ adaptors NHERF2 and PDZK1. We propose that the downregulation of PDZ-adaptor proteins may be an important factor leading to NHE3 dysfunction and diarrhea in the course of the cytokine

  20. The CRKL gene encoding an adaptor protein is amplified, overexpressed, and a possible therapeutic target in gastric cancer

    Directory of Open Access Journals (Sweden)

    Natsume Hiroko

    2012-07-01

    Full Text Available Abstract Background Genomic DNA amplification is a genetic factor involved in cancer, and some oncogenes, such as ERBB2, are highly amplified in gastric cancer. We searched for the possible amplification of other genes in gastric cancer. Methods and Results A genome-wide single nucleotide polymorphism microarray analysis was performed using three cell lines of differentiated gastric cancers, and 22 genes (including ERBB2 in five highly amplified chromosome regions (with a copy number of more than 6 were identified. Particular attention was paid to the CRKL gene, the product of which is an adaptor protein containing Src homology 2 and 3 (SH2/SH3 domains. An extremely high CRKL copy number was confirmed in the MKN74 gastric cancer cell line using fluorescence in situ hybridization (FISH, and a high level of CRKL expression was also observed in the cells. The RNA-interference-mediated knockdown of CRKL in MKN74 disclosed the ability of CRKL to upregulate gastric cell proliferation. An immunohistochemical analysis revealed that CRKL protein was overexpressed in 24.4% (88/360 of the primary gastric cancers that were analyzed. The CRKL copy number was also examined in 360 primary gastric cancers using a FISH analysis, and CRKL amplification was found to be associated with CRKL overexpression. Finally, we showed that MKN74 cells with CRKL amplification were responsive to the dual Src/BCR-ABL kinase inhibitor BMS354825, likely via the inhibition of CRKL phosphorylation, and that the proliferation of MKN74 cells was suppressed by treatment with a CRKL-targeting peptide. Conclusion These results suggested that CRKL protein is overexpressed in a subset of gastric cancers and is associated with CRKL amplification in gastric cancer. Furthermore, our results suggested that CRKL protein has the ability to regulate gastric cell proliferation and has the potential to serve as a molecular therapy target for gastric cancer.

  1. RECOMBINANT LENTIVIRUS-MEDIATED SILENCING OF ADAPTOR PROTEIN RUK/CIN85 EXPRESSION INFLUENCES BIOLOGICAL RESPONSES OF TUMOR CELLS

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    A. A. Samoylenko

    2013-08-01

    Full Text Available Ruk/CIN85 is an adaptor protein that plays important roles in the regulation of cellular processes such as cell death, proliferation and motility. It was recently shown that overexpression of Ruk/CIN85 increases the oncogenic potential of human breast adenocarcinoma MCF-7 cells. It was the aim of the present study to investigate whether inhibition of Ruk/CIN85 expression has an effect on the biological properties of the cells. In order to down-regulate Ruk/CIN85 expression of small interfering RNA-based approach was used. For down-regulation of Ruk/CIN85 lentiviral constructs encoding Ruk/CIN85-specific small hairpin RNA sequences were generated. By using the obtained recombinant lentiviruses it was shown that inhibition of Ruk/CIN85 expression influences biological properties (motility, proliferation, ABCG2 expression, and ROS generation of various tumour cell types such as human breast adenocarcinoma MCF-7, human colorectal adenocarcinoma HT-29, and Lewis mouse lung carcinoma cells.

  2. Nuclear IKKbeta is an adaptor protein for IkappaBalpha ubiquitination and degradation in UV-induced NF-kappaB activation.

    Science.gov (United States)

    Tsuchiya, Yoshihiro; Asano, Tomoichiro; Nakayama, Keiko; Kato, Tomohisa; Karin, Michael; Kamata, Hideaki

    2010-08-27

    Proinflammatory cytokines activate NF-kappaB using the IkappaB kinase (IKK) complex that phosphorylates inhibitory proteins (IkappaBs) at N-terminal sites resulting in their ubiquitination and degradation in the cytoplasm. Although ultraviolet (UV) irradiation does not lead to IKK activity, it activates NF-kappaB by an unknown mechanism through IkappaBalpha degradation without N-terminal phosphorylation. Here, we describe an adaptor function of nuclear IKKbeta in UV-induced IkappaBalpha degradation. UV irradiation induces the nuclear translocation of IkappaBalpha and association with IKKbeta, which constitutively interacts with beta-TrCP through heterogeneous ribonucleoprotein-U (hnRNP-U) leading to IkappaBalpha ubiquitination and degradation. Furthermore, casein kinase 2 (CK2) and p38 associate with IKKbeta and promote IkappaBalpha degradation by phosphorylation at C-terminal sites. Thus, nuclear IKKbeta acts as an adaptor protein for IkappaBalpha degradation in UV-induced NF-kappaB activation. NF-kappaB activated by the nuclear IKKbeta adaptor protein suppresses anti-apoptotic gene expression and promotes UV-induced cell death.

  3. Molecular analysis of the prostacyclin receptor's interaction with the PDZ1 domain of its adaptor protein PDZK1.

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    Gabriel Birrane

    Full Text Available The prostanoid prostacyclin, or prostaglandin I2, plays an essential role in many aspects of cardiovascular disease. The actions of prostacyclin are mainly mediated through its activation of the prostacyclin receptor or, in short, the IP. In recent studies, the cytoplasmic carboxy-terminal domain of the IP was shown to bind several PDZ domains of the multi-PDZ adaptor PDZK1. The interaction between the two proteins was found to enhance cell surface expression of the IP and to be functionally important in promoting prostacyclin-induced endothelial cell migration and angiogenesis. To investigate the interaction of the IP with the first PDZ domain (PDZ1 of PDZK1, we generated a nine residue peptide (KK(411IAACSLC(417 containing the seven carboxy-terminal amino acids of the IP and measured its binding affinity to a recombinant protein corresponding to PDZ1 by isothermal titration calorimetry. We determined that the IP interacts with PDZ1 with a binding affinity of 8.2 µM. Using the same technique, we also determined that the farnesylated form of carboxy-terminus of the IP does not bind to PDZ1. To understand the molecular basis of these findings, we solved the high resolution crystal structure of PDZ1 bound to a 7-residue peptide derived from the carboxy-terminus of the non-farnesylated form of IP ((411IAACSLC(417. Analysis of the structure demonstrates a critical role for the three carboxy-terminal amino acids in establishing a strong interaction with PDZ1 and explains the inability of the farnesylated form of IP to interact with the PDZ1 domain of PDZK1 at least in vitro.

  4. Role of Crk Adaptor Proteins in Cellular Migration and Invasion in Human Breast Cancer

    Science.gov (United States)

    2007-03-01

    adapter protein. Mol Cell Biol. 19(12):8169-79. 22. Cabodi S, Tinnirello A, Di Stefano P, Bisaro B, Ambrosino E, Castellano I, Sapino A, Arisio R...Vande Woude GF. Met, metastasis, motility and more. Nat Rev Mol Cell Biol 2003;4:915 –25. 3. Rosario M, Birchmeier W. How to make tubes: signaling by

  5. Invertebrate and vertebrate class III myosins interact with MORN repeat-containing adaptor proteins.

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    Kirk L Mecklenburg

    Full Text Available In Drosophila photoreceptors, the NINAC-encoded myosin III is found in a complex with a small, MORN-repeat containing, protein Retinophilin (RTP. Expression of these two proteins in other cell types showed NINAC myosin III behavior is altered by RTP. NINAC deletion constructs were used to map the RTP binding site within the proximal tail domain of NINAC. In vertebrates, the RTP ortholog is MORN4. Co-precipitation experiments demonstrated that human MORN4 binds to human myosin IIIA (MYO3A. In COS7 cells, MORN4 and MYO3A, but not MORN4 and MYO3B, co-localize to actin rich filopodia extensions. Deletion analysis mapped the MORN4 binding to the proximal region of the MYO3A tail domain. MYO3A dependent MORN4 tip localization suggests that MYO3A functions as a motor that transports MORN4 to the filopodia tips and MORN4 may enhance MYO3A tip localization by tethering it to the plasma membrane at the protrusion tips. These results establish conserved features of the RTP/MORN4 family: they bind within the tail domain of myosin IIIs to control their behavior.

  6. The Shc family protein adaptor, Rai, negatively regulates T cell antigen receptor signaling by inhibiting ZAP-70 recruitment and activation.

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    Micol Ferro

    Full Text Available Rai/ShcC is a member of the Shc family of protein adaptors expressed with the highest abundance in the central nervous system, where it exerts a protective function by coupling neurotrophic receptors to the PI3K/Akt survival pathway. Rai is also expressed, albeit at lower levels, in other cell types, including T and B lymphocytes. We have previously reported that in these cells Rai attenuates antigen receptor signaling, thereby impairing not only cell proliferation but also, opposite to neurons, cell survival. Here we have addressed the mechanism underlying the inhibitory activity of Rai on TCR signaling. We show that Rai interferes with the TCR signaling cascade one of the earliest steps--recruitment of the initiating kinase ZAP-70 to the phosphorylated subunit of the TCR/CD3 complex, which results in a generalized dampening of the downstream signaling events. The inhibitory activity of Rai is associated to its inducible recruitment to phosphorylated CD3, which occurs in the physiological signaling context of the immune synapse. Rai is moreover found as a pre-assembled complex with ZAP-70 and also constitutively interacts with the regulatory p85 subunit of PI3K, similar to neuronal cells, notwithstanding the opposite biological outcome, i.e. impairment of PI-3K/Akt activation. The data highlight the ability of Rai to establish interactions with the TCR and key signaling mediators which, either directly (e.g. by inhibiting ZAP-70 recruitment to the TCR or sequestering ZAP-70/PI3K in the cytosol or indirectly (e.g. by promoting the recruitment of effectors responsible for signal extinction prevent full triggering of the TCR signaling cascade.

  7. New function of the adaptor protein SH2B1 in brain-derived neurotrophic factor-induced neurite outgrowth.

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    Chien-Hung Shih

    Full Text Available Neurite outgrowth is an essential process for the establishment of the nervous system. Brain-derived neurotrophic factor (BDNF binds to its receptor TrkB and regulates axonal and dendritic morphology of neurons through signal transduction and gene expression. SH2B1 is a signaling adaptor protein that regulates cellular signaling in various physiological processes. The purpose of this study is to investigate the role of SH2B1 in the development of the central nervous system. In this study, we show that knocking down SH2B1 reduces neurite formation of cortical neurons whereas overexpression of SH2B1β promotes the development of hippocampal neurons. We further demonstrate that SH2B1β promotes BDNF-induced neurite outgrowth and signaling using the established PC12 cells stably expressing TrkB, SH2B1β or SH2B1β mutants. Our data indicate that overexpressing SH2B1β enhances BDNF-induced MEK-ERK1/2, and PI3K-AKT signaling pathways. Inhibition of MEK-ERK1/2 and PI3K-AKT pathways by specific inhibitors suggest that these two pathways are required for SH2B1β-promoted BDNF-induced neurite outgrowth. Moreover, SH2B1β enhances BDNF-stimulated phosphorylation of signal transducer and activator of transcription 3 at serine 727. Finally, our data indicate that the SH2 domain and tyrosine phosphorylation of SH2B1β contribute to BDNF-induced signaling pathways and neurite outgrowth. Taken together, these findings demonstrate that SH2B1β promotes BDNF-induced neurite outgrowth through enhancing pathways involved MEK-ERK1/2 and PI3K-AKT.

  8. Structural and Functional Characterization of Cargo-Binding Sites on the μ4-Subunit of Adaptor Protein Complex 4

    Science.gov (United States)

    Ross, Breyan H.; Lin, Yimo; Corales, Esteban A.; Burgos, Patricia V.; Mardones, Gonzalo A.

    2014-01-01

    Adaptor protein (AP) complexes facilitate protein trafficking by playing key roles in the selection of cargo molecules to be sorted in post-Golgi compartments. Four AP complexes (AP-1 to AP-4) contain a medium-sized subunit (μ1-μ4) that recognizes YXXØ-sequences (Ø is a bulky hydrophobic residue), which are sorting signals in transmembrane proteins. A conserved, canonical region in μ subunits mediates recognition of YXXØ-signals by means of a critical aspartic acid. Recently we found that a non-canonical YXXØ-signal on the cytosolic tail of the Alzheimer's disease amyloid precursor protein (APP) binds to a distinct region of the μ4 subunit of the AP-4 complex. In this study we aimed to determine the functionality of both binding sites of μ4 on the recognition of the non-canonical YXXØ-signal of APP. We found that substitutions in either binding site abrogated the interaction with the APP-tail in yeast-two hybrid experiments. Further characterization by isothermal titration calorimetry showed instead loss of binding to the APP signal with only the substitution R283D at the non-canonical site, in contrast to a decrease in binding affinity with the substitution D190A at the canonical site. We solved the crystal structure of the C-terminal domain of the D190A mutant bound to this non-canonical YXXØ-signal. This structure showed no significant difference compared to that of wild-type μ4. Both differential scanning fluorimetry and limited proteolysis analyses demonstrated that the D190A substitution rendered μ4 less stable, suggesting an explanation for its lower binding affinity to the APP signal. Finally, in contrast to overexpression of the D190A mutant, and acting in a dominant-negative manner, overexpression of μ4 with either a F255A or a R283D substitution at the non-canonical site halted APP transport at the Golgi apparatus. Together, our analyses support that the functional recognition of the non-canonical YXXØ-signal of APP is limited to the non

  9. Role of Crk Adaptor Proteins in Cellular Migration and Invasion in Human Breast Cancer

    Science.gov (United States)

    2009-03-01

    0.0001349 1.280209 0.00657 cholesterol 25- hydroxylase ZNF539 2.225650467 0.0042638 1.295457 0.03133 zinc finger protein 254 PRSS7 2.233104326 0.0239284...4.98281  6.27E‐07  Toll‐like receptor signaling pathway  ‐3.51463  0.00044  Caprolactam degradation  ‐0.99768  0.318433  Phenylalanine , tyrosine and...Escherichia coli infection – EHEC  ‐1.38214  0.166928  Phenylalanine  metabolism  ‐2.08135  0.037401  Pathogenic Escherichia coli infection – EPEC  ‐0.48134

  10. Src-like adaptor protein 2 (SLAP2) binds to and inhibits FLT3 signaling

    Science.gov (United States)

    Moharram, Sausan A.; Chougule, Rohit A.; Su, Xianwei; Li, Tianfeng; Sun, Jianmin; Zhao, Hui; Rönnstrand, Lars; Kazi, Julhash U.

    2016-01-01

    Fms-like tyrosine kinase (FLT3) is a frequently mutated oncogene in acute myeloid leukemia (AML). FLT3 inhibitors display promising results in a clinical setting, but patients relapse after short-term treatment due to the development of resistant disease. Therefore, a better understanding of FLT3 downstream signal transduction pathways will help to identify an alternative target for the treatment of AML patients carrying oncogenic FLT3. Activation of FLT3 results in phosphorylation of FLT3 on several tyrosine residues that recruit SH2 domain-containing signaling proteins. We screened a panel of SH2 domain-containing proteins and identified SLAP2 as a potent interacting partner of FLT3. We demonstrated that interaction occurs when FLT3 is activated, and also, an intact SH2 domain of SLAP2 is required for binding. SLAP2 binding sites in FLT3 mainly overlap with those of SRC. SLAP2 over expression in murine proB cells or myeloid cells inhibited oncogenic FLT3-ITD-mediated cell proliferation and colony formation in vitro, and tumor formation in vivo. Microarray analysis suggests that higher SLAP2 expression correlates with a gene signature similar to that of loss of oncogene function. Furthermore, FLT3-ITD positive AML patients with higher SLAP2 expression displayed better prognosis compared to those with lower expression of SLAP2. Expression of SLAP2 blocked FLT3 downstream signaling cascades including AKT, ERK, p38 and STAT5. Finally, SLAP2 accelerated FLT3 degradation through enhanced ubiquitination. Collectively, our data suggest that SLAP2 acts as a negative regulator of FLT3 signaling and therefore, modulation of SLAP2 expression levels may provide an alternative therapeutic approach for FLT3-ITD positive AML. PMID:27458164

  11. Studying multisite binary and ternary protein interactions by global analysis of isothermal titration calorimetry data in SEDPHAT: application to adaptor protein complexes in cell signaling.

    Science.gov (United States)

    Houtman, Jon C D; Brown, Patrick H; Bowden, Brent; Yamaguchi, Hiroshi; Appella, Ettore; Samelson, Lawrence E; Schuck, Peter

    2007-01-01

    Multisite interactions and the formation of ternary or higher-order protein complexes are ubiquitous features of protein interactions. Cooperativity between different ligands is a hallmark for information transfer, and is frequently critical for the biological function. We describe a new computational platform for the global analysis of isothermal titration calorimetry (ITC) data for the study of binary and ternary multisite interactions, implemented as part of the public domain multimethod analysis software SEDPHAT. The global analysis of titrations performed in different orientations was explored, and the potential for unraveling cooperativity parameters in multisite interactions was assessed in theory and experiment. To demonstrate the practical potential and limitations of global analyses of ITC titrations for the study of cooperative multiprotein interactions, we have examined the interactions of three proteins that are critical for signal transduction after T-cell activation, LAT, Grb2, and Sos1. We have shown previously that multivalent interactions between these three molecules promote the assembly of large multiprotein complexes important for T-cell receptor activation. By global analysis of the heats of binding observed in sets of ITC injections in different orientations, which allowed us to follow the formation of binary and ternary complexes, we observed negative and positive cooperativity that may be important to control the pathway of assembly and disassembly of adaptor protein particles.

  12. Cargo adaptors: structures illuminate mechanisms regulating vesicle biogenesis.

    Science.gov (United States)

    Paczkowski, Jon E; Richardson, Brian C; Fromme, J Christopher

    2015-07-01

    Cargo adaptors sort transmembrane protein cargos into nascent vesicles by binding directly to their cytosolic domains. Recent studies have revealed previously unappreciated roles for cargo adaptors and regulatory mechanisms governing their function. The adaptor protein (AP)-1 and AP-2 clathrin adaptors switch between open and closed conformations that ensure they function at the right place at the right time. The exomer cargo adaptor has a direct role in remodeling the membrane for vesicle fission. Several different cargo adaptors functioning in distinct trafficking pathways at the Golgi are similarly regulated through bivalent binding to the ADP-ribosylation factor 1 (Arf1) GTPase, potentially enabling regulation by a threshold concentration of Arf1. Taken together, these studies highlight that cargo adaptors do more than just adapt cargos.

  13. The Adaptor Protein Myd88 Is a Key Signaling Molecule in the Pathogenesis of Irinotecan-Induced Intestinal Mucositis.

    Directory of Open Access Journals (Sweden)

    Deysi V T Wong

    Full Text Available Intestinal mucositis is a common side effect of irinotecan-based anticancer regimens. Mucositis causes cell damage, bacterial/endotoxin translocation and production of cytokines including IL-1 and IL-18. These molecules and toll-like receptors (TLRs activate a common signaling pathway that involves the Myeloid Differentiation adaptor protein, MyD88, whose role in intestinal mucositis is unknown. Then, we evaluated the involvement of TLRs and MyD88 in the pathogenesis of irinotecan-induced intestinal mucositis. MyD88-, TLR2- or TLR9-knockout mice and C57BL/6 (WT mice were given either saline or irinotecan (75 mg/kg, i.p. for 4 days. On day 7, animal survival, diarrhea and bacteremia were assessed, and following euthanasia, samples of the ileum were obtained for morphometric analysis, myeloperoxidase (MPO assay and measurement of pro-inflammatory markers. Irinotecan reduced the animal survival (50% and induced a pronounced diarrhea, increased bacteremia, neutrophil accumulation in the intestinal tissue, intestinal damage and more than twofold increased expression of MyD88 (200%, TLR9 (400%, TRAF6 (236%, IL-1β (405%, IL-18 (365%, COX-2 (2,777% and NF-κB (245% in the WT animals when compared with saline-injected group (P<0.05. Genetic deletion of MyD88, TLR2 or TLR9 effectively controlled the signs of intestinal injury when compared with irinotecan-administered WT controls (P<0.05. In contrast to the MyD88-/- and TLR2-/- mice, the irinotecan-injected TLR9-/- mice showed a reduced survival, a marked diarrhea and an enhanced expression of IL-18 versus irinotecan-injected WT controls. Additionally, the expression of MyD88 was reduced in the TLR2-/- or TLR9-/- mice. This study shows a critical role of the MyD88-mediated TLR2 and TLR9 signaling in the pathogenesis of irinotecan-induced intestinal mucositis.

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

    Institute of Scientific and Technical Information of China (English)

    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.

  15. 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.

    Science.gov (United States)

    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.

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

    DEFF Research Database (Denmark)

    Chen, Y; Grall, D; Salcini, A 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....

  17. Adaptor protein complex 2-mediated, clathrin-dependent endocytosis, and related gene activities, are a prominent feature during maturation stage amelogenesis.

    Science.gov (United States)

    Lacruz, Rodrigo S; Brookes, Steven J; Wen, Xin; Jimenez, Jaime M; Vikman, Susanna; Hu, Ping; White, Shane N; Lyngstadaas, S Petter; Okamoto, Curtis T; Smith, Charles E; Paine, Michael L

    2013-03-01

    Molecular events defining enamel matrix removal during amelogenesis are poorly understood. Early reports have suggested that adaptor proteins (AP) participate in ameloblast-mediated endocytosis. Enamel formation involves the secretory and maturation stages, with an increase in resorptive function during the latter. Here, using real-time PCR, we show that the expression of clathrin and adaptor protein subunits are upregulated in maturation stage rodent enamel organ cells. AP complex 2 (AP-2) is the most upregulated of the four distinct adaptor protein complexes. Immunolocalization confirms the presence of AP-2 and clathrin in ameloblasts, with strongest reactivity at the apical pole. These data suggest that the resorptive functions of enamel cells involve AP-2 mediated, clathrin-dependent endocytosis, thus implying the likelihood of specific membrane-bound receptor(s) of enamel matrix protein debris. The mRNA expression of other endocytosis-related gene products is also upregulated during maturation including: lysosomal-associated membrane protein 1 (Lamp1); cluster of differentiation 63 and 68 (Cd63 and Cd68); ATPase, H(+) transporting, lysosomal V0 subunit D2 (Atp6v0d2); ATPase, H(+) transporting, lysosomal V1 subunit B2 (Atp6v1b2); chloride channel, voltage-sensitive 7 (Clcn7); and cathepsin K (Ctsk). Immunohistologic data confirms the expression of a number of these proteins in maturation stage ameloblasts. The enamel of Cd63-null mice was also examined. Despite increased mRNA and protein expression in the enamel organ during maturation, the enamel of Cd63-null mice appeared normal. This may suggest inherent functional redundancies between Cd63 and related gene products, such as Lamp1 and Cd68. Ameloblast-like LS8 cells treated with the enamel matrix protein complex Emdogain showed upregulation of AP-2 and clathrin subunits, further supporting the existence of a membrane-bound receptor-regulated pathway for the endocytosis of enamel matrix proteins. These data

  18. Analysis of Phosphorylation-dependent Protein Interactions of Adhesion and Degranulation Promoting Adaptor Protein (ADAP) Reveals Novel Interaction Partners Required for Chemokine-directed T cell Migration.

    Science.gov (United States)

    Kuropka, Benno; Witte, Amelie; Sticht, Jana; Waldt, Natalie; Majkut, Paul; Hackenberger, Christian P R; Schraven, Burkhart; Krause, Eberhard; Kliche, Stefanie; Freund, Christian

    2015-11-01

    Stimulation of T cells leads to distinct changes of their adhesive and migratory properties. Signal propagation from activated receptors to integrins depends on scaffolding proteins such as the adhesion and degranulation promoting adaptor protein (ADAP)(1). Here we have comprehensively investigated the phosphotyrosine interactome of ADAP in T cells and define known and novel interaction partners of functional relevance. While most phosphosites reside in unstructured regions of the protein, thereby defining classical SH2 domain interaction sites for master regulators of T cell signaling such as SLP76, Fyn-kinase, and NCK, other binding events depend on structural context. Interaction proteomics using different ADAP constructs comprising most of the known phosphotyrosine motifs as well as the structured domains confirm that a distinct set of proteins is attracted by pY571 of ADAP, including the ζ-chain-associated protein kinase of 70 kDa (ZAP70). The interaction of ADAP and ZAP70 is inducible upon stimulation either of the T cell receptor (TCR) or by chemokine. NMR spectroscopy reveals that the N-terminal SH2 domains within a ZAP70-tandem-SH2 construct is the major site of interaction with phosphorylated ADAP-hSH3(N) and microscale thermophoresis (MST) indicates an intermediate binding affinity (Kd = 2.3 μm). Interestingly, although T cell receptor dependent events such as T cell/antigen presenting cell (APC) conjugate formation and adhesion are not affected by mutation of Y571, migration of T cells along a chemokine gradient is compromised. Thus, although most phospho-sites in ADAP are linked to T cell receptor related functions we have identified a unique phosphotyrosine that is solely required for chemokine induced T cell behavior.

  19. The cell signaling adaptor protein EPS-8 is essential for C. elegans epidermal elongation and interacts with the ankyrin repeat protein VAB-19.

    Directory of Open Access Journals (Sweden)

    Mei Ding

    Full Text Available The epidermal cells of the C. elegans embryo undergo coordinated cell shape changes that result in the morphogenetic process of elongation. The cytoskeletal ankyrin repeat protein VAB-19 is required for cell shape changes and localizes to cell-matrix attachment structures. The molecular functions of VAB-19 in this process are obscure, as no previous interactors for VAB-19 have been described.In screens for VAB-19 binding proteins we identified the signaling adaptor EPS-8. Within C. elegans epidermal cells, EPS-8 and VAB-19 colocalize at cell-matrix attachment structures. The central domain of EPS-8 is necessary and sufficient for its interaction with VAB-19. eps-8 null mutants, like vab-19 mutants, are defective in epidermal elongation and in epidermal-muscle attachment. The eps-8 locus encodes two isoforms, EPS-8A and EPS-8B, that appear to act redundantly in epidermal elongation. The function of EPS-8 in epidermal development involves its N-terminal PTB and central domains, and is independent of its C-terminal SH3 and actin-binding domains. VAB-19 appears to act earlier in the biogenesis of attachment structures and may recruit EPS-8 to these structures.EPS-8 and VAB-19 define a novel pathway acting at cell-matrix attachments to regulate epithelial cell shape. This is the first report of a role for EPS-8 proteins in cell-matrix attachments. The existence of EPS-8B-like isoforms in Drosophila suggests this function of EPS-8 proteins could be conserved among other organisms.

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

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae-Rin; Hahn, Hwa-Sun; Kim, Young-Hoon; Nguyen, Hong-Hoa [Department of Molecular Cell Biology, Center for Molecular Medicine, Samsung Biomedical Research Institute, Sungkyunkwan University School of Medicine, Suwon 440-746 (Korea, Republic of); Yang, Jun-Mo [Department of Dermatology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul 135-710 (Korea, Republic of); Kang, Jong-Sun, E-mail: kangj01@skku.edu [Department of Molecular Cell Biology, Center for Molecular Medicine, Samsung Biomedical Research Institute, Sungkyunkwan University School of Medicine, Suwon 440-746 (Korea, Republic of); Hahn, Myong-Joon, E-mail: hahnmj@skku.edu [Department of Molecular Cell Biology, Center for Molecular Medicine, Samsung Biomedical Research Institute, Sungkyunkwan University School of Medicine, Suwon 440-746 (Korea, Republic of)

    2011-11-11

    Highlights: Black-Right-Pointing-Pointer APPL1 regulates the protein level of EGFR in response to EGF stimulation. Black-Right-Pointing-Pointer Depletion of APPL1 accelerates the movement of EGF/EGFR from the cell surface to the perinuclear region in response to EGF. Black-Right-Pointing-Pointer 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.

  1. Structural basis for the recognition of the scaffold protein Frmpd4/Preso1 by the TPR domain of the adaptor protein LGN.

    Science.gov (United States)

    Takayanagi, Hiroki; Yuzawa, Satoru; Sumimoto, Hideki

    2015-02-01

    The adaptor protein LGN interacts via the N-terminal domain comprising eight tetratricopeptide-repeat (TPR) motifs with its partner proteins mInsc, NuMA, Frmpd1 and Frmpd4 in a mutually exclusive manner. Here, the crystal structure of the LGN TPR domain in complex with human Frmpd4 is described at 1.5 Å resolution. In the complex, the LGN-binding region of Frmpd4 (amino-acid residues 990-1011) adopts an extended structure that runs antiparallel to LGN along the concave surface of the superhelix formed by the TPR motifs. Comparison with the previously determined structures of the LGN-Frmpd1, LGN-mInsc and LGN-NuMA complexes reveals that these partner proteins interact with LGN TPR1-6 via a common core binding region with consensus sequence (E/Q)XEX4-5(E/D/Q)X1-2(K/R)X0-1(V/I). In contrast to Frmpd1, Frmpd4 makes additional contacts with LGN via regions N- and C-terminal to the core sequence. The N-terminal extension is replaced by a specific α-helix in mInsc, which drastically increases the direct contacts with LGN TPR7/8, consistent with the higher affinity of mInsc for LGN. A crystal structure of Frmpd4-bound LGN in an oxidized form is also reported, although oxidation does not appear to strongly affect the interaction with Frmpd4.

  2. The 3A Protein from Multiple Picornaviruses Utilizes the Golgi Adaptor Protein ACBD3 To Recruit PI4KIIIβ

    OpenAIRE

    Greninger, Alexander L.; Giselle M Knudsen; Betegon, Miguel; Burlingame, Alma L.; Joseph L Derisi

    2012-01-01

    The activity of phosphatidylinositol 4-kinase class III beta (PI4KIIIβ) has been shown to be required for the replication of multiple picornaviruses; however, it is unclear whether a physical association between PI4KIIIβ and the viral replication machinery exists and, if it does, whether association is necessary. We examined the ability of the 3A protein from 18 different picornaviruses to form a complex with PI4KIIIβ by affinity purification of Strep-Tagged transiently transfected constructs...

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

    LENUS (Irish Health Repository)

    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.

  4. RECOMBINANT FLUORESCENT SENSOR OF HYDROGEN PEROXIDE HyPer FUSED WITH ADAPTOR PROTEIN Ruk/CIN85: DESIGNING OF EXPRESSION VECTOR AND ITS FUNCTIONAL CHARACTERIZATION

    Directory of Open Access Journals (Sweden)

    А. V. Bazalii

    2015-10-01

    Full Text Available The aim of this study was to design the expression vector encoding fluorescent sensor of hydrogen peroxide HyPer fused with adaptor protein Ruk/CIN85 as well as to check its subcellular distribution and ability to sense hydrogen peroxide. It was demonstrated that in transiently transfected HEK293 and MCF-7 cells Ruk/CIN85-HyPer is concentrated in dot-like vesicular structures of different size while HyPer is diffusely distributed throughout the cell. Using live cell fluorescence microscopy we observed gradual increase in hydrogen peroxide concentration in representative vesicular structures during the time of experiment. Thus, the developed genetic construction encoding the chimeric Ruk/CIN85-HyPer fluorescent protein represents a new tool to study localized H2O2 production in living cells.

  5. Protein modifications regulate the role of 14-3-3γ adaptor protein in cAMP-induced steroidogenesis in MA-10 Leydig cells.

    Science.gov (United States)

    Aghazadeh, Yasaman; Ye, Xiaoying; Blonder, Josip; Papadopoulos, Vassilios

    2014-09-19

    The 14-3-3 protein family comprises adaptors and scaffolds that regulate intracellular signaling pathways. The 14-3-3γ isoform is a negative regulator of steroidogenesis that is hormonally induced and transiently functions at the initiation of steroidogenesis by delaying maximal steroidogenesis in MA-10 mouse tumor Leydig cells. Treatment of MA-10 cells with the cAMP analog 8-bromo-cAMP (8-Br-cAMP), which stimulates steroidogenesis, triggers the interaction of 14-3-3γ with the steroidogenic acute regulatory protein (STAR) in the cytosol, limiting STAR activity to basal levels. Over time, this interaction ceases, allowing for a 2-fold induction in STAR activity and maximal increase in the rate of steroid formation. The 14-3-3γ/STAR pattern of interaction was found to be opposite that of the 14-3-3γ homodimerization pattern. Phosphorylation and acetylation of 14-3-3γ showed similar patterns to homodimerization and STAR binding, respectively. 14-3-3γ Ser(58) phosphorylation and 14-3-3γ Lys(49) acetylation were blocked using trans-activator of HIV transcription factor 1 peptides coupled to 14-3-3γ sequences containing Ser(58) or Lys(49). Blocking either one of these modifications further induced 8-Br-cAMP-induced steroidogenesis while reducing lipid storage, suggesting that the stored cholesterol is used for steroid formation. Taken together, these results indicate that Ser(58) phosphorylation and Lys(49) acetylation of 14-3-3γ occur in a coordinated time-dependent manner to regulate 14-3-3γ homodimerization. 14-3-3γ Ser(58) phosphorylation is required for STAR interactions under control conditions, and 14-3-3γ Lys(49) acetylation is important for the cAMP-dependent induction of these interactions.

  6. Crk adaptor protein-induced phosphorylation of Gab1 on tyrosine 307 via Src is important for organization of focal adhesions and enhanced cell migration

    Institute of Scientific and Technical Information of China (English)

    Takuya Watanabe; Masumi Tsuda; Yoshinori Makino; Tassos Konstantinou; Hiroshi Nishihara; Tokifumi Majima; Akio Minami; Stephan M Feller; Shinya Tanaka

    2009-01-01

    Upon growth factor stimulation, the scaffold protein, Gabl, is tyrosine phosphorylated and subsequently the adaptor protein, Crk, transmits signals from Gabl. We have previously shown that Crk overexpression, which is detectable in various human cancers, induces tyrosine phosphorylation of Gab1 without extraceilular stimuli. In the present study, the underlying mechanisms were further investigated. Mutational analyses of Crkll demonstrated that the SH2 domain, but not the SH3(N) or the regulatory Y221 residue of Crkll, is critical for the induction of Gabl-Y307 phosphorylation. SH2 mutation of Crkll also decreased the interaction with Gab1. In GST pull-down assay, Crk-SH2 bound to wild-type Gabl, whereas Crk-SH3(N) interacted with the Gabl mutant, which lacks the clus-tered tyrosine region (residues 242-410). Tyrosine phosphorylation of Gabl was induced by all Crk family proteins, but not other SH2-containing signalling adaptors. Src-family kinase inhibitor, PP2, abrogates Crk-induced tyrosine phosphorylations of Gabl. Y307 phosphorylation was undetectable in fibroblasts lacking Src, Yes, and Fyn, even upon overexpression of Crk, whereas cells lacking only Yes and Fyn still contained Gabl with phosphorylated Y307. Furthermore, Crk induced the phosphorylation of Src-Y416; accordingly the interaction between Crk and Csk was increased. The GabI-Y307F mutant failed to localize near the plasma membrane even upon HGF stimulation and decreased cell migration. Moreover, Gabl-Y307F disturbed the localization of Crk, FAK, and paxiilin, which are the typical components of focal adhesions. Taken together, these results indicate that Crk facilitates tyrosine phosphory-lation of Gabl-Y307 through Src, contributing to the organization of focal adhesions and enhanced cell migration, thereby possibly promoting human cancer development.

  7. Inflammasome adaptor protein Apoptosis-associated speck-like protein containing CARD (ASC) is critical for the immune response and survival in west Nile virus encephalitis.

    Science.gov (United States)

    Kumar, Mukesh; Roe, Kelsey; Orillo, Beverly; Muruve, Daniel A; Nerurkar, Vivek R; Gale, Michael; Verma, Saguna

    2013-04-01

    West Nile virus (WNV) is a neurotropic flavivirus that has emerged globally as a significant cause of viral encephalitis in humans. The WNV-induced innate immune response, including production of antiviral cytokines, is critical for controlling virus infection. The adaptor protein ASC mediates a critical step in innate immune signaling by bridging the interaction between the pathogen recognition receptors and caspase 1 in inflammasome complexes, but its role in WNV immunopathogenesis is not defined. Here, we demonstrate that ASC is essential for interleukin-1β (IL-1β) production and development of effective host immunity against WNV. ASC-deficient mice exhibited increased susceptibility to WNV infection, and reduced survival was associated with enhanced virus replication in the peripheral tissues and central nervous system (CNS). Infection of cultured bone marrow-derived dendritic cells showed that ASC was essential for the activation of caspase 1, a key component of inflammasome assembly. ASC(-/-) mice exhibited attenuated levels of proinflammatory cytokines in the serum. Intriguingly, infected ASC(-/-) mice also displayed reduced levels of alpha interferon (IFN-α) and IgM in the serum, indicating the overall protective role of ASC in restricting WNV infection. However, brains from ASC(-/-) mice displayed unrestrained inflammation, including elevated levels of proinflammatory cytokines and chemokines, such as IFN-γ, CCL2, and CCL5, which correlated with more pronounced activation of the astrocytes, enhanced infiltration of peripheral immune cells in the CNS, and increased neuronal cell death. Collectively, our data provide new insights into the role of ASC as an essential modulator of inflammasome-dependent and -independent immune responses to effectively control WNV infection.

  8. RTK SLAP down: the emerging role of Src-like adaptor protein as a key player in receptor tyrosine kinase signaling.

    Science.gov (United States)

    Wybenga-Groot, Leanne E; McGlade, C Jane

    2015-02-01

    SLAP (Src like adaptor protein) contains adjacent Src homology 3 (SH3) and Src homology 2 (SH2) domains closely related in sequence to that of cytoplasmic Src family tyrosine kinases. Expressed most abundantly in the immune system, SLAP function has been predominantly studied in the context of lymphocyte signaling, where it functions in the Cbl dependent downregulation of antigen receptor signaling. However, accumulating evidence suggests that SLAP plays a role in the regulation of a broad range of membrane receptors including members of the receptor tyrosine kinase (RTK) family. In this review we highlight the role of SLAP in the ubiquitin dependent regulation of type III RTKs PDGFR, CSF-1R, KIT and Flt3, as well as Eph family RTKs. SLAP appears to bind activated type III and Eph RTKs via a conserved autophosphorylated juxtamembrane tyrosine motif in an SH2-dependent manner, suggesting that SLAP is important in regulating RTK signaling.

  9. 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

    NARCIS (Netherlands)

    A. Sultan (Ayesha); M. Luo (Ma); Q. Yu (Qingbao); B. Riederer (Beat Michel); W. Xia (Weiliang); M. Chen (Mingmin); S. Lissner (Simone); J.E. Gessner (Johannes); M. Donowitz (Mark); C. Chris Yun (C.); H. deJonge (Hugo); G. Lamprecht (Georg); U. Seidler (Ursula)

    2013-01-01

    textabstractBackground/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 uncl

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

    Energy Technology Data Exchange (ETDEWEB)

    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

  11. Induction of Androgen Formation in the Male by a TAT-VDAC1 Fusion Peptide Blocking 14-3-3ɛ Protein Adaptor and Mitochondrial VDAC1 Interactions

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    Aghazadeh, Yasaman; Martinez-Arguelles, Daniel B; Fan, Jinjiang; Culty, Martine; Papadopoulos, Vassilios

    2014-01-01

    Low testosterone (T), a major cause of male hypogonadism and infertility, is linked to mood changes, fatigue, osteoporosis, reduced bone-mass index, and aging. The treatment of choice, T replacement therapy, has been linked with increased risk for prostate cancer and luteinizing hormone (LH) suppression, and shown to lead to infertility, cardiovascular diseases, and obesity. Alternate methods to induce T with lower side effects are desirable. In search of the mechanisms regulating T synthesis in the testes, we identified the 14-3-3ɛ protein adaptor as a negative regulator of steroidogenesis. Steroidogenesis begins in mitochondria. 14-3-3ɛ interacts with the outer mitochondrial membrane voltage-dependent anion channel (VDAC1) protein, forming a scaffold that limits the availability of cholesterol for steroidogenesis. We report the development of a tool able to induce endogenous T formation. Peptides able to penetrate testes conjugated to 14-3-3ɛ site of interaction with VDAC1 blocked 14-3-3ɛ-VDAC1 interactions while at the same time increased VDAC1-translocator protein (18 kDa) interactions that induced steroid formation in rat testes, leading to increased serum T levels. These peptides rescued intratesticular and serum T formation in adult male rats treated with gonadotropin-releasing hormone antagonist, which dampened LH and T production. PMID:24947306

  12. Controllability in protein interaction networks.

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    Wuchty, Stefan

    2014-05-13

    Recently, the focus of network research shifted to network controllability, prompting us to determine proteins that are important for the control of the underlying interaction webs. In particular, we determined minimum dominating sets of proteins (MDSets) in human and yeast protein interaction networks. Such groups of proteins were defined as optimized subsets where each non-MDSet protein can be reached by an interaction from an MDSet protein. Notably, we found that MDSet proteins were enriched with essential, cancer-related, and virus-targeted genes. Their central position allowed MDSet proteins to connect protein complexes and to have a higher impact on network resilience than hub proteins. As for their involvement in regulatory functions, MDSet proteins were enriched with transcription factors and protein kinases and were significantly involved in bottleneck interactions, regulatory links, phosphorylation events, and genetic interactions.

  13. Involvement of Grb2 adaptor protein in nucleophosmin-anaplastic lymphoma kinase (NPM-ALK)-mediated signaling and anaplastic large cell lymphoma growth.

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    Riera, Ludovica; Lasorsa, Elena; Ambrogio, Chiara; Surrenti, Nadia; Voena, Claudia; Chiarle, Roberto

    2010-08-20

    Most anaplastic large cell lymphomas (ALCL) express oncogenic fusion proteins derived from chromosomal translocations or inversions of the anaplastic lymphoma kinase (ALK) gene. Frequently ALCL carry the t(2;5) translocation, which fuses the ALK gene to the nucleophosmin (NPM1) gene. The transforming activity mediated by NPM-ALK fusion induces different pathways that control proliferation and survival of lymphoma cells. Grb2 is an adaptor protein thought to play an important role in ALK-mediated transformation, but its interaction with NPM-ALK, as well as its function in regulating ALCL signaling pathways and cell growth, has never been elucidated. Here we show that active NPM-ALK, but not a kinase-dead mutant, bound and induced Grb2 phosphorylation in tyrosine 160. An intact SH3 domain at the C terminus of Grb2 was required for Tyr(160) phosphorylation. Furthermore, Grb2 did not bind to a single region but rather to different regions of NPM-ALK, mainly Tyr(152-156), Tyr(567), and a proline-rich region, Pro(415-417). Finally, shRNA knockdown experiments showed that Grb2 regulates primarily the NPM-ALK-mediated phosphorylation of SHP2 and plays a key role in ALCL cell growth.

  14. Interaction of ubiquitin ligase CBL with LMP2A protein of Epstein-Barr virus occurs via PTB domain of CBL and does not depend on adaptor ITSN1

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    Dergai O. V.

    2013-03-01

    Full Text Available Aim. Previously Latent membrane protein 2A (LMP2A of Epstein-Barr virus was found to be ubiquitylated by CBL ubiquitin ligase but no direct interaction of LMP2A with CBL was reported. We aimed to explore this interaction and study a possibility of adaptor protein involvement. Taking into consideration that both LMP2A and CBL were shown to interact with endocytic adaptor protein intersectin 1 (ITSN1, we assumed that the latter could serve as a scaffold for LMP2A/CBL complex. Methods. We used an immunofluorescence and coimmuno- precipitation approaches to test a mutual complex formation of ITSN1, CBL and LMP2A proteins. Results. LMP2A coimmunoprecipitated with CBL while LMP2A did not interact with CBL G306E mutant harboring inactive phosphotyrosine-binding domain. We observed a triple colocalization of ITSN1, CBL and LMP2A signals in MCF-7 cells as well as coprecipitation of all mentioned proteins. Overexpression of ITSN1 did not affect the efficiency of complex formation of LMP2A with CBL. Moreover, LMP2A mutant unable to interact with ITSN1 was readily precipitated with CBL. Conclusions. LMP2A can be engaged in the complex together with endocytic adaptor ITSN1 and ubiquitin ligase CBL. We show that PTB domain of CBL is responsible for interaction with LMP2A. ITSN1 is not required for LMP2A recruiting to CBL.

  15. The adaptor protein SAP directly associates with PECAM-1 and regulates PECAM-1-mediated-cell adhesion in T-like cell lines.

    Science.gov (United States)

    Proust, Richard; Crouin, Catherine; Gandji, Leslie Yewakon; Bertoglio, Jacques; Gesbert, Franck

    2014-04-01

    SAP is a small cytosolic adaptor protein expressed in hematopoietic lineages whose main function is to regulate intracellular signaling pathways induced by the triggering of members of the SLAM receptor family. In this paper, we have identified the adhesion molecule PECAM-1 as a new partner for SAP in a conditional yeast two-hybrid screen. PECAM-1 is an immunoglobulin-like molecule expressed by endothelial cells and leukocytes, which possesses both pro- and anti-inflammatory properties. However, little is known about PECAM-1 functions in T cells. We show that SAP directly and specifically interacts with the cytosolic tyrosine 686 of PECAM-1. We generated different T-like cell lines in which SAP or PECAM-1 are expressed or down modulated and we demonstrate that a diminished SAP expression correlates with a diminished PECAM-1-mediated adhesion. Although SAP has mainly been shown to associate with SLAM receptors, we evidence here that SAP is a new actor downstream of PECAM-1.

  16. Src-Like adaptor protein (SLAP) binds to the receptor tyrosine kinase Flt3 and modulates receptor stability and downstream signaling.

    Science.gov (United States)

    Kazi, Julhash U; Rönnstrand, Lars

    2012-01-01

    Fms-like tyrosine kinase 3 (Flt3) is an important growth factor receptor in hematopoiesis. Gain-of-function mutations of the receptor contribute to the transformation of acute myeloid leukemia (AML). Src-like adaptor protein (SLAP) is an interaction partner of the E3 ubiquitin ligase Cbl that can regulate receptor tyrosine kinases-mediated signal transduction. In this study, we analyzed the role of SLAP in signal transduction downstream of the type III receptor tyrosine kinase Flt3. The results show that upon ligand stimulation SLAP stably associates with Flt3 through multiple phosphotyrosine residues in Flt3. SLAP constitutively interacts with oncogenic Flt3-ITD and co-localizes with Flt3 near the cell membrane. This association initiates Cbl-dependent receptor ubiquitination and degradation. Depletion of SLAP expression by shRNA in Flt3-transfected Ba/F3 cells resulted in a weaker activation of FL-induced PI3K-Akt and MAPK signaling. Meta-analysis of microarray data from patient samples suggests that SLAP mRNA is differentially expressed in different cancers and its expression was significantly increased in patients carrying the Flt3-ITD mutation. Thus, our data suggest a novel role of SLAP in different cancers and in modulation of receptor tyrosine kinase signaling apart from its conventional role in regulation of receptor stability.

  17. Src-Like adaptor protein (SLAP binds to the receptor tyrosine kinase Flt3 and modulates receptor stability and downstream signaling.

    Directory of Open Access Journals (Sweden)

    Julhash U Kazi

    Full Text Available Fms-like tyrosine kinase 3 (Flt3 is an important growth factor receptor in hematopoiesis. Gain-of-function mutations of the receptor contribute to the transformation of acute myeloid leukemia (AML. Src-like adaptor protein (SLAP is an interaction partner of the E3 ubiquitin ligase Cbl that can regulate receptor tyrosine kinases-mediated signal transduction. In this study, we analyzed the role of SLAP in signal transduction downstream of the type III receptor tyrosine kinase Flt3. The results show that upon ligand stimulation SLAP stably associates with Flt3 through multiple phosphotyrosine residues in Flt3. SLAP constitutively interacts with oncogenic Flt3-ITD and co-localizes with Flt3 near the cell membrane. This association initiates Cbl-dependent receptor ubiquitination and degradation. Depletion of SLAP expression by shRNA in Flt3-transfected Ba/F3 cells resulted in a weaker activation of FL-induced PI3K-Akt and MAPK signaling. Meta-analysis of microarray data from patient samples suggests that SLAP mRNA is differentially expressed in different cancers and its expression was significantly increased in patients carrying the Flt3-ITD mutation. Thus, our data suggest a novel role of SLAP in different cancers and in modulation of receptor tyrosine kinase signaling apart from its conventional role in regulation of receptor stability.

  18. Activation of EphA receptors mediates the recruitment of the adaptor protein Slap, contributing to the downregulation of N-methyl-D-aspartate receptors.

    Science.gov (United States)

    Semerdjieva, Sophia; Abdul-Razak, Hayder H; Salim, Sharifah S; Yáñez-Muñoz, Rafael J; Chen, Philip E; Tarabykin, Victor; Alifragis, Pavlos

    2013-04-01

    Regulation of the activity of N-methyl-d-aspartate receptors (NMDARs) at glutamatergic synapses is essential for certain forms of synaptic plasticity underlying learning and memory and is also associated with neurotoxicity and neurodegenerative diseases. In this report, we investigate the role of Src-like adaptor protein (Slap) in NMDA receptor signaling. We present data showing that in dissociated neuronal cultures, activation of ephrin (Eph) receptors by chimeric preclustered eph-Fc ligands leads to recruitment of Slap and NMDA receptors at the sites of Eph receptor activation. Interestingly, our data suggest that prolonged activation of EphA receptors is as efficient in recruiting Slap and NMDA receptors as prolonged activation of EphB receptors. Using established heterologous systems, we examined whether Slap is an integral part of NMDA receptor signaling. Our results showed that Slap does not alter baseline activity of NMDA receptors and does not affect Src-dependent potentiation of NMDA receptor currents in Xenopus oocytes. We also demonstrate that Slap reduces excitotoxic cell death triggered by activation of NMDARs in HEK293 cells. Finally, we present evidence showing reduced levels of NMDA receptors in the presence of Slap occurring in an activity-dependent manner, suggesting that Slap is part of a mechanism that homeostatically modulates the levels of NMDA receptors.

  19. The interaction of the cellular export adaptor protein Aly/REF with ICP27 contributes to the efficiency of herpes simplex virus 1 mRNA export.

    Science.gov (United States)

    Tian, Xiaochen; Devi-Rao, Gayathri; Golovanov, Alexander P; Sandri-Goldin, Rozanne M

    2013-07-01

    Herpes simplex virus 1 (HSV-1) protein ICP27 enables viral mRNA export by accessing the cellular mRNA export receptor TAP/NXF, which guides mRNA through the nuclear pore complex. ICP27 binds viral mRNAs and interacts with TAP/NXF, providing a link to the cellular mRNA export pathway. ICP27 also interacts with the mRNA export adaptor protein Aly/REF, which binds cellular mRNAs and also interacts with TAP/NXF. Studies using small interfering RNA (siRNA) knockdown indicated that Aly/REF is not required for cellular mRNA export, and similar knockdown studies during HSV-1 infection led us to conclude that Aly/REF may be dispensable for viral RNA export. Recently, the structural basis of the interaction of ICP27 with Aly/REF was elucidated at atomic resolution, and it was shown that three ICP27 residues, W105, R107, and L108, interface with the RNA recognition motif (RRM) domain of Aly/REF. Here, to determine the role the interaction of ICP27 and Aly/REF plays during infection, these residues were mutated to alanine, and a recombinant virus, WRL-A, was constructed. Virus production was reduced about 10-fold during WRL-A infection, and export of ICP27 protein and most viral mRNAs was less efficient. We conclude that interaction of ICP27 with Aly/REF contributes to efficient viral mRNA export.

  20. SH2 domain–containing adaptor protein B expressed in dendritic cells is involved in T-cell homeostasis by regulating dendritic cell–mediated Th2 immunity

    Science.gov (United States)

    2017-01-01

    Purpose The Src homology 2 domain–containing adaptor protein B (SHB) is widely expressed in immune cells and acts as an important regulator for hematopoietic cell function. SHB silencing induces Th2 immunity in mice. SHB is also involved in T-cell homeostasis in vivo. However, SHB has not yet been studied and addressed in association with dendritic cells (DCs). Materials and Methods The effects of SHB expression on the immunogenicity of DCs were assessed by Shb gene silencing in mouse bone marrow–derived DCs (BMDCs). After silencing, surface phenotype, cytokine expression profile, and T-cell stimulation capacity of BMDCs were examined. We investigated the signaling pathways involved in SHB expression during BMDC development. We also examined the immunogenicity of SHB-knockdown (SHBKD) BMDCs in a mouse atopic dermatitis model. Results SHB was steadily expressed in mouse splenic DCs and in in vitro–generated BMDCs in both immature and mature stages. SHB expression was contingent on activation of the mitogen- activated protein kinase/Foxa2 signaling pathway during DC development. SHBKD increased the expression of MHC class II and costimulatory molecules without affecting the cytokine expression of BMDCs. When co-cultured with T cells, SHBKD in BMDCs significantly induced CD4+ T-cell proliferation and the expression of Th2 cytokines, while the regulatory T cell (Treg) population was downregulated. In mouse atopic dermatitis model, mice inoculated with SHBKD DCs developed more severe symptoms of atopic dermatitis compared with mice injected with control DCs. Conclusion SHB expression in DCs plays an important role in T-cell homeostasis in vivo by regulating DC-mediated Th2 polarization. PMID:28168174

  1. Pseudomonas aeruginosa ExoT Induces Atypical Anoikis Apoptosis in Target Host Cells by Transforming Crk Adaptor Protein into a Cytotoxin.

    Science.gov (United States)

    Wood, Stephen; Goldufsky, Josef; Shafikhani, Sasha H

    2015-05-01

    Previously, we demonstrated that Pseudomonas aeruginosa ExoT induces potent apoptosis in host epithelial cells in a manner that primarily depends on its ADP-ribosyltransferase domain (ADPRT) activity. However, the mechanism underlying ExoT/ADPRT-induced apoptosis remains undetermined. We now report that ExoT/ADPRT disrupts focal adhesion sites, activates p38β and JNK, and interferes with integrin-mediated survival signaling; causing atypical anoikis. We show that ExoT/ADPRT-induced anoikis is mediated by the Crk adaptor protein. We found that Crk-/- knockout cells are significantly more resistant to ExoT-induced apoptosis, while Crk-/- cells complemented with Crk are rendered sensitive to ExoT-induced apoptosis. Moreover, a dominant negative (DN) mutant form of Crk phenocopies ExoT-induced apoptosis both kinetically and mechanistically. Crk is generally believed to be a component of focal adhesion (FA) and its role in cellular survival remains controversial in that it has been found to be either pro-survival or pro-apoptosis. Our data demonstrate that although Crk is recruited to FA sites, its function is likely not required for FA assembly or for survival per se. However, when modified by ExoT or by mutagenesis, it can be transformed into a cytotoxin that induces anoikis by disrupting FA sites and interfering with integrin survival signaling. To our knowledge, this is the first example whereby a bacterial toxin exerts its cytotoxicity by subverting the function of an innocuous host cellular protein and turning it against the host cell.

  2. SmShb, the SH2-Containing Adaptor Protein B of Schistosoma mansoni Regulates Venus Kinase Receptor Signaling Pathways

    Science.gov (United States)

    Morel, Marion; Vanderstraete, Mathieu; Cailliau, Katia; Hahnel, Steffen; Grevelding, Christoph G.; Dissous, Colette

    2016-01-01

    Venus kinase receptors (VKRs) are invertebrate receptor tyrosine kinases (RTKs) formed by an extracellular Venus Fly Trap (VFT) ligand binding domain associated via a transmembrane domain with an intracellular tyrosine kinase (TK) domain. Schistosoma mansoni VKRs, SmVKR1 and SmVKR2, are both implicated in reproductive activities of the parasite. In this work, we show that the SH2 domain-containing protein SmShb is a partner of the phosphorylated form of SmVKR1. Expression of these proteins in Xenopus oocytes allowed us to demonstrate that the SH2 domain of SmShb interacts with the phosphotyrosine residue (pY979) located in the juxtamembrane region of SmVKR1. This interaction leads to phosphorylation of SmShb on tyrosines and promotes SmVKR1 signaling towards the JNK pathway. SmShb transcripts are expressed in all parasite stages and they were found in ovary and testes of adult worms, suggesting a possible colocalization of SmShb and SmVKR1 proteins. Silencing of SmShb in adult S. mansoni resulted in an accumulation of mature sperm in testes, indicating a possible role of SmShb in gametogenesis. PMID:27636711

  3. SmShb, the SH2-Containing Adaptor Protein B of Schistosoma mansoni Regulates Venus Kinase Receptor Signaling Pathways.

    Science.gov (United States)

    Morel, Marion; Vanderstraete, Mathieu; Cailliau, Katia; Hahnel, Steffen; Grevelding, Christoph G; Dissous, Colette

    2016-01-01

    Venus kinase receptors (VKRs) are invertebrate receptor tyrosine kinases (RTKs) formed by an extracellular Venus Fly Trap (VFT) ligand binding domain associated via a transmembrane domain with an intracellular tyrosine kinase (TK) domain. Schistosoma mansoni VKRs, SmVKR1 and SmVKR2, are both implicated in reproductive activities of the parasite. In this work, we show that the SH2 domain-containing protein SmShb is a partner of the phosphorylated form of SmVKR1. Expression of these proteins in Xenopus oocytes allowed us to demonstrate that the SH2 domain of SmShb interacts with the phosphotyrosine residue (pY979) located in the juxtamembrane region of SmVKR1. This interaction leads to phosphorylation of SmShb on tyrosines and promotes SmVKR1 signaling towards the JNK pathway. SmShb transcripts are expressed in all parasite stages and they were found in ovary and testes of adult worms, suggesting a possible colocalization of SmShb and SmVKR1 proteins. Silencing of SmShb in adult S. mansoni resulted in an accumulation of mature sperm in testes, indicating a possible role of SmShb in gametogenesis.

  4. Role of the Caenorhabditis elegans Shc adaptor protein in the c-Jun N-terminal kinase signaling pathway.

    Science.gov (United States)

    Mizuno, Tomoaki; Fujiki, Kota; Sasakawa, Aya; Hisamoto, Naoki; Matsumoto, Kunihiro

    2008-12-01

    Mitogen-activated protein kinases (MAPKs) are integral to the mechanisms by which cells respond to physiological stimuli and a wide variety of environmental stresses. In Caenorhabditis elegans, the stress response is controlled by a c-Jun N-terminal kinase (JNK)-like mitogen-activated protein kinase (MAPK) signaling pathway, which is regulated by MLK-1 MAPK kinase kinase (MAPKKK), MEK-1 MAPK kinase (MAPKK), and KGB-1 JNK-like MAPK. In this study, we identify the shc-1 gene, which encodes a C. elegans homolog of Shc, as a factor that specifically interacts with MEK-1. The shc-1 loss-of-function mutation is defective in activation of KGB-1, resulting in hypersensitivity to heavy metals. A specific tyrosine residue in the NPXY motif of MLK-1 creates a docking site for SHC-1 with the phosphotyrosine binding (PTB) domain. Introduction of a mutation that perturbs binding to the PTB domain or the NPXY motif abolishes the function of SHC-1 or MLK-1, respectively, thereby abolishing the resistance to heavy metal stress. These results suggest that SHC-1 acts as a scaffold to link MAPKKK to MAPKK activation in the KGB-1 MAPK signal transduction pathway.

  5. The adaptor protein SAP regulates type II NKT-cell development, cytokine production, and cytotoxicity against lymphoma.

    Science.gov (United States)

    Weng, Xiufang; Liao, Chia-Min; Bagchi, Sreya; Cardell, Susanna L; Stein, Paul L; Wang, Chyung-Ru

    2014-12-01

    CD1d-restricted NKT cells represent a unique lineage of immunoregulatory T cells that are divided into two groups, type I and type II, based on their TCR usage. Because there are no specific tools to identify type II NKT cells, little is known about their developmental requirements and functional regulation. In our previous study, we showed that signaling lymphocytic activation molecule associated protein (SAP) is essential for the development of type II NKT cells. Here, using a type II NKT-cell TCR transgenic mouse model, we demonstrated that CD1d-expressing hematopoietic cells, but not thymic epithelial cells, meditate efficient selection of type II NKT cells. Furthermore, we showed that SAP regulates type II NKT-cell development by controlling early growth response 2 protein and promyelocytic leukemia zinc finger expression. SAP-deficient 24αβ transgenic T cells (24αβ T cells) exhibited an immature phenotype with reduced Th2 cytokine-producing capacity and diminished cytotoxicity to CD1d-expressing lymphoma cells. The impaired IL-4 production by SAP-deficient 24αβ T cells was associated with reduced IFN regulatory factor 4 and GATA-3 induction following TCR stimulation. Collectively, these data suggest that SAP is critical for regulating type II NKT cell responses. Aberrant responses of these T cells may contribute to the immune dysregulation observed in X-linked lymphoproliferative disease caused by mutations in SAP.

  6. The Mu subunit of Plasmodium falciparum clathrin-associated adaptor protein 2 modulates in vitro parasite response to artemisinin and quinine.

    Science.gov (United States)

    Henriques, Gisela; van Schalkwyk, Donelly A; Burrow, Rebekah; Warhurst, David C; Thompson, Eloise; Baker, David A; Fidock, David A; Hallett, Rachel; Flueck, Christian; Sutherland, Colin J

    2015-05-01

    The emergence of drug-resistant parasites is a serious threat faced by malaria control programs. Understanding the genetic basis of resistance is critical to the success of treatment and intervention strategies. A novel locus associated with antimalarial resistance, ap2-mu (encoding the mu chain of the adaptor protein 2 [AP2] complex), was recently identified in studies on the rodent malaria parasite Plasmodium chabaudi (pcap2-mu). Furthermore, analysis in Kenyan malaria patients of polymorphisms in the Plasmodium falciparum ap2-mu homologue, pfap2-mu, found evidence that differences in the amino acid encoded by codon 160 are associated with enhanced parasite survival in vivo following combination treatments which included artemisinin derivatives. Here, we characterize the role of pfap2-mu in mediating the in vitro antimalarial drug response of P. falciparum by generating transgenic parasites constitutively expressing codon 160 encoding either the wild-type Ser (Ser160) or the Asn mutant (160Asn) form of pfap2-mu. Transgenic parasites carrying the pfap2-mu 160Asn allele were significantly less sensitive to dihydroartemisinin using a standard 48-h in vitro test, providing direct evidence of an altered parasite response to artemisinin. Our data also provide evidence that pfap2-mu variants can modulate parasite sensitivity to quinine. No evidence was found that pfap2-mu variants contribute to the slow-clearance phenotype exhibited by P. falciparum in Cambodian patients treated with artesunate monotherapy. These findings provide compelling evidence that pfap2-mu can modulate P. falciparum responses to multiple drugs. We propose that this gene should be evaluated further as a potential molecular marker of antimalarial resistance.

  7. Identification of Topological Network Modules in Perturbed Protein Interaction Networks

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    Sardiu, Mihaela E.; Gilmore, Joshua M.; Groppe, Brad; Florens, Laurence; Washburn, Michael P.

    2017-01-01

    Biological networks consist of functional modules, however detecting and characterizing such modules in networks remains challenging. Perturbing networks is one strategy for identifying modules. Here we used an advanced mathematical approach named topological data analysis (TDA) to interrogate two perturbed networks. In one, we disrupted the S. cerevisiae INO80 protein interaction network by isolating complexes after protein complex components were deleted from the genome. In the second, we reanalyzed previously published data demonstrating the disruption of the human Sin3 network with a histone deacetylase inhibitor. Here we show that disrupted networks contained topological network modules (TNMs) with shared properties that mapped onto distinct locations in networks. We define TMNs as proteins that occupy close network positions depending on their coordinates in a topological space. TNMs provide new insight into networks by capturing proteins from different categories including proteins within a complex, proteins with shared biological functions, and proteins disrupted across networks. PMID:28272416

  8. Controlling allosteric networks in proteins

    Science.gov (United States)

    Dokholyan, Nikolay

    2013-03-01

    We present a novel methodology based on graph theory and discrete molecular dynamics simulations for delineating allosteric pathways in proteins. We use this methodology to uncover the structural mechanisms responsible for coupling of distal sites on proteins and utilize it for allosteric modulation of proteins. We will present examples where inference of allosteric networks and its rewiring allows us to ``rescue'' cystic fibrosis transmembrane conductance regulator (CFTR), a protein associated with fatal genetic disease cystic fibrosis. We also use our methodology to control protein function allosterically. We design a novel protein domain that can be inserted into identified allosteric site of target protein. Using a drug that binds to our domain, we alter the function of the target protein. We successfully tested this methodology in vitro, in living cells and in zebrafish. We further demonstrate transferability of our allosteric modulation methodology to other systems and extend it to become ligh-activatable.

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

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    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.

  10. Oligomeric protein structure networks: insights into protein-protein interactions

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    Brinda KV

    2005-12-01

    Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

  11. Vaccinia virus protein C6 is a virulence factor that binds TBK-1 adaptor proteins and inhibits activation of IRF3 and IRF7.

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    Leonie Unterholzner

    2011-09-01

    Full Text Available Recognition of viruses by pattern recognition receptors (PRRs causes interferon-β (IFN-β induction, a key event in the anti-viral innate immune response, and also a target of viral immune evasion. Here the vaccinia virus (VACV protein C6 is identified as an inhibitor of PRR-induced IFN-β expression by a functional screen of select VACV open reading frames expressed individually in mammalian cells. C6 is a member of a family of Bcl-2-like poxvirus proteins, many of which have been shown to inhibit innate immune signalling pathways. PRRs activate both NF-κB and IFN regulatory factors (IRFs to activate the IFN-β promoter induction. Data presented here show that C6 inhibits IRF3 activation and translocation into the nucleus, but does not inhibit NF-κB activation. C6 inhibits IRF3 and IRF7 activation downstream of the kinases TANK binding kinase 1 (TBK1 and IκB kinase-ε (IKKε, which phosphorylate and activate these IRFs. However, C6 does not inhibit TBK1- and IKKε-independent IRF7 activation or the induction of promoters by constitutively active forms of IRF3 or IRF7, indicating that C6 acts at the level of the TBK1/IKKε complex. Consistent with this notion, C6 immunoprecipitated with the TBK1 complex scaffold proteins TANK, SINTBAD and NAP1. C6 is expressed early during infection and is present in both nucleus and cytoplasm. Mutant viruses in which the C6L gene is deleted, or mutated so that the C6 protein is not expressed, replicated normally in cell culture but were attenuated in two in vivo models of infection compared to wild type and revertant controls. Thus C6 contributes to VACV virulence and might do so via the inhibition of PRR-induced activation of IRF3 and IRF7.

  12. The influenza virus protein PB1-F2 inhibits the induction of type I interferon at the level of the MAVS adaptor protein.

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    Zsuzsanna T Varga

    2011-06-01

    Full Text Available PB1-F2 is a 90 amino acid protein that is expressed from the +1 open reading frame in the PB1 gene of some influenza A viruses and has been shown to contribute to viral pathogenicity. Notably, a serine at position 66 (66S in PB1-F2 is known to increase virulence compared to an isogenic virus with an asparagine (66N at this position. Recently, we found that an influenza virus expressing PB1-F2 N66S suppresses interferon (IFN-stimulated genes in mice. To characterize this phenomenon, we employed several in vitro assays. Overexpression of the A/Puerto Rico/8/1934 (PR8 PB1-F2 protein in 293T cells decreased RIG-I mediated activation of an IFN-β reporter and secretion of IFN as determined by bioassay. Of note, the PB1-F2 N66S protein showed enhanced IFN antagonism activity compared to PB1-F2 wildtype. Similar observations were found in the context of viral infection with a PR8 PB1-F2 N66S virus. To understand the relationship between NS1, a previously described influenza virus protein involved in suppression of IFN synthesis, and PB1-F2, we investigated the induction of IFN when NS1 and PB1-F2 were co-expressed in an in vitro transfection system. In this assay we found that PB1-F2 N66S further reduced IFN induction in the presence of NS1. By inducing the IFN-β reporter at different levels in the signaling cascade, we found that PB1-F2 inhibited IFN production at the level of the mitochondrial antiviral signaling protein (MAVS. Furthermore, immunofluorescence studies revealed that PB1-F2 co-localizes with MAVS. In summary, we have characterized the anti-interferon function of PB1-F2 and we suggest that this activity contributes to the enhanced pathogenicity seen with PB1-F2 N66S- expressing influenza viruses.

  13. Deducing topology of protein-protein interaction networks from experimentally measured sub-networks

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    MacLellan W Robb

    2008-07-01

    Full Text Available Abstract Background Protein-protein interaction networks are commonly sampled using yeast two hybrid approaches. However, whether topological information reaped from these experimentally-measured sub-networks can be extrapolated to complete protein-protein interaction networks is unclear. Results By analyzing various experimental protein-protein interaction datasets, we found that they are not random samples of the parent networks. Based on the experimental bait-prey behaviors, our computer simulations show that these non-random sampling features may affect the topological information. We tested the hypothesis that a core sub-network exists within the experimentally sampled network that better maintains the topological characteristics of the parent protein-protein interaction network. We developed a method to filter the experimentally sampled network to result in a core sub-network that more accurately reflects the topology of the parent network. These findings have fundamental implications for large-scale protein interaction studies and for our understanding of the behavior of cellular networks. Conclusion The topological information from experimental measured networks network as is may not be the correct source for topological information about the parent protein-protein interaction network. We define a core sub-network that more accurately reflects the topology of the parent network.

  14. Protein interaction networks from literature mining

    Science.gov (United States)

    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.

  15. Discovering functional interaction patterns in protein-protein interaction networks

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    Can Tolga

    2008-06-01

    Full Text Available Abstract Background In recent years, a considerable amount of research effort has been directed to the analysis of biological networks with the availability of genome-scale networks of genes and/or proteins of an increasing number of organisms. A protein-protein interaction (PPI network is a particular biological network which represents physical interactions between pairs of proteins of an organism. Major research on PPI networks has focused on understanding the topological organization of PPI networks, evolution of PPI networks and identification of conserved subnetworks across different species, discovery of modules of interaction, use of PPI networks for functional annotation of uncharacterized proteins, and improvement of the accuracy of currently available networks. Results In this article, we map known functional annotations of proteins onto a PPI network in order to identify frequently occurring interaction patterns in the functional space. We propose a new frequent pattern identification technique, PPISpan, adapted specifically for PPI networks from a well-known frequent subgraph identification method, gSpan. Existing module discovery techniques either look for specific clique-like highly interacting protein clusters or linear paths of interaction. However, our goal is different; instead of single clusters or pathways, we look for recurring functional interaction patterns in arbitrary topologies. We have applied PPISpan on PPI networks of Saccharomyces cerevisiae and identified a number of frequently occurring functional interaction patterns. Conclusion With the help of PPISpan, recurring functional interaction patterns in an organism's PPI network can be identified. Such an analysis offers a new perspective on the modular organization of PPI networks. The complete list of identified functional interaction patterns is available at http://bioserver.ceng.metu.edu.tr/PPISpan/.

  16. Protein Networks in Alzheimer’s Disease

    DEFF Research Database (Denmark)

    Carlsen, Eva Maria Meier; Rasmussen, Rune

    2017-01-01

    Overlap of RNA and protein networks reveals glia cells as key players for the development of symptomatic Alzheimer’s disease in humans......Overlap of RNA and protein networks reveals glia cells as key players for the development of symptomatic Alzheimer’s disease in humans...

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

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    Yang Zhihao

    2011-10-01

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

  18. 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

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    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

  19. The cellular RNA export receptor TAP/NXF1 is required for ICP27-mediated export of herpes simplex virus 1 RNA, but the TREX complex adaptor protein Aly/REF appears to be dispensable.

    Science.gov (United States)

    Johnson, Lisa A; Li, Ling; Sandri-Goldin, Rozanne M

    2009-07-01

    Herpes simplex virus 1 (HSV-1) protein ICP27 has been shown to shuttle between the nucleus and cytoplasm and to bind viral RNA during infection. ICP27 was found to interact with the cellular RNA export adaptor protein Aly/REF, which is part of the TREX complex, and to relocalize Aly/REF to viral replication sites. ICP27 is exported to the cytoplasm through the export receptor TAP/NXF1, and ICP27 must be able to interact with TAP/NXF1 for efficient export of HSV-1 early and late transcripts. We examined the dynamics of ICP27 movement and its localization with respect to Aly/REF and TAP/NXF1 in living cells during viral infection. Recombinant viruses with a yellow fluorescent protein (YFP) tag on the N or C terminus of ICP27 were constructed. While the N-terminally tagged ICP27 virus behaved like wild-type HSV-1, the C-terminally tagged virus was defective in viral replication and gene expression, and ICP27 was confined to the nucleus, suggesting that the C-terminal YFP tag interfered with ICP27's C-terminal interactions, including the interaction with TAP/NXF1. To assess the role of Aly/REF and TAP/NXF1 in viral RNA export, these factors were knocked down using small interfering RNA. Knockdown of Aly/REF had little effect on the export of ICP27 or poly(A)(+) RNA during infection. In contrast, a decrease in TAP/NXF1 levels severely impaired export of ICP27 and poly(A)(+) RNA. We conclude that TAP/NXF1 is essential for ICP27-mediated export of RNA during HSV-1 infection, whereas Aly/REF may be dispensable.

  20. The microRNA mir-71 inhibits calcium signaling by targeting the TIR-1/Sarm1 adaptor protein to control stochastic L/R neuronal asymmetry in C. elegans.

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    Yi-Wen Hsieh

    Full Text Available The Caenorhabditis elegans left and right AWC olfactory neurons communicate to establish stochastic asymmetric identities, AWC(ON and AWC(OFF, by inhibiting a calcium-mediated signaling pathway in the future AWC(ON cell. NSY-4/claudin-like protein and NSY-5/innexin gap junction protein are the two parallel signals that antagonize the calcium signaling pathway to induce the AWC(ON fate. However, it is not known how the calcium signaling pathway is downregulated by nsy-4 and nsy-5 in the AWC(ON cell. Here we identify a microRNA, mir-71, that represses the TIR-1/Sarm1 adaptor protein in the calcium signaling pathway to promote the AWC(ON identity. Similar to tir-1 loss-of-function mutants, overexpression of mir-71 generates two AWC(ON neurons. tir-1 expression is downregulated through its 3' UTR in AWC(ON, in which mir-71 is expressed at a higher level than in AWC(OFF. In addition, mir-71 is sufficient to inhibit tir-1 expression in AWC through the mir-71 complementary site in the tir-1 3' UTR. Our genetic studies suggest that mir-71 acts downstream of nsy-4 and nsy-5 to promote the AWC(ON identity in a cell autonomous manner. Furthermore, the stability of mature mir-71 is dependent on nsy-4 and nsy-5. Together, these results provide insight into the mechanism by which nsy-4 and nsy-5 inhibit calcium signaling to establish stochastic asymmetric AWC differentiation.

  1. The microRNA mir-71 inhibits calcium signaling by targeting the TIR-1/Sarm1 adaptor protein to control stochastic L/R neuronal asymmetry in C. elegans.

    Science.gov (United States)

    Hsieh, Yi-Wen; Chang, Chieh; Chuang, Chiou-Fen

    2012-01-01

    The Caenorhabditis elegans left and right AWC olfactory neurons communicate to establish stochastic asymmetric identities, AWC(ON) and AWC(OFF), by inhibiting a calcium-mediated signaling pathway in the future AWC(ON) cell. NSY-4/claudin-like protein and NSY-5/innexin gap junction protein are the two parallel signals that antagonize the calcium signaling pathway to induce the AWC(ON) fate. However, it is not known how the calcium signaling pathway is downregulated by nsy-4 and nsy-5 in the AWC(ON) cell. Here we identify a microRNA, mir-71, that represses the TIR-1/Sarm1 adaptor protein in the calcium signaling pathway to promote the AWC(ON) identity. Similar to tir-1 loss-of-function mutants, overexpression of mir-71 generates two AWC(ON) neurons. tir-1 expression is downregulated through its 3' UTR in AWC(ON), in which mir-71 is expressed at a higher level than in AWC(OFF). In addition, mir-71 is sufficient to inhibit tir-1 expression in AWC through the mir-71 complementary site in the tir-1 3' UTR. Our genetic studies suggest that mir-71 acts downstream of nsy-4 and nsy-5 to promote the AWC(ON) identity in a cell autonomous manner. Furthermore, the stability of mature mir-71 is dependent on nsy-4 and nsy-5. Together, these results provide insight into the mechanism by which nsy-4 and nsy-5 inhibit calcium signaling to establish stochastic asymmetric AWC differentiation.

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

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    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.

  3. The Fe65 adaptor protein interacts through its PID1 domain with the transcription factor CP2/LSF/LBP1.

    Science.gov (United States)

    Zambrano, N; Minopoli, G; de Candia, P; Russo, T

    1998-08-07

    The neural protein Fe65 possesses three putative protein-protein interaction domains: one WW domain and two phosphotyrosine interaction/phosphotyrosine binding domains (PID1 and PID2); the most C-terminal of these domains (PID2) interacts in vivo with the Alzheimer's beta-amyloid precursor protein, whereas the WW domain binds to Mena, the mammalian homolog of Drosophila-enabled protein. By the interaction trap procedure, we isolated a cDNA clone encoding a possible ligand of the N-terminal PID/PTB domain of Fe65 (PID1). Sequence analysis of this clone revealed that this ligand corresponded to the previously identified transcription factor CP2/LSF/LBP1. Co-immunoprecipitation experiments demonstrated that the interaction between Fe65 and CP2/LSF/LBP1 also takes place in vivo between the native molecules. The localization of both proteins was studied using fractionated cellular extracts. These experiments demonstrated that the various isoforms of CP2/LSF/LBP1 are differently distributed among subcellular fractions. At least one isoform, derived from alternative splicing (LSF-ID), is present outside the nucleus; Fe65 was found in both fractions. Furthermore, transfection experiments with an HA-tagged CP2/LSF/LBP1 cDNA demonstrated that Fe65 interacts also with the nuclear form of CP2/LSF/LBP1. Considering that the analysis of Fe65 distribution in fractionated cell extracts demonstrated that this protein is present both in nuclear and non-nuclear fractions, we examined the expression of Fe65 deletion mutants in the two fractions. This analysis allowed us to observe that a small region N-terminal to the WW domain is phosphorylated and is necessary for the presence of Fe65 in the nuclear fraction.

  4. Human cancer protein-protein interaction network: a structural perspective.

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    Gozde Kar

    2009-12-01

    Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

  5. The adaptor molecule signaling lymphocytic activation molecule (SLAM)-associated protein (SAP) is essential in mechanisms involving the Fyn tyrosine kinase for induction and progression of collagen-induced arthritis.

    Science.gov (United States)

    Zhong, Ming-Chao; Veillette, André

    2013-11-01

    Signaling lymphocytic activation molecule-associated protein (SAP) is an Src homology 2 domain-only adaptor involved in multiple immune cell functions. It has also been linked to immunodeficiencies and autoimmune diseases, such as systemic lupus erythematosus. Here, we examined the role and mechanism of action of SAP in autoimmunity using a mouse model of autoimmune arthritis, collagen-induced arthritis (CIA). We found that SAP was essential for development of CIA in response to collagen immunization. It was also required for production of collagen-specific antibodies, which play a key role in disease pathogenesis. These effects required SAP expression in T cells, not in B cells. In mice immunized with a high dose of collagen, the activity of SAP was nearly independent of its ability to bind the protein tyrosine kinase Fyn and correlated with the capacity of SAP to promote full differentiation of follicular T helper (TFH) cells. However, with a lower dose of collagen, the role of SAP was more dependent on Fyn binding, suggesting that additional mechanisms other than TFH cell differentiation were involved. Further studies suggested that this might be due to a role of the SAP-Fyn interaction in natural killer T cell development through the ability of SAP-Fyn to promote Vav-1 activation. We also found that removal of SAP expression during progression of CIA attenuated disease severity. However, it had no effect on disease when CIA was clinically established. Together, these results indicate that SAP plays an essential role in CIA because of Fyn-independent and Fyn-dependent effects on TFH cells and, possibly, other T cell types.

  6. Defective jejunal and colonic salt absorption and alteredNa +/H+ exchanger 3 (NHE3) activity in NHE regulatory factor 1 (NHERF1) adaptor protein-deficient mice

    NARCIS (Netherlands)

    N. Broere (Nellie); M. Chen (Min); A. Cinar (Ayhan); A.K. Singh (Arbind); J. Hillesheim (Jutta); B. Riederer (Beat Michel); M. Lunnemann; I. Rottinghaus (Ingrid); A. Krabbenhöft (Anja); R. Engelhardt (Regina); B. Rausch; E.J. Weinman (Edward); M. Donowitz (Mark); A. Hubbard; O. Kocher (Olivier); H.R. de Jonge (Hugo); B.M. Hogema (Boris); U. Seidler (Ursula)

    2009-01-01

    textabstractWe investigated the role of the Na+/H+ exchanger regulatory factor 1 (NHERF1) on intestinal salt and water absorption, brush border membrane (BBM) morphology, and on the NHE3 mRNA expression, protein abundance, and transport activity in the murine intestine. NHERF1-deficient mice display

  7. Protein-protein interaction network of celiac disease

    Science.gov (United States)

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

    2016-01-01

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

  8. SLAM-family receptors: immune regulators with or without SAP-family adaptors.

    Science.gov (United States)

    Veillette, André

    2010-03-01

    The signaling lymphocytic activation molecule (SLAM) family of receptors and the SLAM-associated protein (SAP) family of intracellular adaptors are expressed in immune cells. By way of their cytoplasmic domain, SLAM-related receptors physically associate with SAP-related adaptors. Evidence is accumulating that the SLAM and SAP families play crucial roles in multiple immune cell types. Moreover, the prototype of the SAP family, that is SAP, is mutated in a human immunodeficiency, X-linked lymphoproliferative (XLP) disease. In the presence of SAP-family adaptors, the SLAM family usually mediates stimulatory signals that promote immune cell activation or differentiation. In the absence of SAP-family adaptors, though, the SLAM family undergoes a "switch-of-function," thereby mediating inhibitory signals that suppress immune cell functions. The molecular basis and significance of this mechanism are discussed herein.

  9. Reconstruction of human protein interolog network using evolutionary conserved network

    Directory of Open Access Journals (Sweden)

    Lin Chung-Yen

    2007-05-01

    Full Text Available Abstract Background The recent increase in the use of high-throughput two-hybrid analysis has generated large quantities of data on protein interactions. Specifically, the availability of information about experimental protein-protein interactions and other protein features on the Internet enables human protein-protein interactions to be computationally predicted from co-evolution events (interolog. This study also considers other protein interaction features, including sub-cellular localization, tissue-specificity, the cell-cycle stage and domain-domain combination. Computational methods need to be developed to integrate these heterogeneous biological data to facilitate the maximum accuracy of the human protein interaction prediction. Results This study proposes a relative conservation score by finding maximal quasi-cliques in protein interaction networks, and considering other interaction features to formulate a scoring method. The scoring method can be adopted to discover which protein pairs are the most likely to interact among multiple protein pairs. The predicted human protein-protein interactions associated with confidence scores are derived from six eukaryotic organisms – rat, mouse, fly, worm, thale cress and baker's yeast. Conclusion Evaluation results of the proposed method using functional keyword and Gene Ontology (GO annotations indicate that some confidence is justified in the accuracy of the predicted interactions. Comparisons among existing methods also reveal that the proposed method predicts human protein-protein interactions more accurately than other interolog-based methods.

  10. The Neuron-Specific Rai (ShcC) Adaptor Protein Inhibits Apoptosis by Coupling Ret to the Phosphatidylinositol 3-Kinase/Akt Signaling Pathway

    Science.gov (United States)

    Pelicci, Giuliana; Troglio, Flavia; Bodini, Alessandra; Melillo, Rosa Marina; Pettirossi, Valentina; Coda, Laura; De Giuseppe, Antonio; Santoro, Massimo; Pelicci, Pier Giuseppe

    2002-01-01

    Rai is a recently identified member of the family of Shc-like proteins, which are cytoplasmic signal transducers characterized by the unique PTB-CH1-SH2 modular organization. Rai expression is restricted to neuronal cells and regulates in vivo the number of postmitotic sympathetic neurons. We report here that Rai is not a common substrate of receptor tyrosine kinases under physiological conditions and that among the analyzed receptors (Ret, epidermal growth factor receptor, and TrkA) it is activated specifically by Ret. Overexpression of Rai in neuronal cell lines promoted survival by reducing apoptosis both under conditions of limited availability of the Ret ligand glial cell line-derived neurotrophic factor (GDNF) and in the absence of Ret activation. Overexpressed Rai resulted in the potentiation of the Ret-dependent activation of phosphatidylinositol 3-kinase (PI3K) and Akt. Notably, increased Akt phosphorylation and PI3K activity were also found under basal conditions, e.g., in serum-starved neuronal cells. Phosphorylated and hypophosphorylated Rai proteins form a constitutive complex with the p85 subunit of PI3K: upon Ret triggering, the Rai-PI3K complex is recruited to the tyrosine-phosphorylated Ret receptor through the binding of the Rai PTB domain to tyrosine 1062 of Ret. In neurons treated with low concentrations of GDNF, the prosurvival effect of Rai depends on Rai phosphorylation and Ret activation. In the absence of Ret activation, the prosurvival effect of Rai is, instead, phosphorylation independent. Finally, we showed that overexpression of Rai, at variance with Shc, had no effects on the early peak of mitogen-activated protein kinase (MAPK) activation, whereas it increased its activation at later time points. Phosphorylated Rai, however, was not found in complexes with Grb2. We propose that Rai potentiates the MAPK and PI3K signaling pathways and regulates Ret-dependent and -independent survival signals. PMID:12242309

  11. Neural Networks for protein Structure Prediction

    DEFF Research Database (Denmark)

    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...

  12. The polarity sub-network in the yeast network of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Luca Paris

    2011-12-01

    Full Text Available Rare, but highly connected, hub proteins subdivide hierarchically global networks of interacting proteins into modular clusters. Most biological research, however, focuses on functionally defined sub-networks. Thus, it is important to know whether the sub-networks retain the same topology of the global networks, from which they derive. To address this issue, we have analyzed the protein-protein interaction sub-network that participates in the polarized growth of the budding yeast Saccharomyces cerevisiae and that is derived from the global network of this model organism. We have observed that, in contrast to global networks, the distribution of connectivity k (i.e., the number of interactions per protein does not follow a power law, but decays exponentially, which reflects the local absence of hub proteins. Nonetheless, far from being randomly organized, the polarity sub-network can be subdivided into functional modules. In addition, most non-hub connector proteins, besides ensuring communications among modules, are linked mutually and contribute to the formation of the polarisome, a structure that coordinates actin assembly with polarized growth. These findings imply that identifying critical proteins within sub-networks (e.g., for the aim of targeted therapy requires searching not only for hubs but also for key non-hub connectors, which might remain otherwise unnoticed due to their relatively low connectivity.

  13. 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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Oleksii Kuchaiev

    2009-08-01

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

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

    DEFF Research Database (Denmark)

    Barres, Romain; Grémeaux, Thierry; Gual, Philippe

    2006-01-01

    a critical role in actin cytoskeleton organization in fibroblastic cells. Because actin rearrangement is important for insulin-induced glucose transporter 4 (Glut 4) translocation, we studied the potential involvement of Enigma in insulin-induced glucose transport in 3T3-L1 adipocytes. Enigma m......RNA was expressed in differentiated adipocytes and APS and Enigma were colocalized with cortical actin. Expression of an APS mutant unable to bind Enigma increased the insulin-induced Glut 4 translocation to the plasma membrane. By contrast, overexpression of Enigma inhibited insulin-stimulated glucose transport...... 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...

  16. Influence of degree correlations on network structure and stability in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Zimmer Ralf

    2007-08-01

    Full Text Available Abstract Background The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs. Results For each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks. Conclusion Considerable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree

  17. Protein enriched pasta: structure and digestibility of its protein network.

    Science.gov (United States)

    Laleg, Karima; Barron, Cécile; Santé-Lhoutellier, Véronique; Walrand, Stéphane; Micard, Valérie

    2016-02-01

    Wheat (W) pasta was enriched in 6% gluten (G), 35% faba (F) or 5% egg (E) to increase its protein content (13% to 17%). The impact of the enrichment on the multiscale structure of the pasta and on in vitro protein digestibility was studied. Increasing the protein content (W- vs. G-pasta) strengthened pasta structure at molecular and macroscopic scales but reduced its protein digestibility by 3% by forming a higher covalently linked protein network. Greater changes in the macroscopic and molecular structure of the pasta were obtained by varying the nature of protein used for enrichment. Proteins in G- and E-pasta were highly covalently linked (28-32%) resulting in a strong pasta structure. Conversely, F-protein (98% SDS-soluble) altered the pasta structure by diluting gluten and formed a weak protein network (18% covalent link). As a result, protein digestibility in F-pasta was significantly higher (46%) than in E- (44%) and G-pasta (39%). The effect of low (55 °C, LT) vs. very high temperature (90 °C, VHT) drying on the protein network structure and digestibility was shown to cause greater molecular changes than pasta formulation. Whatever the pasta, a general strengthening of its structure, a 33% to 47% increase in covalently linked proteins and a higher β-sheet structure were observed. However, these structural differences were evened out after the pasta was cooked, resulting in identical protein digestibility in LT and VHT pasta. Even after VHT drying, F-pasta had the best amino acid profile with the highest protein digestibility, proof of its nutritional interest.

  18. Network compression as a quality measure for protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Loic Royer

    Full Text Available With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients.

  19. Interface-resolved network of protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Margaret E Johnson

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Yang, Lei; Zhao, Xudong; Tang, Xianglong

    2014-01-01

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

  2. Neural network models of protein domain evolution

    OpenAIRE

    Sylvia Nagl

    2000-01-01

    Protein domains are complex adaptive systems, and here a novel procedure is presented that models the evolution of new functional sites within stable domain folds using neural networks. Neural networks, which were originally developed in cognitive science for the modeling of brain functions, can provide a fruitful methodology for the study of complex systems in general. Ethical implications of developing complex systems models of biomolecules are discussed, with particular reference to molecu...

  3. Data management of protein interaction networks

    CERN Document Server

    Cannataro, Mario

    2012-01-01

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

  4. DETECTION OF TOPOLOGICAL PATTERNS IN PROTEIN NETWORKS.

    Energy Technology Data Exchange (ETDEWEB)

    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

  5. DETECTION OF TOPOLOGICAL PATTERNS IN PROTEIN NETWORKS.

    Energy Technology Data Exchange (ETDEWEB)

    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

  6. Finding local communities in protein networks

    Directory of Open Access Journals (Sweden)

    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

  7. Spectral reconstruction of protein contact networks

    Science.gov (United States)

    Maiorino, Enrico; Rizzi, Antonello; Sadeghian, Alireza; Giuliani, Alessandro

    2017-04-01

    In this work, we present a method for generating an adjacency matrix encoding a typical protein contact network. This work constitutes a follow-up to our recent work (Livi et al., 2015), whose aim was to estimate the relative contribution of different topological features in discovering of the unique properties of protein structures. We perform a genetic algorithm based optimization in order to modify the matrices generated with the procedures explained in (Livi et al., 2015). Our objective here is to minimize the distance with respect to a target spectral density, which is elaborated using the normalized graph Laplacian representation of graphs. Such a target density is obtained by averaging the kernel-estimated densities of a class of experimental protein maps having different dimensions. This is possible given the bounded-domain property of the normalized Laplacian spectrum. By exploiting genetic operators designed for this specific problem and an exponentially-weighted objective function, we are able to reconstruct adjacency matrices representing networks of varying size whose spectral density is indistinguishable from the target. The topological features of the optimized networks are then compared to the real protein contact networks and they show an increased similarity with respect to the starting networks. Subsequently, the statistical properties of the spectra of the newly generated matrices are analyzed by employing tools borrowed from random matrix theory. The nearest neighbors spacing distribution of the spectra of the generated networks indicates that also the (short-range) correlations of the Laplacian eigenvalues are compatible with those of real proteins.

  8. A conserved mammalian protein interaction network.

    Directory of Open Access Journals (Sweden)

    Åsa Pérez-Bercoff

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

  9. Role of polymorphisms of toll-like receptor (TLR 4, TLR9, toll-interleukin 1 receptor domain containing adaptor protein (TIRAP and FCGR2A genes in malaria susceptibility and severity in Burundian children

    Directory of Open Access Journals (Sweden)

    Esposito Susanna

    2012-06-01

    Full Text Available Abstract Background Malaria caused by Plasmodium falciparum is one of the leading causes of human morbidity and mortality from infectious diseases, predominantly in tropical and sub-tropical countries. As genetic variations in the toll-like receptors (TLRs-signalling pathway have been associated with either susceptibility or resistance to several infectious and inflammatory diseases, the supposition is that single nucleotide polymorphisms (SNPs of TLR2, TLR4, TLR9, Toll-interleukin 1 receptor domain containing adaptor protein (TIRAP and FCGR2A could modulate malaria susceptibility and severity. Methods This study was planned to make a further contribution to solving the problem of the real role of the most common polymorphisms of TLR4, TLR9, TIRAP and FCGR2A genes in modulating the risk of malaria and disease severity in children from Burundi, Central Africa. All the paediatric patients aged six months to 10 years admitted to the hospital of Kiremba, Burundi, between February 2011 and September 2011, for fever and suspicion of acute malaria were screened for malaria parasitaemia by light microscopy of thick and thin blood smears. In children with malaria and in uninfected controls enrolled during the study period in the same hospital, blood samples were obtained on filter paper and TLR4 Asp299Gly rs4986790, TLR9 G1174A rs352139, T-1486 C rs187084 TLR9 T-1237 C rs5743836, TIRAP Ser180Leu rs8177374 and the FCGR2A His131Arg rs1801274 polymorphisms were studied using an ABI PRISM 7900 HT Fast Real-time instrument. Results A total of 602 patients and 337 controls were enrolled. Among the malaria cases, 553 (91.9 % were considered as suffering from uncomplicated and 49 (8.1 % from severe malaria. TLR9 T1237C rs5743836CC was associated with an increased risk of developing malaria (p = 0.03, although it was found with the same frequency in uncomplicated and severe malaria cases. No other differences were found in all alleles studied and in

  10. Analysis of protein folds using protein contact networks

    Indian Academy of Sciences (India)

    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.

  11. Adaptor protein Crk Ⅰ mediates malignant potential of human ovarian cancer%接合物蛋白CrkⅠ在卵巢癌恶性潜能中的作用

    Institute of Scientific and Technical Information of China (English)

    车亚玲; 王瑾; 令狐华

    2011-01-01

    Objective To explore the role of adaptor protein Crk Ⅰ in malignant potential of human ovarian cancer. Methods Crk and Dock180 expression were detected by Western blotting in ovarian cancer tissues (EOC, n =28), benign ovarian tumors (BOT, n =13) and normal ovary tissues (Normal, n =10). Co-precipitation was performed to evaluate the in vivo protein-protein interaction of Dock180 and Crk Ⅰn 3 different ovarian cancer cell lines ( SKOV3, MCAS and RMUG-L cells). The expression of Crk Ⅰn SKOV3 cells were silenced by using siRNA interference, and then Rac1 activity and cell invasion in the transfected cells were observed. Results The intensity of Crk Ⅰ and Dock180 expression was consistent with each other in EOC tissues. Both were observed to be significantly higher in EOC than those in the BOT and normal ovary tissues(P < 0. 05 ). No significant difference was found between BOT and Normal group either for Crk Ⅰ or Dock180 expression (P > 0. 05 ). In consistent with this result, Dock180 preferred to combine with Crk Ⅰ rather than with Crk Ⅱ in all 3 ovarian cancer cell lines. Furthermore, Crk knockdown celIs presented with sustainable Crk Ⅰ expression depletion, significantly decreased Rac1 activity and cell invasion. Conclusion Crk might be involved in malignant potential of human EOC mainly through Crk Ⅰ/Dock180/Rac1 pathway.%目的 证实接合物蛋白CrkⅠ在卵巢癌恶性潜能中的作用.方法 采用Western blot法检测卵巢癌组织、卵巢良性肿瘤组织、正常卵巢组织中Crk和Dock180蛋白的表达;用免疫沉淀法检测3种卵巢癌细胞株中Crk与Dock180蛋白的内源性结合;用小干扰RNA敲低SKOV3细胞中内源性的Crk,检测Crk表达缺失性细胞Crk蛋白表达水平、Rac1酶活性和侵袭力的变化.结果 Dock180与CrkⅠ的表达强度呈现明显的一致性,卵巢癌组织中二者的表达均显著高于卵巢良性肿瘤组织和正常卵巢组织(P0.05).3个卵巢癌细胞株中Dock180主要

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

    Science.gov (United States)

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

    2015-01-01

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

  13. Styles of Creativity: Adaptors and Innovators in a Singapore Context

    Science.gov (United States)

    Ee, Jessie; Seng, Tan Oon; Kwang, Ng Aik

    2007-01-01

    Kirton (1976) described two creative styles, namely adaptors and innovators. Adaptors prefer to "do things better" whilst, innovators prefer to "do things differently". This study explored the relationship between two creative styles (adaptor and innovator) and the Big Five personality traits (extraversion, agreeableness, conscientiousness,…

  14. WD40 proteins propel cellular networks.

    Science.gov (United States)

    Stirnimann, Christian U; Petsalaki, Evangelia; Russell, Robert B; Müller, Christoph W

    2010-10-01

    Recent findings indicate that WD40 domains play central roles in biological processes by acting as hubs in cellular networks; however, they have been studied less intensely than other common domains, such as the kinase, PDZ or SH3 domains. As suggested by various interactome studies, they are among the most promiscuous interactors. Structural studies suggest that this property stems from their ability, as scaffolds, to interact with diverse proteins, peptides or nucleic acids using multiple surfaces or modes of interaction. A general scaffolding role is supported by the fact that no WD40 domain has been found with intrinsic enzymatic activity despite often being part of large molecular machines. We discuss the WD40 domain distributions in protein networks and structures of WD40-containing assemblies to demonstrate their versatility in mediating critical cellular functions.

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

    Institute of Scientific and Technical Information of China (English)

    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.

  16. Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case

    Directory of Open Access Journals (Sweden)

    Guang Hu

    2017-01-01

    Full Text Available The overall topology and interfacial interactions play key roles in understanding structural and functional principles of protein complexes. Elastic Network Model (ENM and Protein Contact Network (PCN are two widely used methods for high throughput investigation of structures and interactions within protein complexes. In this work, the comparative analysis of ENM and PCN relative to hemoglobin (Hb was taken as case study. We examine four types of structural and dynamical paradigms, namely, conformational change between different states of Hbs, modular analysis, allosteric mechanisms studies, and interface characterization of an Hb. The comparative study shows that ENM has an advantage in studying dynamical properties and protein-protein interfaces, while PCN is better for describing protein structures quantitatively both from local and from global levels. We suggest that the integration of ENM and PCN would give a potential but powerful tool in structural systems biology.

  17. SLAM family receptors and SAP adaptors in immunity.

    Science.gov (United States)

    Cannons, Jennifer L; Tangye, Stuart G; Schwartzberg, Pamela L

    2011-01-01

    The signaling lymphocyte activation molecule (SLAM)-associated protein, SAP, was first identified as the protein affected in most cases of X-linked lymphoproliferative (XLP) syndrome, a rare genetic disorder characterized by abnormal responses to Epstein-Barr virus infection, lymphoproliferative syndromes, and dysgammaglobulinemia. SAP consists almost entirely of a single SH2 protein domain that interacts with the cytoplasmic tail of SLAM and related receptors, including 2B4, Ly108, CD84, Ly9, and potentially CRACC. SLAM family members are now recognized as important immunomodulatory receptors with roles in cytotoxicity, humoral immunity, autoimmunity, cell survival, lymphocyte development, and cell adhesion. In this review, we cover recent findings on the roles of SLAM family receptors and the SAP family of adaptors, with a focus on their regulation of the pathways involved in the pathogenesis of XLP and other immune disorders.

  18. Probing heterobivalent binding to the endocytic AP-2 adaptor complex by DNA-based spatial screening.

    Science.gov (United States)

    Diezmann, F; von Kleist, L; Haucke, V; Seitz, O

    2015-08-01

    The double helical DNA scaffold offers a unique set of properties, which are particularly useful for studies of multivalency in biomolecular interactions: (i) multivalent ligand displays can be formed upon nucleic acid hybridization in a self-assembly process, which facilitates spatial screening (ii) valency and spatial arrangement of the ligand display can be precisely controlled and (iii) the flexibility of the ligand display can be adjusted by integrating nick sites and unpaired template regions. Herein we describe the use of DNA-based spatial screening for the characterization of the adaptor complex 2 (AP-2), a central interaction hub within the endocytic protein network in clathrin-mediated endocytosis. AP-2 is comprised of a core domain and two, so-called appendage domains, the α- and the β2-ear, which associate with cytoplasmatic proteins required for the formation or maturation of clathrin/AP-2 coated pits. Each appendage domain has two binding grooves which recognize distinct peptide motives with micromolar affinity. This provides opportunities for enhanced interactions with protein molecules that contain two (or more) different peptide motives. To determine whether a particular, spatial arrangement of binding motifs is required for high affinity binding we probed the distance-affinity relationships by means of DNA-programmed spatial screening with self-assembled peptide-DNA complexes. By using trimolecular and tetramolecular assemblies two different peptides were positioned in 2-22 nucleotide distance. The binding data obtained with both recombinant protein in well-defined buffer systems and native AP-2 in brain extract suggests that the two binding sites of the AP-2 α-appendage can cooperate to provide up to 40-fold enhancement of affinity compared to the monovalent interaction. The distance between the two recognized peptide motives was less important provided that the DNA duplex segments were connected by flexible, single strand segments. By

  19. Protein Structure Network-based Drug Design.

    Science.gov (United States)

    Liang, Zhongjie; Hu, Guang

    2016-01-01

    Although structure-based drug design (SBDD) has become an indispensable tool in drug discovery for a long time, it continues to pose major challenges to date. With the advancement of "omics" techniques, systems biology has enriched SBDD into a new era, called polypharmacology, in which multi-targets drug or drug combination is designed to fight complex diseases. As a preliminary tool in systems biology, protein structure networks (PSNs) treat a protein as a set of residues linked by edges corresponding to the intramolecular interactions existing in folded structures between the residues. The PSN offers a computationally efficient tool to study the structure and function of proteins, and thus may facilitate structurebased drug design. Herein, we provide an overview of recent advances in PSNs, from predicting functionally important residues, to charactering protein-protein interactions and allosteric communication paths. Furthermore, we discuss potential pharmacological applications of PSN concepts and tools, and highlight the application to two families of drug targets, GPCRs and Hsp90. Although the application of PSNs as a framework for computer-aided drug discovery has been limited to date, we put forward the potential utility value in the near future and propose the PSNs could also serve as a new tool for polypharmacology research.

  20. Construction of ontology augmented networks for protein complex prediction.

    Science.gov (United States)

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

    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 augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

  1. Discriminating lysosomal membrane protein types using dynamic neural network.

    Science.gov (United States)

    Tripathi, Vijay; Gupta, Dwijendra Kumar

    2014-01-01

    This work presents a dynamic artificial neural network methodology, which classifies the proteins into their classes from their sequences alone: the lysosomal membrane protein classes and the various other membranes protein classes. In this paper, neural networks-based lysosomal-associated membrane protein type prediction system is proposed. Different protein sequence representations are fused to extract the features of a protein sequence, which includes seven feature sets; amino acid (AA) composition, sequence length, hydrophobic group, electronic group, sum of hydrophobicity, R-group, and dipeptide composition. To reduce the dimensionality of the large feature vector, we applied the principal component analysis. The probabilistic neural network, generalized regression neural network, and Elman regression neural network (RNN) are used as classifiers and compared with layer recurrent network (LRN), a dynamic network. The dynamic networks have memory, i.e. its output depends not only on the input but the previous outputs also. Thus, the accuracy of LRN classifier among all other artificial neural networks comes out to be the highest. The overall accuracy of jackknife cross-validation is 93.2% for the data-set. These predicted results suggest that the method can be effectively applied to discriminate lysosomal associated membrane proteins from other membrane proteins (Type-I, Outer membrane proteins, GPI-Anchored) and Globular proteins, and it also indicates that the protein sequence representation can better reflect the core feature of membrane proteins than the classical AA composition.

  2. The myxoma virus m-t5 ankyrin repeat host range protein is a novel adaptor that coordinately links the cellular signaling pathways mediated by Akt and Skp1 in virus-infected cells.

    Science.gov (United States)

    Werden, Steven J; Lanchbury, Jerry; Shattuck, Donna; Neff, Chris; Dufford, Max; McFadden, Grant

    2009-12-01

    Most poxviruses express multiple proteins containing ankyrin (ANK) repeats accounting for a large superfamily of related but unique determinants of poxviral tropism. Recently, select members of this novel family of poxvirus proteins have drawn considerable attention for their potential roles in modulating intracellular signaling networks during viral infection. The rabbit-specific poxvirus, myxoma virus (MYXV), encodes four unique ANK repeat proteins, termed M-T5, M148, M149, and M150, all of which include a carboxy-terminal PRANC domain which closely resembles a cellular protein motif called the F-box domain. Here, we show that each MYXV-encoded ANK repeat protein, including M-T5, interacts directly with the Skp1 component of the host SCF ubiquitin ligase complex, and that the binding of M-T5 to cullin 1 is indirect via binding to Skp1 in the host SCF complex. To understand the significance of these virus-host protein interactions, the various binding domains of M-T5 were mapped. The N-terminal ANK repeats I and II were identified as being important for interaction with Akt, whereas the C-terminal PRANC/F-box-like domain was essential for binding to Skp1. We also report that M-T5 can bind Akt and the host SCF complex (via Skp1) simultaneously in MYXV-infected cells. Finally, we report that M-T5 specifically mediates the relocalization of Akt from the nucleus to the cytoplasm during infection with the wild-type MYXV, but not the M-T5 knockout version of the virus. These results indicate that ANK/PRANC proteins play a critical role in reprogramming disparate cellular signaling cascades to establish a new cellular environment more favorable for virus replication.

  3. Protein interaction network related to Helicobacter pylori infection response

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. Mining minimal motif pair sets maximally covering interactions in a protein-protein interaction network

    NARCIS (Netherlands)

    Boyen, P.; Neven, F.; Valentim, F.L.; Dijk, van A.D.J.

    2013-01-01

    Correlated motif covering (CMC) is the problem of finding a set of motif pairs, i.e., pairs of patterns, in the sequences of proteins from a protein-protein interaction network (PPI-network) that describe the interactions in the network as concisely as possible. In other words, a perfect solution fo

  6. Scaffold functions of 14-3-3 adaptors in B cell immunoglobulin class switch DNA recombination.

    Science.gov (United States)

    Lam, Tonika; Thomas, Lisa M; White, Clayton A; Li, Guideng; Pone, Egest J; Xu, Zhenming; Casali, Paolo

    2013-01-01

    Class switch DNA recombination (CSR) of the immunoglobulin heavy chain (IgH) locus crucially diversifies antibody biological effector functions. CSR involves the induction of activation-induced cytidine deaminase (AID) expression and AID targeting to switch (S) regions by 14-3-3 adaptors. 14-3-3 adaptors specifically bind to 5'-AGCT-3' repeats, which make up for the core of all IgH locus S regions. They selectively target the upstream and downstream S regions that are set to undergo S-S DNA recombination. We hypothesized that 14-3-3 adaptors function as scaffolds to stabilize CSR enzymatic elements on S regions. Here we demonstrate that all seven 14-3-3β, 14-3-3ε, 14-3-3γ, 14-3-3η, 14-3-3σ, 14-3-3τ and 14-3-3ζ adaptors directly interacted with AID, PKA-Cα (catalytic subunit) and PKA-RIα (regulatory inhibitory subunit) and uracil DNA glycosylase (Ung). 14-3-3 adaptors, however, did not interact with AID C-terminal truncation mutant AIDΔ(180-198) or AIDF193A and AIDL196A point-mutants (which have been shown not to bind to S region DNA and fail to mediate CSR). 14-3-3 adaptors colocalized with AID and replication protein A (RPA) in B cells undergoing CSR. 14-3-3 and AID binding to S region DNA was disrupted by viral protein R (Vpr), an accessory protein of human immunodeficiency virus type-1 (HIV-1), which inhibited CSR without altering AID expression or germline IH-CH transcription. Accordingly, we demonstrated that 14-3-3 directly interact with Vpr, which in turn, also interact with AID, PKA-Cα and Ung. Altogether, our findings suggest that 14-3-3 adaptors play important scaffold functions and nucleate the assembly of multiple CSR factors on S regions. They also show that such assembly can be disrupted by a viral protein, thereby allowing us to hypothesize that small molecule compounds that specifically block 14-3-3 interactions with AID, PKA and/or Ung can be used to inhibit unwanted CSR.

  7. Scaffold functions of 14-3-3 adaptors in B cell immunoglobulin class switch DNA recombination.

    Directory of Open Access Journals (Sweden)

    Tonika Lam

    Full Text Available Class switch DNA recombination (CSR of the immunoglobulin heavy chain (IgH locus crucially diversifies antibody biological effector functions. CSR involves the induction of activation-induced cytidine deaminase (AID expression and AID targeting to switch (S regions by 14-3-3 adaptors. 14-3-3 adaptors specifically bind to 5'-AGCT-3' repeats, which make up for the core of all IgH locus S regions. They selectively target the upstream and downstream S regions that are set to undergo S-S DNA recombination. We hypothesized that 14-3-3 adaptors function as scaffolds to stabilize CSR enzymatic elements on S regions. Here we demonstrate that all seven 14-3-3β, 14-3-3ε, 14-3-3γ, 14-3-3η, 14-3-3σ, 14-3-3τ and 14-3-3ζ adaptors directly interacted with AID, PKA-Cα (catalytic subunit and PKA-RIα (regulatory inhibitory subunit and uracil DNA glycosylase (Ung. 14-3-3 adaptors, however, did not interact with AID C-terminal truncation mutant AIDΔ(180-198 or AIDF193A and AIDL196A point-mutants (which have been shown not to bind to S region DNA and fail to mediate CSR. 14-3-3 adaptors colocalized with AID and replication protein A (RPA in B cells undergoing CSR. 14-3-3 and AID binding to S region DNA was disrupted by viral protein R (Vpr, an accessory protein of human immunodeficiency virus type-1 (HIV-1, which inhibited CSR without altering AID expression or germline IH-CH transcription. Accordingly, we demonstrated that 14-3-3 directly interact with Vpr, which in turn, also interact with AID, PKA-Cα and Ung. Altogether, our findings suggest that 14-3-3 adaptors play important scaffold functions and nucleate the assembly of multiple CSR factors on S regions. They also show that such assembly can be disrupted by a viral protein, thereby allowing us to hypothesize that small molecule compounds that specifically block 14-3-3 interactions with AID, PKA and/or Ung can be used to inhibit unwanted CSR.

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

    Directory of Open Access Journals (Sweden)

    Isambert Hervé

    2007-11-01

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

  9. Identifying drug-target proteins based on network features

    Institute of Scientific and Technical Information of China (English)

    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.

  10. Identifying drug-target proteins based on network features

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Science.gov (United States)

    Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

    2013-04-01

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

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

    Science.gov (United States)

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

    2012-07-01

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

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

    DEFF Research Database (Denmark)

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

    2017-01-01

    Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (In...

  14. A least square method based model for identifying protein complexes in protein-protein interaction network.

    Science.gov (United States)

    Dai, Qiguo; Guo, Maozu; Guo, Yingjie; Liu, Xiaoyan; Liu, Yang; Teng, Zhixia

    2014-01-01

    Protein complex formed by a group of physical interacting proteins plays a crucial role in cell activities. Great effort has been made to computationally identify protein complexes from protein-protein interaction (PPI) network. However, the accuracy of the prediction is still far from being satisfactory, because the topological structures of protein complexes in the PPI network are too complicated. This paper proposes a novel optimization framework to detect complexes from PPI network, named PLSMC. The method is on the basis of the fact that if two proteins are in a common complex, they are likely to be interacting. PLSMC employs this relation to determine complexes by a penalized least squares method. PLSMC is applied to several public yeast PPI networks, and compared with several state-of-the-art methods. The results indicate that PLSMC outperforms other methods. In particular, complexes predicted by PLSMC can match known complexes with a higher accuracy than other methods. Furthermore, the predicted complexes have high functional homogeneity.

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

    Institute of Scientific and Technical Information of China (English)

    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.

  16. An organized co-assembly of clathrin adaptors is essential for endocytosis.

    Science.gov (United States)

    Skruzny, Michal; Desfosses, Ambroise; Prinz, Simone; Dodonova, Svetlana O; Gieras, Anna; Uetrecht, Charlotte; Jakobi, Arjen J; Abella, Marc; Hagen, Wim J H; Schulz, Joachim; Meijers, Rob; Rybin, Vladimir; Briggs, John A G; Sachse, Carsten; Kaksonen, Marko

    2015-04-20

    Clathrin-mediated endocytosis, the main trafficking route from the plasma membrane to the cytoplasm, is critical to many fundamental cellular processes. Clathrin, coupled to the membrane by adaptor proteins, is thought to play a major structural role in endocytosis by self-assembling into a cage-like lattice around the forming vesicle. Although clathrin adaptors are essential for endocytosis, little is known about their structural role in this process. Here we show that the membrane-binding domains of two conserved clathrin adaptors, Sla2 and Ent1, co-assemble in a PI(4,5)P2-dependent manner to form organized lattices on membranes. We determined the structure of the co-assembled lattice by electron cryo-microscopy and designed mutations that specifically impair the lattice formation in vitro. We show that these mutations block endocytosis in vivo. We suggest that clathrin adaptors not only link the polymerized clathrin to the membrane but also form an oligomeric structure, which is essential for membrane remodeling during endocytosis.

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

    Directory of Open Access Journals (Sweden)

    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

  18. Combining neural networks for protein secondary structure prediction

    DEFF Research Database (Denmark)

    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...

  19. Topological Analyses of Protein-Ligand Binding: a Network Approach.

    Science.gov (United States)

    Costanzi, Stefano

    2016-01-01

    Proteins can be conveniently represented as networks of interacting residues, thus allowing the study of several network parameters that can shed light onto several of their structural and functional aspects. With respect to the binding of ligands, which are central for the function of many proteins, network analysis may constitute a possible route to assist the identification of binding sites. As the bulk of this review illustrates, this has generally been easier for enzymes than for non-enzyme proteins, perhaps due to the different topological nature of the binding sites of the former over those of the latter. The article also illustrates how network representations of binding sites can be used to search PDB structures in order to identify proteins that bind similar molecules and, lastly, how codifying proteins as networks can assist the analysis of the conformational changes consequent to ligand binding.

  20. The architectural design of networks of protein domain architectures.

    Science.gov (United States)

    Hsu, Chia-Hsin; Chen, Chien-Kuo; Hwang, Ming-Jing

    2013-08-23

    Protein domain architectures (PDAs), in which single domains are linked to form multiple-domain proteins, are a major molecular form used by evolution for the diversification of protein functions. However, the design principles of PDAs remain largely uninvestigated. In this study, we constructed networks to connect domain architectures that had grown out from the same single domain for every single domain in the Pfam-A database and found that there are three main distinctive types of these networks, which suggests that evolution can exploit PDAs in three different ways. Further analysis showed that these three different types of PDA networks are each adopted by different types of protein domains, although many networks exhibit the characteristics of more than one of the three types. Our results shed light on nature's blueprint for protein architecture and provide a framework for understanding architectural design from a network perspective.

  1. Enhancing the functional content of eukaryotic protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Gaurav Pandey

    Full Text Available Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over 100 GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the HC.cont measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks.

  2. Convolutional LSTM Networks for Subcellular Localization of Proteins

    OpenAIRE

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

  3. Disordered proteins and network disorder in network descriptions of protein structure, dynamics and function: hypotheses and a comprehensive review.

    Science.gov (United States)

    Csermely, Peter; Sandhu, Kuljeet Singh; Hazai, Eszter; Hoksza, Zsolt; Kiss, Huba J M; Miozzo, Federico; Veres, Dániel V; Piazza, Francesco; Nussinov, Ruth

    2012-02-01

    During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here we review the links between disordered proteins and the associated networks, and describe the consequences of local, mesoscopic and global network disorder on changes in protein structure and dynamics. We introduce a new classification of protein networks into 'cumulus-type', i.e., those similar to puffy (white) clouds, and 'stratus-type', i.e., those similar to flat, dense (dark) low-lying clouds, and relate these network types to protein disorder dynamics and to differences in energy transmission processes. In the first class, there is limited overlap between the modules, which implies higher rigidity of the individual units; there the conformational changes can be described by an 'energy transfer' mechanism. In the second class, the topology presents a compact structure with significant overlap between the modules; there the conformational changes can be described by 'multi-trajectories'; that is, multiple highly populated pathways. We further propose that disordered protein regions evolved to help other protein segments reach 'rarely visited' but functionally-related states. We also show the role of disorder in 'spatial games' of amino acids; highlight the effects of intrinsically disordered proteins (IDPs) on cellular networks and list some possible studies linking protein disorder and protein structure networks.

  4. TRAM is involved in IL-18 signaling and functions as a sorting adaptor for MyD88.

    Directory of Open Access Journals (Sweden)

    Hidenori Ohnishi

    Full Text Available MyD88, a Toll/interleukin-1 receptor homology (TIR domain-containing adaptor protein, mediates signals from the Toll-like receptors (TLR or IL-1/IL-18 receptors to downstream kinases. In MyD88-dependent TLR4 signaling, the function of MyD88 is enhanced by another TIR domain-containing adaptor, Mal/TIRAP, which brings MyD88 to the plasma membrane and promotes its interaction with the cytosolic region of TLR4. Hence, Mal is recognized as the "sorting adaptor" for MyD88. In this study, a direct interaction between MyD88-TIR and another membrane-sorting adaptor, TRAM/TICAM-2, was demonstrated in vitro. Cell-based assays including RNA interference experiments and TRAM deficient mice revealed that the interplay between MyD88 and TRAM in cells is important in mediating IL-18 signal transduction. Live cell imaging further demonstrated the co-localized accumulation of MyD88 and TRAM in the membrane regions in HEK293 cells. These findings suggest that TRAM serves as the sorting adaptor for MyD88 in IL-18 signaling, which then facilitates the signal transduction. The binding sites for TRAM are located in the TIR domain of MyD88 and actually overlap with the binding sites for Mal. MyD88, the multifunctional signaling adaptor that works together with most of the TLR members and with the IL-1/IL-18 receptors, can interact with two distinct sorting adaptors, TRAM and Mal, in a conserved manner in a distinct context.

  5. Graph spectral analysis of protein interaction network evolution

    OpenAIRE

    Thorne, Thomas; Stumpf, Michael P. H.

    2012-01-01

    We present an analysis of protein interaction network data via the comparison of models of network evolution to the observed data. We take a Bayesian approach and perform posterior density estimation using an approximate Bayesian computation with sequential Monte Carlo method. Our approach allows us to perform model selection over a selection of potential network growth models. The methodology we apply uses a distance defined in terms of graph spectra which captures the network data more natu...

  6. Evolutionary pressure on the topology of protein interface interaction networks.

    Science.gov (United States)

    Johnson, Margaret E; Hummer, Gerhard

    2013-10-24

    The densely connected structure of protein-protein interaction (PPI) networks reflects the functional need of proteins to cooperate in cellular processes. However, PPI networks do not adequately capture the competition in protein binding. By contrast, the interface interaction network (IIN) studied here resolves the modular character of protein-protein binding and distinguishes between simultaneous and exclusive interactions that underlie both cooperation and competition. We show that the topology of the IIN is under evolutionary pressure, and we connect topological features of the IIN to specific biological functions. To reveal the forces shaping the network topology, we use a sequence-based computational model of interface binding along with network analysis. We find that the more fragmented structure of IINs, in contrast to the dense PPI networks, arises in large part from the competition between specific and nonspecific binding. The need to minimize nonspecific binding favors specific network motifs, including a minimal number of cliques (i.e., fully connected subgraphs) and many disconnected fragments. Validating the model, we find that these network characteristics are closely mirrored in the IIN of clathrin-mediated endocytosis. Features unexpected on the basis of our motif analysis are found to indicate either exceptional binding selectivity or important regulatory functions.

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

    Science.gov (United States)

    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.

  8. Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.

    Directory of Open Access Journals (Sweden)

    Martin H Schaefer

    Full Text Available Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs, which are conditional on the cellular context: both interacting proteins must be expressed in the same cell and localized in the same organelle to meet. Additionally, interactions underlie a delicate control of signaling pathways, e.g. by post-translational modifications of the protein partners - hence, many diseases are caused by the perturbation of these mechanisms. Despite the high degree of cell-state specificity of PPIs, many interactions are measured under artificial conditions (e.g. yeast cells are transfected with human genes in yeast two-hybrid assays or even if detected in a physiological context, this information is missing from the common PPI databases. To overcome these problems, we developed a method that assigns context information to PPIs inferred from various attributes of the interacting proteins: gene expression, functional and disease annotations, and inferred pathways. We demonstrate that context consistency correlates with the experimental reliability of PPIs, which allows us to generate high-confidence tissue- and function-specific subnetworks. We illustrate how these context-filtered networks are enriched in bona fide pathways and disease proteins to prove the ability of context-filters to highlight meaningful interactions with respect to various biological questions. We use this approach to study the lung-specific pathways used by the influenza virus, pointing to IRAK1, BHLHE40 and TOLLIP as potential regulators of influenza virus pathogenicity, and to study the signalling pathways that play a role in Alzheimer's disease, identifying a pathway involving the altered phosphorylation of the Tau protein. Finally, we provide the

  9. Optimization of multiplexed RADseq libraries using low-cost adaptors.

    Science.gov (United States)

    Henri, Hélène; Cariou, Marie; Terraz, Gabriel; Martinez, Sonia; El Filali, Adil; Veyssiere, Marine; Duret, Laurent; Charlat, Sylvain

    2015-04-01

    Reduced representation genomics approaches, of which RADseq is currently the most popular form, offer the possibility to produce genome wide data from potentially any species, without previous genomic information. The application of RADseq to highly multiplexed libraries (including numerous specimens, and potentially numerous different species) is however limited by technical constraints. First, the cost of synthesis of Illumina adaptors including molecular identifiers (MIDs) becomes excessive when numerous specimens are to be multiplexed. Second, the necessity to empirically adjust the ratio of adaptors to genomic DNA concentration impedes the high throughput application of RADseq to heterogeneous samples, of variable DNA concentration and quality. In an attempt to solve these problems, we propose here some adjustments regarding the adaptor synthesis. First, we show that the common and unique (MID) parts of adaptors can be synthesized separately and subsequently ligated, which drastically reduces the synthesis cost, and thus allows multiplexing hundreds of specimens. Second, we show that self-ligation of adaptors, which makes the adaptor concentration so critical, can be simply prevented by using unphosphorylated adaptors, which significantly improves the ligation and sequencing yield.

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

    Science.gov (United States)

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

    2012-01-01

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

  11. PANADA: protein association network annotation, determination and analysis.

    Directory of Open Access Journals (Sweden)

    Alberto J M Martin

    Full Text Available Increasingly large numbers of proteins require methods for functional annotation. This is typically based on pairwise inference from the homology of either protein sequence or structure. Recently, similarity networks have been presented to leverage both the ability to visualize relationships between proteins and assess the transferability of functional inference. Here we present PANADA, a novel toolkit for the visualization and analysis of protein similarity networks in Cytoscape. Networks can be constructed based on pairwise sequence or structural alignments either on a set of proteins or, alternatively, by database search from a single sequence. The Panada web server, executable for download and examples and extensive help files are available at URL: http://protein.bio.unipd.it/panada/.

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

    Directory of Open Access Journals (Sweden)

    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

  13. Dissipative electro-elastic network model of protein electrostatics

    CERN Document Server

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

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

    Science.gov (United States)

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

    2016-05-19

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

  17. Network based approaches reveal clustering in protein point patterns

    Science.gov (United States)

    Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

    2014-03-01

    Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

  18. A quantitative approach to study indirect effects among disease proteins in the human protein interaction network

    Directory of Open Access Journals (Sweden)

    Jordán Ferenc

    2010-07-01

    Full Text Available Abstract Background Systems biology makes it possible to study larger and more intricate systems than before, so it is now possible to look at the molecular basis of several diseases in parallel. Analyzing the interaction network of proteins in the cell can be the key to understand how complex processes lead to diseases. Novel tools in network analysis provide the possibility to quantify the key interacting proteins in large networks as well as proteins that connect them. Here we suggest a new method to study the relationships between topology and functionality of the protein-protein interaction network, by identifying key mediator proteins possibly maintaining indirect relationships among proteins causing various diseases. Results Based on the i2d and OMIM databases, we have constructed (i a network of proteins causing five selected diseases (DP, disease proteins plus their interacting partners (IP, non-disease proteins, the DPIP network and (ii a protein network showing only these IPs and their interactions, the IP network. The five investigated diseases were (1 various cancers, (2 heart diseases, (3 obesity, (4 diabetes and (5 autism. We have quantified the number and strength of IP-mediated indirect effects between the five groups of disease proteins and hypothetically identified the most important mediator proteins linking heart disease to obesity or diabetes in the IP network. The results present the relationship between mediator role and centrality, as well as between mediator role and functional properties of these proteins. Conclusions We show that a protein which plays an important indirect mediator role between two diseases is not necessarily a hub in the PPI network. This may suggest that, even if hub proteins and disease proteins are trivially of great interest, mediators may also deserve more attention, especially if disease-disease associations are to be understood. Identifying the hubs may not be sufficient to understand

  19. Characterization of Protein-Protein Interfaces through a Protein Contact Network Approach.

    Science.gov (United States)

    Di Paola, Luisa; Platania, Chiara Bianca Maria; Oliva, Gabriele; Setola, Roberto; Pascucci, Federica; Giuliani, Alessandro

    2015-01-01

    Anthrax toxin comprises three different proteins, jointly acting to exert toxic activity: a non-toxic protective agent (PA), toxic edema factor (EF), and lethal factor (LF). Binding of PA to anthrax receptors promotes oligomerization of PA, binding of EF and LF, and then endocytosis of the complex. Homomeric forms of PA, complexes of PA bound to LF and to the endogenous receptor capillary morphogenesis gene 2 (CMG2) were analyzed. In this work, we characterized protein-protein interfaces (PPIs) and identified key residues at PPIs of complexes, by means of a protein contact network (PCN) approach. Flexibility and global and local topological properties of each PCN were computed. The vulnerability of each PCN was calculated using different node removal strategies, with reference to specific PCN topological descriptors, such as participation coefficient, contact order, and degree. The participation coefficient P, the topological descriptor of the node's ability to intervene in protein inter-module communication, was the key descriptor of PCN vulnerability of all structures. High P residues were localized both at PPIs and other regions of complexes, so that we argued an allosteric mechanism in protein-protein interactions. The identification of residues, with key role in the stability of PPIs, has a huge potential in the development of new drugs, which would be designed to target not only PPIs but also residues localized in allosteric regions of supramolecular complexes.

  20. Finding finer functions for partially characterized proteins by protein-protein interaction networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins' novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.

  1. Convolutional LSTM Networks for Subcellular Localization of Proteins

    DEFF Research Database (Denmark)

    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...... 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 (0.902) outperforming current state of the art algorithms. We further improve the performance by introducing...

  2. Convolutional LSTM Networks for Subcellular Localization of Proteins

    DEFF Research Database (Denmark)

    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...... 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 (0.902) outperforming current state of the art algorithms. We further improve the performance by introducing...

  3. An analysis pipeline for the inferenceof protein-protein interaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C. [Pacific Northwest National Laboratory (PNNL); Singhal, Mudita [Pacific Northwest National Laboratory (PNNL); Daly, Don S. [Pacific Northwest National Laboratory (PNNL); Gilmore, Jason [Pacific Northwest National Laboratory (PNNL); Cannon, Bill [Pacific Northwest National Laboratory (PNNL); Domico, Kelly [Pacific Northwest National Laboratory (PNNL); White, Amanda M. [Pacific Northwest National Laboratory (PNNL); Auberry, Deanna L [ORNL; Auberry, Kenneth J [ORNL; Hooker, Brian [Pacific Northwest National Laboratory (PNNL); Hurst, Gregory {Greg} B [ORNL; McDermott, Jason [Pacific Northwest National Laboratory (PNNL); McDonald, W Hayes [ORNL; Pelletier, Dale A [ORNL; Schmoyer, Denise D [ORNL; Wiley, Steven [Pacific Northwest National Laboratory (PNNL)

    2009-09-01

    We present an integrated platform that is used for the reconstruction and analysis of protein-protein interaction networks inferred from Mass Spectrometry (MS) bait-prey experiment data. At the heart of this pipeline is the Software Environment for Biological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data. Among the many algorithms available in SEBINI is the Bayesian Estimator of Probabilities of Protein-Protein Associations (BEPro3) algorithm, which is used to infer interaction networks from such MS affinity isolation data. For integration, comparison and analysis of the inferred protein-protein interactions with interaction evidence obtained from multiple public sources, the pipeline connects to the Collective Analysis of Biological Interaction Networks (CABIN) software. Incorporating BEPro3 into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of MS bait-prey experiments.

  4. Advanced path sampling of the kinetic network of small proteins

    NARCIS (Netherlands)

    Du, W.

    2014-01-01

    This thesis is focused on developing advanced path sampling simulation methods to study protein folding and unfolding, and to build kinetic equilibrium networks describing these processes. In Chapter 1 the basic knowledge of protein structure and folding theories were introduced and a brief overview

  5. Properties of Fibrillar Protein Assemblies and their Percolating Networks

    NARCIS (Netherlands)

    Veerman, C.

    2004-01-01

    Properties of Fibrillar Protein Assemblies and their Percolating Networks. PhD thesis, Wageningen University, The Netherlands Keywords: bovine serum albumin, complex fluids, excluded volume, fibrils, gels, innovation, b-lactoglobulin, ovalbumin, percolation, proteins, rheology, rheo-optics, self-ass

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

    Science.gov (United States)

    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.

  7. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    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.

  8. Dynamic rheology of food protein networks

    Science.gov (United States)

    Small amplitude oscillatory shear analyses of samples containing protein are useful for determining the nature of the protein matrix without damaging it. Elastic modulus, viscous modulus, and loss tangent (the ratio of viscous modulus to elastic modulus) give information on the strength of the netw...

  9. Protein-protein interaction networks in the spinocerebellar ataxias

    OpenAIRE

    David C Rubinsztein

    2006-01-01

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

  10. Interrogating the architecture of protein assemblies and protein interaction networks by cross-linking mass spectrometry

    NARCIS (Netherlands)

    Liu, Fan; Heck, Albert J R

    2015-01-01

    Proteins are involved in almost all processes of the living cell. They are organized through extensive networks of interaction, by tightly bound macromolecular assemblies or more transiently via signaling nodes. Therefore, revealing the architecture of protein complexes and protein interaction netwo

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

    CERN Document Server

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-12-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

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

    2010-07-01

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

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

    Science.gov (United States)

    Poirot, Olivier; Timsit, Youri

    2016-05-26

    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.

  16. Topology-free querying of protein interaction networks.

    Science.gov (United States)

    Bruckner, Sharon; Hüffner, Falk; Karp, Richard M; Shamir, Ron; Sharan, Roded

    2010-03-01

    In the network querying problem, one is given a protein complex or pathway of species A and a protein-protein interaction network of species B; the goal is to identify subnetworks of B that are similar to the query in terms of sequence, topology, or both. Existing approaches mostly depend on knowledge of the interaction topology of the query in the network of species A; however, in practice, this topology is often not known. To address this problem, we develop a topology-free querying algorithm, which we call Torque. Given a query, represented as a set of proteins, Torque seeks a matching set of proteins that are sequence-similar to the query proteins and span a connected region of the network, while allowing both insertions and deletions. The algorithm uses alternatively dynamic programming and integer linear programming for the search task. We test Torque with queries from yeast, fly, and human, where we compare it to the QNet topology-based approach, and with queries from less studied species, where only topology-free algorithms apply. Torque detects many more matches than QNet, while giving results that are highly functionally coherent.

  17. Towards a matrix mechanics framework for dynamic protein network.

    Science.gov (United States)

    Bhattacharya, Sanjoy K

    2010-06-01

    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 interactions. Building mathematical foundation for intracellular protein interactions can be achieved in two increments (a) trigger and capture the dynamic molecular changes for a select subset of proteins using several model systems and high throughput time resolved proteomics and, (b) use this information to build the mathematical foundation and computational algorithm for a compartmentalized and dynamic protein interaction network. Such a foundation is expected to provide benefit in at least two spheres: (a) understanding physiology enabling explanation of phenomenon such as incomplete penetrance in genetic disorders and (b) enabling several fold increase in biopharmaceutical production using impure starting materials.

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

    Directory of Open Access Journals (Sweden)

    Pike Andrew D

    2010-06-01

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

  19. Analysis of signaling networks distributed over intracellular compartments based on protein-protein interactions

    OpenAIRE

    2014-01-01

    BackgroundBiological processes are usually distributed over various intracellular compartments. Proteins from diverse cellular compartments are often involved in similar signaling networks. However, the difference in the reaction rates between similar proteins among different compartments is usually quite high. We suggest that the estimation of frequency of intracompartmental as well as intercompartmental protein-protein interactions is an appropriate approach to predict the efficiency of a p...

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

    DEFF Research Database (Denmark)

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

    2005-01-01

    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...... (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...... hundreds of linear motifs yet to be discovered that will give molecular insight into protein networks and greatly illuminate cellular processes....

  1. PathFinder: mining signal transduction pathway segments from protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Yang Jiong

    2007-09-01

    Full Text Available Abstract Background A Signal transduction pathway is the chain of processes by which a cell converts an extracellular signal into a response. In most unicellular organisms, the number of signal transduction pathways influences the number of ways the cell can react and respond to the environment. Discovering signal transduction pathways is an arduous problem, even with the use of systematic genomic, proteomic and metabolomic technologies. These techniques lead to an enormous amount of data and how to interpret and process this data becomes a challenging computational problem. Results In this study we present a new framework for identifying signaling pathways in protein-protein interaction networks. Our goal is to find biologically significant pathway segments in a given interaction network. Currently, protein-protein interaction data has excessive amount of noise, e.g., false positive and false negative interactions. First, we eliminate false positives in the protein-protein interaction network by integrating the network with microarray expression profiles, protein subcellular localization and sequence information. In addition, protein families are used to repair false negative interactions. Then the characteristics of known signal transduction pathways and their functional annotations are extracted in the form of association rules. Conclusion Given a pair of starting and ending proteins, our methodology returns candidate pathway segments between these two proteins with possible missing links (recovered false negatives. In our study, S. cerevisiae (yeast data is used to demonstrate the effectiveness of our method.

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

    CERN Document Server

    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.

  3. Dynamic modularity in protein interaction networks predicts breast cancer outcome

    DEFF Research Database (Denmark)

    Taylor, Ian W; Linding, Rune; Warde-Farley, David

    2009-01-01

    Changes in the biochemical wiring of oncogenic cells drives phenotypic transformations that directly affect disease outcome. Here we examine the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used...... to predict patient outcome. An analysis of hub proteins identified intermodular hub proteins that are co-expressed with their interacting partners in a tissue-restricted manner and intramodular hub proteins that are co-expressed with their interacting partners in all or most tissues. Substantial differences...

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

    Directory of Open Access Journals (Sweden)

    Sandip Chakraborty

    2016-01-01

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

  5. Efficient mapping of ligand migration channel networks in dynamic proteins.

    Science.gov (United States)

    Lin, Tu-Liang; Song, Guang

    2011-08-01

    For many proteins such as myoglobin, the binding site lies in the interior, and there is no obvious route from the exterior to the binding site in the average structure. Although computer simulations for a limited number of proteins have found some transiently open channels, it is not clear if there exist more channels elsewhere or how the channels are regulated. A systematic approach that can map out the whole ligand migration channel network is lacking. Ligand migration in a dynamic protein resembles closely a well-studied problem in robotics, namely, the navigation of a mobile robot in a dynamic environment. In this work, we present a novel robotic motion planning inspired approach that can map the ligand migration channel network in a dynamic protein. The method combines an efficient spatial mapping of protein inner space with a temporal exploration of protein structural heterogeneity, which is represented by a structure ensemble. The spatial mapping of each conformation in the ensemble produces a partial map of protein inner cavities and their inter-connectivity. These maps are then merged to form a super map that contains all the channels that open dynamically. Results on the pathways in myoglobin for gaseous ligands demonstrate the efficiency of our approach in mapping the ligand migration channel networks. The results, obtained in a significantly less amount of time than trajectory-based approaches, are in agreement with previous simulation results. Additionally, the method clearly illustrates how and what conformational changes open or close a channel.

  6. Protein intrinsic disorder and network connectivity. The case of 14-3-3 proteins.

    Directory of Open Access Journals (Sweden)

    Marina eUhart

    2014-02-01

    Full Text Available The understanding of networks is a common goal of an unprecedented array oftraditional disciplines. One of the network properties most influenced by thestructural contents of its nodes is the inter-connectivity. Recent studies in whichstructural information was included into the topological analysis of proteinnetworks revealed that the content of intrinsic disorder in the nodes couldmodulate the network topology, rewire networks and change their inter-connectivity, which is defined by its clustering coefficient. Here, we review therole of intrinsic disorder present in the partners of the highly conserved 14-3-3protein family on its interaction networks. The 14-3-3s are phospho-serine/threonine binding proteins that have strong influence in the regulation ofmetabolism and signal transduction networks. Intrinsic disorder increases theclustering coefficients, namely the inter-connectivity of the nodes within each14-3-3 paralog networks. We also review two new ideas to measure intrinsicdisorder independently of the primary sequence of proteins, a thermodynamicmodel and a method that uses protein structures and their solventenvironment. This new methods could be useful to explain unsolved questionsabout versatility and fixation of intrinsic disorder through evolution. Therelation between the intrinsic disorder and network topologies could be aninteresting model to investigate new implicitness of the graph theory intobiology.

  7. [Statistical characteristics of inhomogeneities of protein and chromation networks].

    Science.gov (United States)

    Gutorov, E I; Gutorov, A E; Kogan, E M

    2005-01-01

    Natural textures (networks) are observed in many cases: the inter-cellular contact sites, endoplasmic reticulum membranes etc. The vast amount of experimental data was analyzed to produce the distribution histograms for the length of the segments in the protein and chromatin networks of different origin. The networks both from the eukaryotic cells and nucleis, as well as from E. coli and viruses are presented. Statistical analysis demonstrated that all experimentally observed histograms fit to the following formula: F(x) = (5(5)[4]) x x(4)x exp(-5x) where x =l/, l- length of the network segment, and is the average length of the segment. In contrast to the Gaussian distribution, the distribution of the segments' lengths is markedly assymetrical. The shape of the distribution does not dependent on the origin of the analyzed network.

  8. Reduction of Protein Networks Models by Passivity Preserving Projection

    Institute of Scientific and Technical Information of China (English)

    Luca Mesin; Flavio Canavero; Lamberto Rondoni

    2013-01-01

    Reduction of complex protein networks models is of great importance.The accuracy of a passivity preserving algorithm (PRIMA) for model order reduction (MOR) is here tested on protein networks,introducing innovative variations of the standard PRIMA method to fit the problem at hand.The reduction method does not require to solve the complete system,resulting in a promising tool for studying very large-scale models for which the full solution cannot be computed.The mathematical structure of the considered kinetic equations is preserved.Keeping constant the reduction factor,the approximation error is lower for larger systems.

  9. Associating genes and protein complexes with disease via network propagation.

    Directory of Open Access Journals (Sweden)

    Oron Vanunu

    2010-01-01

    Full Text Available A fundamental challenge in human health is the identification of disease-causing genes. Recently, several studies have tackled this challenge via a network-based approach, motivated by the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. However, most of these approaches use only local network information in the inference process and are restricted to inferring single gene associations. Here, we provide a global, network-based method for prioritizing disease genes and inferring protein complex associations, which we call PRINCE. The method is based on formulating constraints on the prioritization function that relate to its smoothness over the network and usage of prior information. We exploit this function to predict not only genes but also protein complex associations with a disease of interest. We test our method on gene-disease association data, evaluating both the prioritization achieved and the protein complexes inferred. We show that our method outperforms extant approaches in both tasks. Using data on 1,369 diseases from the OMIM knowledgebase, our method is able (in a cross validation setting to rank the true causal gene first for 34% of the diseases, and infer 139 disease-related complexes that are highly coherent in terms of the function, expression and conservation of their member proteins. Importantly, we apply our method to study three multi-factorial diseases for which some causal genes have been found already: prostate cancer, alzheimer and type 2 diabetes mellitus. PRINCE's predictions for these diseases highly match the known literature, suggesting several novel causal genes and protein complexes for further investigation.

  10. Lists2Networks: Integrated analysis of gene/protein lists

    Directory of Open Access Journals (Sweden)

    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.

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

    KAUST Repository

    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.

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Science.gov (United States)

    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.

  14. Ubc2, an Ortholog of the Yeast Ste50p Adaptor, Possesses a Basidiomycete-Specific Carboxy terminal Extension Essential for Pathogenicity Independent of Pheromone Response.

    Science.gov (United States)

    Proteins involved in the MAP kinase pathway controlling mating, morphogenesis and pathogenicity have been identified previously in the fungus Ustilago maydis. One of these, the Ubc2 adaptor protein, possesses a basidiomycete-specific structure. In addition to containing SAM and RA domains typical of...

  15. Protein complex prediction based on k-connected subgraphs in protein interaction network

    Directory of Open Access Journals (Sweden)

    Habibi Mahnaz

    2010-09-01

    Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

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

    Institute of Scientific and Technical Information of China (English)

    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. The Pch2 AAA+ ATPase promotes phosphorylation of the Hop1 meiotic checkpoint adaptor in response to synaptonemal complex defects.

    Science.gov (United States)

    Herruzo, Esther; Ontoso, David; González-Arranz, Sara; Cavero, Santiago; Lechuga, Ana; San-Segundo, Pedro A

    2016-09-19

    Meiotic cells possess surveillance mechanisms that monitor critical events such as recombination and chromosome synapsis. Meiotic defects resulting from the absence of the synaptonemal complex component Zip1 activate a meiosis-specific checkpoint network resulting in delayed or arrested meiotic progression. Pch2 is an evolutionarily conserved AAA+ ATPase required for the checkpoint-induced meiotic block in the zip1 mutant, where Pch2 is only detectable at the ribosomal DNA array (nucleolus). We describe here that high levels of the Hop1 protein, a checkpoint adaptor that localizes to chromosome axes, suppress the checkpoint defect of a zip1 pch2 mutant restoring Mek1 activity and meiotic cell cycle delay. We demonstrate that the critical role of Pch2 in this synapsis checkpoint is to sustain Mec1-dependent phosphorylation of Hop1 at threonine 318. We also show that the ATPase activity of Pch2 is essential for its checkpoint function and that ATP binding to Pch2 is required for its localization. Previous work has shown that Pch2 negatively regulates Hop1 chromosome abundance during unchallenged meiosis. Based on our results, we propose that, under checkpoint-inducing conditions, Pch2 also possesses a positive action on Hop1 promoting its phosphorylation and its proper distribution on unsynapsed chromosome axes.

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

    Directory of Open Access Journals (Sweden)

    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.

  19. Proteasome inhibition, the pursuit of new cancer therapeutics, and the adaptor molecule p130Cas

    Directory of Open Access Journals (Sweden)

    Anderson Kenneth C

    2011-10-01

    Full Text Available Abstract Current interest in proteasome inhibitors for cancer therapy has stimulated considerable research efforts to identify the molecular pathway to their cytotoxicity with a view to identifying the mechanisms of sensitivity and resistance as well as informing the development of new drugs. Zhao and Vuori describe this month in BMC Biology experiments indicating a novel role of the adaptor protein p130Cas in sensitivity to apoptosis induced not only by proteasome inhibitors but also by the unrelated drug doxorubicin. See research article: http:// http://www.biomedcentral.com/1741-7007/9/73

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

    Directory of Open Access Journals (Sweden)

    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

  1. Identifying functional modules in protein-protein interaction networks: An integrated exact approach

    NARCIS (Netherlands)

    Dittrich, M.; Klau, G.W.; Rosenwald, A.; Dandekar, T.; et al, not CWI

    2008-01-01

    Motivation: With the exponential growth of expression and protein-protein interaction (PPI) data, the frontier of research in system biology shifts more and more to the integrated analysis of these large datasets. Of particular interest is the identification of functional modules in PPI networks, sh

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

    Science.gov (United States)

    Poirot, Olivier; Timsit, Youri

    2016-05-01

    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.

  3. A neural network dynamics that resembles protein evolution

    Science.gov (United States)

    Ferrán, Edgardo A.; Ferrara, Pascual

    1992-06-01

    We use neutral networks to classify proteins according to their sequence similarities. A network composed by 7 × 7 neurons, was trained with the Kohonen unsupervised learning algorithm using, as inputs, matrix patterns derived from the bipeptide composition of cytochrome c proteins belonging to 76 different species. As a result of the training, the network self-organized the activation of its neurons into topologically ordered maps, wherein phylogenetically related sequences were positioned close to each other. The evolution of the topological map during learning, in a representative computational experiment, roughly resembles the way in which one species evolves into several others. For instance, sequences corresponding to vertebrates, initially grouped together into one neuron, were placed in a contiguous zone of the final neural map, with sequences of fishes, amphibia, reptiles, birds and mammals associated to different neurons. Some apparent wrong classifications are due to the fact that some proteins have a greater degree of sequence identity than the one expected by phylogenetics. In the final neural map, each synaptic vector may be considered as the pattern corresponding to the ancestor of all the proteins that are attached to that neuron. Although it may be also tempting to link real time with learning epochs and to use this relationship to calibrate the molecular evolutionary clock, this is not correct because the evolutionary time schedule obtained with the neural network depends highly on the discrete way in which the winner neighborhood is decreased during learning.

  4. Simple Protein Complex Purification and Identification Method Suitable for High- throughput Mapping of Protein Interaction Networks

    Energy Technology Data Exchange (ETDEWEB)

    Markillie, Lye Meng; Lin, Chiann Tso; Adkins, Joshua N.; Auberry, Deanna L.; Hill, Eric A.; Hooker, Brian S.; Moore, Priscilla A.; Moore, Ronald J.; Shi, Liang; Wiley, H. S.; Kery, Vladimir

    2005-04-11

    Most of the current methods for purification and identification of protein complexes use endogenous expression of affinity tagged bait, tandem affinity tag purification of protein complexes followed by specific elution of complexes from beads, gel separation, in-gel digestion and mass spectrometric analysis of protein interactors. We propose a single affinity tag in vitro pulldown assay with denaturing elution, trypsin digestion in organic solvent and LC ESI MS/MS protein identification using SEQUEST analysis. Our method is simple, easy to scale up and automate thus suitable for high throughput mapping of protein interaction networks and functional proteomics.

  5. Viral proteins that bridge unconnected proteins and components in the human PPI network.

    Science.gov (United States)

    Rachita, H R; Nagarajaram, H A

    2014-07-29

    Viruses, despite having small genomes and few proteins, make an array of interactions with host proteins as they solely depend on host machinery for their replication and reproduction. Hence, analysis of the Human-Virus Protein-Protein Interaction Network (Hu-Vir PPI network) helps us to gain certain insights into the molecular mechanisms underlying the hijacking of host cell machinery by viruses for their perpetuation. Here we report an analysis of the Human-Virus Bridged PPI Networks that has led us to identify viral articulation points (VAPs) which connect unconnected components of the Human-PPI (Hu-PPI) network. VAPs cross-link peripheral nodes to the giant component of the Hu-PPI network. VAPs interact with a number of relatively lower topologically central human proteins and are conserved among related viruses. The linked nodes comprise of those that are mostly expressed during viral infection, as well as those that are found exclusively in some metabolic pathways, indicating that the novel viral mediation of certain human protein-protein interactions may form the basis for virus-specific tuning of the host machinery. The functional importance of VAPs and their interaction partners in virus replication make them potential drug targets against viral infection. Our investigations also led to the discovery of an example of a Human Endogenous Retrovirus (HERV) encoded protein, syncytin, as an Articulation Point (AP) in the Hu-PPI network, suggesting that VAPs may be retained in a genome if they result in any beneficial function in the host.

  6. AtPIN: Arabidopsis thaliana Protein Interaction Network

    Directory of Open Access Journals (Sweden)

    Silva-Filho Marcio C

    2009-12-01

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

  7. Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

    Science.gov (United States)

    Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

    2008-10-01

    Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

  8. Conventional and novel Gγ protein families constitute the heterotrimeric G-protein signaling network in soybean.

    Directory of Open Access Journals (Sweden)

    Swarup Roy Choudhury

    Full Text Available Heterotrimeric G-proteins comprised of Gα, Gβ and Gγ proteins are important signal transducers in all eukaryotes. The Gγ protein of the G-protein heterotrimer is crucial for its proper targeting at the plasma membrane and correct functioning. Gγ proteins are significantly smaller and more diverse than the Gα and Gβ proteins. In model plants Arabidopsis and rice that have a single Gα and Gβ protein, the presence of two canonical Gγ proteins provide some diversity to the possible heterotrimeric combinations. Our recent analysis of the latest version of the soybean genome has identified ten Gγ proteins which belong to three distinct families based on their C-termini. We amplified the full length cDNAs, analyzed their detailed expression profile by quantitative PCR, assessed their localization and performed yeast-based interaction analysis to evaluate interaction specificity with different Gβ proteins. Our results show that ten Gγ genes are retained in the soybean genome and have interesting expression profiles across different developmental stages. Six of the newly identified proteins belong to two plant-specific Gγ protein families. Yeast-based interaction analyses predict some degree of interaction specificity between different Gβ and Gγ proteins. This research thus identifies a highly diverse G-protein network from a plant species. Homologs of these novel proteins have been previously identified as QTLs for grain size and yield in rice.

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

    Lifescience Database Archive (English)

    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

  10. Locus heterogeneity disease genes encode proteins with high interconnectivity in the human protein interaction network.

    Science.gov (United States)

    Keith, Benjamin P; Robertson, David L; Hentges, Kathryn E

    2014-01-01

    Mutations in genes potentially lead to a number of genetic diseases with differing severity. These disease genes have been the focus of research in recent years showing that the disease gene population as a whole is not homogeneous, and can be categorized according to their interactions. Locus heterogeneity describes a single disorder caused by mutations in different genes each acting individually to cause the same disease. Using datasets of experimentally derived human disease genes and protein interactions, we created a protein interaction network to investigate the relationships between the products of genes associated with a disease displaying locus heterogeneity, and use network parameters to suggest properties that distinguish these disease genes from the overall disease gene population. Through the manual curation of known causative genes of 100 diseases displaying locus heterogeneity and 397 single-gene Mendelian disorders, we use network parameters to show that our locus heterogeneity network displays distinct properties from the global disease network and a Mendelian network. Using the global human proteome, through random simulation of the network we show that heterogeneous genes display significant interconnectivity. Further topological analysis of this network revealed clustering of locus heterogeneity genes that cause identical disorders, indicating that these disease genes are involved in similar biological processes. We then use this information to suggest additional genes that may contribute to diseases with locus heterogeneity.

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

    Directory of Open Access Journals (Sweden)

    Kwoh Chee-Keong

    2010-02-01

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

  12. Differential Protein Network Analysis of the Immune Cell Lineage

    Directory of Open Access Journals (Sweden)

    Trevor Clancy

    2014-01-01

    Full Text Available Recently, the Immunological Genome Project (ImmGen completed the first phase of the goal to understand the molecular circuitry underlying the immune cell lineage in mice. That milestone resulted in the creation of the most comprehensive collection of gene expression profiles in the immune cell lineage in any model organism of human disease. There is now a requisite to examine this resource using bioinformatics integration with other molecular information, with the aim of gaining deeper insights into the underlying processes that characterize this immune cell lineage. We present here a bioinformatics approach to study differential protein interaction mechanisms across the entire immune cell lineage, achieved using affinity propagation applied to a protein interaction network similarity matrix. We demonstrate that the integration of protein interaction networks with the most comprehensive database of gene expression profiles of the immune cells can be used to generate hypotheses into the underlying mechanisms governing the differentiation and the differential functional activity across the immune cell lineage. This approach may not only serve as a hypothesis engine to derive understanding of differentiation and mechanisms across the immune cell lineage, but also help identify possible immune lineage specific and common lineage mechanism in the cells protein networks.

  13. Anti-adaptors use distinct modes of binding to inhibit the RssB-dependent turnover of RpoS (σS by ClpXP.

    Directory of Open Access Journals (Sweden)

    Dimce eMicevski

    2015-04-01

    Full Text Available In Escherichia coli, σS is the master regulator of the general stress response. The level of σS changes in response to multiple stress conditions and it is regulated at many levels including protein turnover. In the absence of stress, σS is rapidly degraded by the AAA+ protease, ClpXP in a regulated manner that depends on the adaptor protein RssB. This two-component response regulator mediates the recognition of σS and its delivery to ClpXP. The turnover of σS however, can be inhibited in a stress specific manner, by one of three anti-adaptor proteins. Each anti-adaptor binds to RssB and inhibits its activity, but how this is achieved is not fully understood at a molecular level. Here we describe details of the interaction between each anti-adaptor and RssB that leads to the stabilization of σS. By defining the domains of RssB using partial proteolysis we demonstrate that each anti-adaptor uses a distinct mode of binding to inhibit RssB activity. IraD docks specifically to the N-terminal domain of RssB, IraP interacts primarily with the C-terminal domain, while IraM interacts with both domains. Despite these differences in binding, we propose that docking of each anti-adaptor induces a conformational change in RssB, which resembles the inactive dimer of RssB. This dimer-like state of RssB not only prevents substrate binding but also triggers substrate release from a pre-bound complex.

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

    Directory of Open Access Journals (Sweden)

    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.

  15. UIF, a New mRNA export adaptor that works together with REF/ALY, requires FACT for recruitment to mRNA.

    Science.gov (United States)

    Hautbergue, Guillaume M; Hung, Ming-Lung; Walsh, Matthew J; Snijders, Ambrosius P L; Chang, Chung-Te; Jones, Rachel; Ponting, Chris P; Dickman, Mark J; Wilson, Stuart A

    2009-12-01

    Messenger RNA (mRNA) export adaptors play an important role in the transport of mRNA from the nucleus to the cytoplasm. They couple early mRNA processing events such as 5' capping and 3' end formation with loading of the TAP/NXF1 export receptor onto mRNA. The canonical adaptor REF/ALY/Yra1 is recruited to mRNA via UAP56 and subsequently delivers the mRNA to NXF1 [1]. Knockdown of UAP56 [2, 3] and NXF1 [4-7] in higher eukaryotes efficiently blocks mRNA export, whereas knockdown of REF only causes a modest reduction, suggesting the existence of additional adaptors [8-10]. Here we identify a new UAP56-interacting factor, UIF, which functions as an export adaptor, binding NXF1 and delivering mRNA to the nuclear pore. REF and UIF are simultaneously found on the same mRNA molecules, and both proteins are required for efficient export of mRNA. We show that the histone chaperone FACT specifically binds UIF, but not REF, via the SSRP1 subunit, and this interaction is required for recruitment of UIF to mRNA. Together the results indicate that REF and UIF represent key human adaptors for the export of cellular mRNAs via the UAP56-NXF1 pathway.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

    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.

  18. Cell cycle-dependent adaptor complex for ClpXP-mediated proteolysis directly integrates phosphorylation and second messenger signals.

    Science.gov (United States)

    Smith, Stephen C; Joshi, Kamal K; Zik, Justin J; Trinh, Katherine; Kamajaya, Aron; Chien, Peter; Ryan, Kathleen R

    2014-09-30

    The cell-division cycle of Caulobacter crescentus depends on periodic activation and deactivation of the essential response regulator CtrA. Although CtrA is critical for transcription during some parts of the cell cycle, its activity must be eliminated before chromosome replication because CtrA also blocks the initiation of DNA replication. CtrA activity is down-regulated both by dephosphorylation and by proteolysis, mediated by the ubiquitous ATP-dependent protease ClpXP. Here we demonstrate that proteins needed for rapid CtrA proteolysis in vivo form a phosphorylation-dependent and cyclic diguanylate (cdG)-dependent adaptor complex that accelerates CtrA degradation in vitro by ClpXP. The adaptor complex includes CpdR, a single-domain response regulator; PopA, a cdG-binding protein; and RcdA, a protein whose activity cannot be predicted. When CpdR is unphosphorylated and when PopA is bound to cdG, they work together with RcdA in an all-or-none manner to reduce the Km of CtrA proteolysis 10-fold. We further identified a set of amino acids in the receiver domain of CtrA that modulate its adaptor-mediated degradation in vitro and in vivo. Complex formation between PopA and CtrA depends on these amino acids, which reside on alpha-helix 1 of the CtrA receiver domain, and on cdG binding by PopA. These results reveal that each accessory factor plays an essential biochemical role in the regulated proteolysis of CtrA and demonstrate, to our knowledge, the first example of a multiprotein, cdG-dependent proteolytic adaptor.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  20. Evolution versus "intelligent design": comparing the topology of protein-protein interaction networks to the Internet.

    Science.gov (United States)

    Yang, Q; Siganos, G; Faloutsos, M; Lonardi, S

    2006-01-01

    Recent research efforts have made available genome-wide, high-throughput protein-protein interaction (PPI) maps for several model organisms. This has enabled the systematic analysis of PPI networks, which has become one of the primary challenges for the system biology community. In this study, we attempt to understand better the topological structure of PPI networks by comparing them against man-made communication networks, and more specifically, the Internet. Our comparative study is based on a comprehensive set of graph metrics. Our results exhibit an interesting dichotomy. On the one hand, both networks share several macroscopic properties such as scale-free and small-world properties. On the other hand, the two networks exhibit significant topological differences, such as the cliqueishness of the highest degree nodes. We attribute these differences to the distinct design principles and constraints that both networks are assumed to satisfy. We speculate that the evolutionary constraints that favor the survivability and diversification are behind the building process of PPI networks, whereas the leading force in shaping the Internet topology is a decentralized optimization process geared towards efficient node communication.

  1. Neural network definitions of highly predictable protein secondary structure classes

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A. [Los Alamos National Lab., NM (United States)]|[Santa Fe Inst., NM (United States); Steeg, E. [Toronto Univ., ON (Canada). Dept. of Computer Science; Farber, R. [Los Alamos National Lab., NM (United States)

    1994-02-01

    We use two co-evolving neural networks to determine new classes of protein secondary structure which are significantly more predictable from local amino sequence than the conventional secondary structure classification. Accurate prediction of the conventional secondary structure classes: alpha helix, beta strand, and coil, from primary sequence has long been an important problem in computational molecular biology. Neural networks have been a popular method to attempt to predict these conventional secondary structure classes. Accuracy has been disappointingly low. The algorithm presented here uses neural networks to similtaneously examine both sequence and structure data, and to evolve new classes of secondary structure that can be predicted from sequence with significantly higher accuracy than the conventional classes. These new classes have both similarities to, and differences with the conventional alpha helix, beta strand and coil.

  2. FunPred-1: protein function prediction from a protein interaction network using neighborhood analysis.

    Science.gov (United States)

    Saha, Sovan; Chatterjee, Piyali; Basu, Subhadip; Kundu, Mahantapas; Nasipuri, Mita

    2014-12-01

    Proteins are responsible for all biological activities in living organisms. Thanks to genome sequencing projects, large amounts of DNA and protein sequence data are now available, but the biological functions of many proteins are still not annotated in most cases. The unknown function of such non-annotated proteins may be inferred or deduced from their neighbors in a protein interaction network. In this paper, we propose two new methods to predict protein functions based on network neighborhood properties. FunPred 1.1 uses a combination of three simple-yet-effective scoring techniques: the neighborhood ratio, the protein path connectivity and the relative functional similarity. FunPred 1.2 applies a heuristic approach using the edge clustering coefficient to reduce the search space by identifying densely connected neighborhood regions. The overall accuracy achieved in FunPred 1.2 over 8 functional groups involving hetero-interactions in 650 yeast proteins is around 87%, which is higher than the accuracy with FunPred 1.1. It is also higher than the accuracy of many of the state-of-the-art protein function prediction methods described in the literature. The test datasets and the complete source code of the developed software are now freely available at http://code.google.com/p/cmaterbioinfo/ .

  3. Weighted protein interaction network analysis of frontotemporal dementia\\ud

    OpenAIRE

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

    2016-01-01

    The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein−protein\\ud interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological...

  4. Comparison of protein interaction networks reveals species conservation and divergence

    Directory of Open Access Journals (Sweden)

    Teng Maikun

    2006-10-01

    Full Text Available Abstract Background Recent progresses in high-throughput proteomics have provided us with a first chance to characterize protein interaction networks (PINs, but also raised new challenges in interpreting the accumulating data. Results Motivated by the need of analyzing and interpreting the fast-growing data in the field of proteomics, we propose a comparative strategy to carry out global analysis of PINs. We compare two PINs by combining interaction topology and sequence similarity to identify conserved network substructures (CoNSs. Using this approach we perform twenty-one pairwise comparisons among the seven recently available PINs of E.coli, H.pylori, S.cerevisiae, C.elegans, D.melanogaster, M.musculus and H.sapiens. In spite of the incompleteness of data, PIN comparison discloses species conservation at the network level and the identified CoNSs are also functionally conserved and involve in basic cellular functions. We investigate the yeast CoNSs and find that many of them correspond to known complexes. We also find that different species harbor many conserved interaction regions that are topologically identical and these regions can constitute larger interaction regions that are topologically different but similar in framework. Based on the species-to-species difference in CoNSs, we infer potential species divergence. It seems that different species organize orthologs in similar but not necessarily the same topology to achieve similar or the same function. This attributes much to duplication and divergence of genes and their associated interactions. Finally, as the application of CoNSs, we predict 101 protein-protein interactions (PPIs, annotate 339 new protein functions and deduce 170 pairs of orthologs. Conclusion Our result demonstrates that the cross-species comparison strategy we adopt is powerful for the exploration of biological problems from the perspective of networks.

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

    OpenAIRE

    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 sta...

  6. Improving Protein Fold Recognition by Deep Learning Networks

    Science.gov (United States)

    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.

  7. Amyloid Beta-Protein and Neural Network Dysfunction

    Directory of Open Access Journals (Sweden)

    Fernando Peña-Ortega

    2013-01-01

    Full Text Available Understanding the neural mechanisms underlying brain dysfunction induced by amyloid beta-protein (Aβ represents one of the major challenges for Alzheimer’s disease (AD research. The most evident symptom of AD is a severe decline in cognition. Cognitive processes, as any other brain function, arise from the activity of specific cell assemblies of interconnected neurons that generate neural network dynamics based on their intrinsic and synaptic properties. Thus, the origin of Aβ-induced cognitive dysfunction, and possibly AD-related cognitive decline, must be found in specific alterations in properties of these cells and their consequences in neural network dynamics. The well-known relationship between AD and alterations in the activity of several neural networks is reflected in the slowing of the electroencephalographic (EEG activity. Some features of the EEG slowing observed in AD, such as the diminished generation of different network oscillations, can be induced in vivo and in vitro upon Aβ application or by Aβ overproduction in transgenic models. This experimental approach offers the possibility to study the mechanisms involved in cognitive dysfunction produced by Aβ. This type of research may yield not only basic knowledge of neural network dysfunction associated with AD, but also novel options to treat this modern epidemic.

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Science.gov (United States)

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

    2014-05-01

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

  10. An automated approach to network features of protein structure ensembles.

    Science.gov (United States)

    Bhattacharyya, Moitrayee; Bhat, Chanda R; Vishveshwara, Saraswathi

    2013-10-01

    Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of β2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.

  11. Prediction and characterization of protein-protein interaction networks in swine

    Directory of Open Access Journals (Sweden)

    Wang Fen

    2012-01-01

    Full Text Available Abstract Background Studying the large-scale protein-protein interaction (PPI network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes. Results We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively. Conclusion The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/.

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

    Science.gov (United States)

    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.

  13. Validation of protein models by a neural network approach

    Directory of Open Access Journals (Sweden)

    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.

  14. Deciphering primordial cyanobacterial genome functions from protein network analysis.

    Science.gov (United States)

    Harel, Arye; Karkar, Slim; Cheng, Shu; Falkowski, Paul G; Bhattacharya, Debashish

    2015-03-02

    The Great Oxidation Event (GOE) ∼2.4 billion years ago resulted from the accumulation of oxygen by the ancestors of cyanobacteria [1-3]. Cyanobacteria continue to play a significant role in primary production [4] and in regulating the global marine and limnic nitrogen cycles [5, 6]. Relatively little is known, however, about the evolutionary history and gene content of primordial cyanobacteria [7, 8]. To address these issues, we used protein similarity networks [9], containing proteomes from 48 cyanobacteria as the test group, and reference proteomes from 84 microbes representing four distinct metabolic groups from most reducing to most oxidizing: methanogens, obligate anaerobes (nonmethanogenic), facultative aerobes, and obligate aerobes. These four metabolic groups represent extant bioinformatic proxies for ancient redox chemistries, extending from an anoxic origin through the GOE and ultimately to obligate aerobes [10-13]. Analysis of the network metric degree showed a strong relationship between cyanobacteria and obligate anaerobes, from which cyanobacteria presumably arose, for core functions that include translation, photosynthesis, energy conservation, and environmental interactions. These data were used to reconstruct primordial functions in cyanobacteria that included nine gene families involved in photosynthesis, hydrogenases, and proteins involved in defense from environmental stress. The presence of 60% of these genes in both reaction center I (RC-I) and RC-II-type bacteria may be explained by selective loss of either RC in the evolutionary history of some photosynthetic lineages. Finally, the network reveals that cyanobacteria occupy a unique position among prokaryotes as a hub between anaerobes and obligate aerobes.

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

    Directory of Open Access Journals (Sweden)

    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.

  16. The Hypoxic Regulator of Sterol Synthesis Nro1 Is a Nuclear Import Adaptor

    Energy Technology Data Exchange (ETDEWEB)

    T Yeh; C Lee; L Amzel; P Espenshade; M Bianchet

    2011-12-31

    Fission yeast protein Sre1, the homolog of the mammalian sterol regulatory element-binding protein (SREBP), is a hypoxic transcription factor required for sterol homeostasis and low-oxygen growth. Nro1 regulates the stability of the N-terminal transcription factor domain of Sre1 (Sre1N) by inhibiting the action of the prolyl 4-hydroxylase-like Ofd1 in an oxygen-dependent manner. The crystal structure of Nro1 determined at 2.2 {angstrom} resolution shows an all-{alpha}-helical fold that can be divided into two domains: a small N-terminal domain, and a larger C-terminal HEAT-repeat domain. Follow-up studies showed that Nro1 defines a new class of nuclear import adaptor that functions both in Ofd1 nuclear localization and in the oxygen-dependent inhibition of Ofd1 to control the hypoxic response.

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

    Science.gov (United States)

    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. Category theoretic analysis of hierarchical protein materials and social networks

    CERN Document Server

    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...

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

    Science.gov (United States)

    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 proteins related to cytoplasmic male sterility (CMS), 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. Gene, protein and network of male sterility in rice

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    David I Spivak

    Full Text Available Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe 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 olog. We consider simple cases of beta-helical and amyloid-like protein filaments 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 for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine.

  2. Direct and Propagated Effects of Small Molecules on Protein-Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Laura C Cesa

    2015-08-01

    Full Text Available Networks of protein-protein interactions (PPIs link all aspects of cellular biology. Dysfunction in the assembly or dynamics of PPI networks is a hallmark of human disease, and as such, there is growing interest in the discovery of small molecules that either promote or inhibit PPIs. Protein-protein interactions were once considered undruggable because of their relatively large buried surface areas and difficult topologies. Despite these challenges, recent advances in chemical screening methodologies, combined with improvements in structural and computational biology have made some of these targets more tractable. In this review, we highlight developments that have opened the door to potent chemical modulators. We focus on how allostery is being used to produce surprisingly robust changes in PPIs, even for the most challenging targets. We also discuss how interfering with one PPI can propagate changes through the broader web of interactions. Through this analysis, it is becoming clear that a combination of direct and propagated effects on PPI networks is ultimately how small molecules re-shape biology.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    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 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...

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

    Science.gov (United States)

    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.

  5. A New Method for Identifying Essential Proteins Based on Network Topology Properties and Protein Complexes

    Science.gov (United States)

    Qin, Chao; Sun, Yongqi; Dong, Yadong

    2016-01-01

    Essential proteins are indispensable to the viability and reproduction of an organism. The identification of essential proteins is necessary not only for understanding the molecular mechanisms of cellular life but also for disease diagnosis, medical treatments and drug design. Many computational methods have been proposed for discovering essential proteins, but the precision of the prediction of essential proteins remains to be improved. In this paper, we propose a new method, LBCC, which is based on the combination of local density, betweenness centrality (BC) and in-degree centrality of complex (IDC). First, we introduce the common centrality measures; second, we propose the densities Den1(v) and Den2(v) of a node v to describe its local properties in the network; and finally, the combined strategy of Den1, Den2, BC and IDC is developed to improve the prediction precision. The experimental results demonstrate that LBCC outperforms traditional topological measures for predicting essential proteins, including degree centrality (DC), BC, subgraph centrality (SC), eigenvector centrality (EC), network centrality (NC), and the local average connectivity-based method (LAC). LBCC also improves the prediction precision by approximately 10 percent on the YMIPS and YMBD datasets compared to the most recently developed method, LIDC. PMID:27529423

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

    Directory of Open Access Journals (Sweden)

    Thomas Wallach

    2013-03-01

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

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

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    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.

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

    Science.gov (United States)

    Cui, Di; Ou, Shuching; Patel, Sandeep

    2014-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Sylvie Lalonde

    2010-09-01

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

  10. Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions

    DEFF Research Database (Denmark)

    Di Roberto, Raphaël B; Chang, Belinda; Trusina, Ala;

    2016-01-01

    All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae...

  11. A Topology Potential-Based Method for Identifying Essential Proteins from PPI Networks.

    Science.gov (United States)

    Li, Min; Lu, Yu; Wang, Jianxin; Wu, Fang-Xiang; Pan, Yi

    2015-01-01

    Essential proteins are indispensable for cellular life. It is of great significance to identify essential proteins that can help us understand the minimal requirements for cellular life and is also very important for drug design. However, identification of essential proteins based on experimental approaches are typically time-consuming and expensive. With the development of high-throughput technology in the post-genomic era, more and more protein-protein interaction data can be obtained, which make it possible to study essential proteins from the network level. There have been a series of computational approaches proposed for predicting essential proteins based on network topologies. Most of these topology based essential protein discovery methods were to use network centralities. In this paper, we investigate the essential proteins' topological characters from a completely new perspective. To our knowledge it is the first time that topology potential is used to identify essential proteins from a protein-protein interaction (PPI) network. The basic idea is that each protein in the network can be viewed as a material particle which creates a potential field around itself and the interaction of all proteins forms a topological field over the network. By defining and computing the value of each protein's topology potential, we can obtain a more precise ranking which reflects the importance of proteins from the PPI network. The experimental results show that topology potential-based methods TP and TP-NC outperform traditional topology measures: degree centrality (DC), betweenness centrality (BC), closeness centrality (CC), subgraph centrality (SC), eigenvector centrality (EC), information centrality (IC), and network centrality (NC) for predicting essential proteins. In addition, these centrality measures are improved on their performance for identifying essential proteins in biological network when controlled by topology potential.

  12. Adaptor-tagged competitive PCR: a novel method for measuring relative gene expression.

    OpenAIRE

    Kato, K.

    1997-01-01

    A simple and reliable PCR-based method to quantitate gene expression is described. Following the digestion of double-stranded cDNA by a restriction enzyme, an adaptor is ligated to a cDNA from a first RNA sample, and another adaptor to a second RNA sample. The two adaptors share a common sequence at the outer region, but differ in size. Equal amounts of the ligated samples are mixed, and amplified by an adaptor-primer and a primer specific to the gene of interest. Products derived from the tw...

  13. Analysis of membrane proteins in metagenomics: networks of correlated environmental features and protein families.

    Science.gov (United States)

    Patel, Prianka V; Gianoulis, Tara A; Bjornson, Robert D; Yip, Kevin Y; Engelman, Donald M; Gerstein, Mark B

    2010-07-01

    Recent metagenomics studies have begun to sample the genomic diversity among disparate habitats and relate this variation to features of the environment. Membrane proteins are an intuitive, but thus far overlooked, choice in this type of analysis as they directly interact with the environment, receiving signals from the outside and transporting nutrients. Using global ocean sampling (GOS) data, we found nearly approximately 900,000 membrane proteins in large-scale metagenomic sequence, approximately a fifth of which are completely novel, suggesting a large space of hitherto unexplored protein diversity. Using GPS coordinates for the GOS sites, we extracted additional environmental features via interpolation from the World Ocean Database, the National Center for Ecological Analysis and Synthesis, and empirical models of dust occurrence. This allowed us to study membrane protein variation in terms of natural features, such as phosphate and nitrate concentrations, and also in terms of human impacts, such as pollution and climate change. We show that there is widespread variation in membrane protein content across marine sites, which is correlated with changes in both oceanographic variables and human factors. Furthermore, using these data, we developed an approach, protein families and environment features network (PEN), to quantify and visualize the correlations. PEN identifies small groups of covarying environmental features and membrane protein families, which we call "bimodules." Using this approach, we find that the affinity of phosphate transporters is related to the concentration of phosphate and that the occurrence of iron transporters is connected to the amount of shipping, pollution, and iron-containing dust.

  14. Release behavior of non-network proteins and its relationship to the structure of heat-induced soy protein gels.

    Science.gov (United States)

    Wu, Chao; Hua, Yufei; Chen, Yeming; Kong, Xiangzhen; Zhang, Caimeng

    2015-04-29

    Heat-induced soy protein gels were prepared by heating protein solutions at 12%, 15% ,or 18% for 0.5, 1.0, or 2.0 h. The release of non-network proteins from gel slices was conducted in 10 mM pH 7.0 sodium phosphate buffer. SDS-PAGE and diagonal electrophoresis demonstrated that the released proteins consisted of undenatured AB subunits and denatured proteins including monomers of A polypeptides, disulfide bond linked dimers, trimers, and polymers of A polypeptides, and an unidentified 15 kDa protein. SEC-HPLC analysis of non-network proteins revealed three major protein peaks, with molecular weights of approximately 253.9, 44.8, and 9.7 kDa. The experimental data showed that the time-dependent release of the three fractions from soy protein gels fit Fick's second law. An increasing protein concentration or heating time resulted in a decrease in diffusion coefficients of non-network proteins. A power law expression was used to describe the relationship between non-network protein diffusion coefficient and molecular weight, for which the exponent (α) shifted to higher value with an increase in protein concentration or heating time, indicating that a more compact gel structure was formed.

  15. In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein-protein interaction networks

    DEFF Research Database (Denmark)

    Folador, Edson Luiz; de Carvalho, Paulo Vinícius Sanches Daltro; Silva, Wanderson Marques;

    2016-01-01

    and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis. RESULTS: Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts...

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

    Energy Technology Data Exchange (ETDEWEB)

    Beers, Eric [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Brunner, Amy [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Helm, Richard [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Dickerman, Allan [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

    2015-07-31

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

  17. Protein-protein interaction network and subcellular localization of the Arabidopsis thaliana ESCRT machinery

    Directory of Open Access Journals (Sweden)

    Lynn eRichardson

    2011-06-01

    Full Text Available The Endosomal Sorting Complex Required for Transport (ESCRT consists of several multi-protein subcomplexes which assemble sequentially at the endosomal surface and function in multivesicular body (MVB biogenesis. While ESCRT has been relatively well characterized in yeasts and mammals, comparably little is known about ESCRT in plants. Here we explored the yeast two-hybrid protein interaction network and subcellular localization of the Arabidopsis thaliana ESCRT machinery. We show that Arabidopsis ESCRT interactome possess a number of protein-protein interactions that are either conserved in yeasts and mammals or distinct to plants. We show also that most of the Arabidopsis ESCRT proteins examined at least partially localize to MVBs in plant cells when ectopically expressed on their own or co-expressed with other interacting ESCRT proteins, and some also induce abnormal MVB phenotypes, consistent with their proposed functional roles in MVB biogenesis. Overall, our results help define the plant ESCRT machinery by highlighting both conserved and unique features when compared to ESCRT in other evolutionarily diverse organisms, providing a foundation for further exploration of ESCRT in plants.

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

    Directory of Open Access Journals (Sweden)

    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. Construction of a cancer-perturbed protein-protein interaction network for discovery of apoptosis drug targets

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2008-06-01

    Full Text Available Abstract Background Cancer is caused by genetic abnormalities, such as mutations of oncogenes or tumor suppressor genes, which alter downstream signal transduction pathways and protein-protein interactions. Comparisons of the interactions of proteins in cancerous and normal cells can shed light on the mechanisms of carcinogenesis. Results We constructed initial networks of protein-protein interactions involved in the apoptosis of cancerous and normal cells by use of two human yeast two-hybrid data sets and four online databases. Next, we applied a nonlinear stochastic model, maximum likelihood parameter estimation, and Akaike Information Criteria (AIC to eliminate false-positive protein-protein interactions in our initial protein interaction networks by use of microarray data. Comparisons of the networks of apoptosis in HeLa (human cervical carcinoma cells and in normal primary lung fibroblasts provided insight into the mechanism of apoptosis and allowed identification of potential drug targets. The potential targets include BCL2, caspase-3 and TP53. Our comparison of cancerous and normal cells also allowed derivation of several party hubs and date hubs in the human protein-protein interaction networks involved in caspase activation. Conclusion Our method allows identification of cancer-perturbed protein-protein interactions involved in apoptosis and identification of potential molecular targets for development of anti-cancer drugs.

  20. MyProteinNet: build up-to-date protein interaction networks for organisms, tissues and user-defined contexts.

    Science.gov (United States)

    Basha, Omer; Flom, Dvir; Barshir, Ruth; Smoly, Ilan; Tirman, Shoval; Yeger-Lotem, Esti

    2015-07-01

    The identification of the molecular pathways active in specific contexts, such as disease states or drug responses, often requires an extensive view of the potential interactions between a subset of proteins. This view is not easily obtained: it requires the integration of context-specific protein list or expression data with up-to-date data of protein interactions that are typically spread across multiple databases. The MyProteinNet web server allows users to easily create such context-sensitive protein interaction networks. Users can automatically gather and consolidate data from up to 11 different databases to create a generic protein interaction network (interactome). They can score the interactions based on reliability and filter them by user-defined contexts including molecular expression and protein annotation. The output of MyProteinNet includes the generic and filtered interactome files, together with a summary of their network attributes. MyProteinNet is particularly geared toward building human tissue interactomes, by maintaining tissue expression profiles from multiple resources. The ability of MyProteinNet to facilitate the construction of up-to-date, context-specific interactomes and its applicability to 11 different organisms and to tens of human tissues, make it a powerful tool in meaningful analysis of protein networks. MyProteinNet is available at http://netbio.bgu.ac.il/myproteinnet.

  1. Topological robustness analysis of protein interaction networks reveals key targets for overcoming chemotherapy resistance in glioma

    OpenAIRE

    Hátylas Azevedo; Carlos Alberto Moreira-Filho

    2015-01-01

    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 fu...

  2. The protein interaction network of a taxis signal transduction system in a Halophilic Archaeon

    Directory of Open Access Journals (Sweden)

    Schlesner Matthias

    2012-11-01

    Full Text Available Abstract Background The taxis signaling system of the extreme halophilic archaeon Halobacterium (Hbt. salinarum differs in several aspects from its model bacterial counterparts Escherichia coli and Bacillus subtilis. We studied the protein interactions in the Hbt. salinarum taxis signaling system to gain an understanding of its structure, to gain knowledge about its known components and to search for new members. Results The interaction analysis revealed that the core signaling proteins are involved in different protein complexes and our data provide evidence for dynamic interchanges between them. Fifteen of the eighteen taxis receptors (halobacterial transducers, Htrs can be assigned to four different groups depending on their interactions with the core signaling proteins. Only one of these groups, which contains six of the eight Htrs with known signals, shows the composition expected for signaling complexes (receptor, kinase CheA, adaptor CheW, response regulator CheY. From the two Hbt. salinarum CheW proteins, only CheW1 is engaged in signaling complexes with Htrs and CheA, whereas CheW2 interacts with Htrs but not with CheA. CheY connects the core signaling structure to a subnetwork consisting of the two CheF proteins (which build a link to the flagellar apparatus, CheD (the hub of the subnetwork, two CheC complexes and the receptor methylesterase CheB. Conclusions Based on our findings, we propose two hypotheses. First, Hbt. salinarum might have the capability to dynamically adjust the impact of certain Htrs or Htr clusters depending on its current needs or environmental conditions. Secondly, we propose a hypothetical feedback loop from the response regulator to Htr methylation made from the CheC proteins, CheD and CheB, which might contribute to adaptation analogous to the CheC/CheD system of B. subtilis.

  3. The eFIP system for text mining of protein interaction networks of phosphorylated proteins.

    Science.gov (United States)

    Tudor, Catalina O; Arighi, Cecilia N; Wang, Qinghua; Wu, Cathy H; Vijay-Shanker, K

    2012-01-01

    Protein phosphorylation is a central regulatory mechanism in signal transduction involved in most biological processes. Phosphorylation of a protein may lead to activation or repression of its activity, alternative subcellular location and interaction with different binding partners. Extracting this type of information from scientific literature is critical for connecting phosphorylated proteins with kinases and interaction partners, along with their functional outcomes, for knowledge discovery from phosphorylation protein networks. We have developed the Extracting Functional Impact of Phosphorylation (eFIP) text mining system, which combines several natural language processing techniques to find relevant abstracts mentioning phosphorylation of a given protein together with indications of protein-protein interactions (PPIs) and potential evidences for impact of phosphorylation on the PPIs. eFIP integrates our previously developed tools, Extracting Gene Related ABstracts (eGRAB) for document retrieval and name disambiguation, Rule-based LIterature Mining System (RLIMS-P) for Protein Phosphorylation for extraction of phosphorylation information, a PPI module to detect PPIs involving phosphorylated proteins and an impact module for relation extraction. The text mining system has been integrated into the curation workflow of the Protein Ontology (PRO) to capture knowledge about phosphorylated proteins. The eFIP web interface accepts gene/protein names or identifiers, or PubMed identifiers as input, and displays results as a ranked list of abstracts with sentence evidence and summary table, which can be exported in a spreadsheet upon result validation. As a participant in the BioCreative-2012 Interactive Text Mining track, the performance of eFIP was evaluated on document retrieval (F-measures of 78-100%), sentence-level information extraction (F-measures of 70-80%) and document ranking (normalized discounted cumulative gain measures of 93-100% and mean average

  4. Reconstruction of Protein-Protein Interaction Network of Insulin Signaling in Homo Sapiens

    Directory of Open Access Journals (Sweden)

    Saliha Durmuş Tekir

    2010-01-01

    Full Text Available Diabetes is one of the most prevalent diseases in the world. Type 1 diabetes is characterized by the failure of synthesizing and secreting of insulin because of destroyed pancreatic β-cells. Type 2 diabetes, on the other hand, is described by the decreased synthesis and secretion of insulin because of the defect in pancreatic β-cells as well as by the failure of responding to insulin because of malfunctioning of insulin signaling. In order to understand the signaling mechanisms of responding to insulin, it is necessary to identify all components in the insulin signaling network. Here, an interaction network consisting of proteins that have statistically high probability of being biologically related to insulin signaling in Homo sapiens was reconstructed by integrating Gene Ontology (GO annotations and interactome data. Furthermore, within this reconstructed network, interacting proteins which mediate the signal from insulin hormone to glucose transportation were identified using linear paths. The identification of key components functioning in insulin action on glucose metabolism is crucial for the efforts of preventing and treating type 2 diabetes mellitus.

  5. Analysis of protein-protein interaction network in chronic obstructive pulmonary disease.

    Science.gov (United States)

    Yuan, Y P; Shi, Y H; Gu, W C

    2014-10-31

    Chronic obstructive pulmonary disease (COPD) is a growing cause of morbidity and mortality throughout the world. The purpose of our study was to uncover biomarkers and explore its pathogenic mechanisms at the molecular level. The gene expression profiles of COPD samples and normal controls were downloaded from Gene Expression Omnibus. Matlab was used for data preprocessing and SAM4.0 was applied to determine the differentially expressed genes (DEGs). Furthermore, a protein-protein interaction (PPI) network was constructed by mapping the DEGs into PPI data, and functional analysis of the network was conducted with BiNGO. A total of 348 DEGs and 765 interactive genes were identified. The hub genes were mainly involved in metabolic processes and ribosome biogenesis. Several genes related to COPD in the PPI network were found, including CAMK1D, ALB, KIT, and DDX3Y. In conclusion, CAMK1D, ALB, KIT, and DDX3Y were chosen as candidate genes, which have the potential to be biomarkers or candidate target molecules to apply in clinical diagnosis and treatment of COPD.

  6. PCE-FR: A Novel Method for Identifying Overlapping Protein Complexes in Weighted Protein-Protein Interaction Networks Using Pseudo-Clique Extension Based on Fuzzy Relation.

    Science.gov (United States)

    Cao, Buwen; Luo, Jiawei; Liang, Cheng; Wang, Shulin; Ding, Pingjian

    2016-10-01

    Identifying overlapping protein complexes in protein-protein interaction (PPI) networks can provide insight into cellular functional organization and thus elucidate underlying cellular mechanisms. Recently, various algorithms for protein complexes detection have been developed for PPI networks. However, majority of algorithms primarily depend on network topological feature and/or gene expression profile, failing to consider the inherent biological meanings between protein pairs. In this paper, we propose a novel method to detect protein complexes using pseudo-clique extension based on fuzzy relation (PCE-FR). Our algorithm operates in three stages: it first forms the nonoverlapping protein substructure based on fuzzy relation and then expands each substructure by adding neighbor proteins to maximize the cohesive score. Finally, highly overlapped candidate protein complexes are merged to form the final protein complex set. Particularly, our algorithm employs the biological significance hidden in protein pairs to construct edge weight for protein interaction networks. The experiment results show that our method can not only outperform classical algorithms such as CFinder, ClusterONE, CMC, RRW, HC-PIN, and ProRank +, but also achieve ideal overall performance in most of the yeast PPI datasets in terms of composite score consisting of precision, accuracy, and separation. We further apply our method to a human PPI network from the HPRD dataset and demonstrate it is very effective in detecting protein complexes compared to other algorithms.

  7. Analysis of Arf1 GTPase-dependent membrane binding and remodeling using the exomer secretory vesicle cargo adaptor

    Science.gov (United States)

    Paczkowski, Jon E.; Fromme, J. Christopher

    2016-01-01

    Summary Protein-protein and protein-membrane interactions play a critical role in shaping biological membranes through direct physical contact with the membrane surface. This is particularly evident in many steps of membrane trafficking, in which proteins deform the membrane and induce fission to form transport carriers. The small GTPase Arf1 and related proteins have the ability to remodel membranes by insertion of an amphipathic helix into the membrane. Arf1 and the exomer cargo adaptor coordinate cargo sorting into subset of secretory vesicle carriers in the model organism Saccharomyces cerevisiae. Here, we detail the assays we used to explore the cooperative action of Arf1 and exomer to bind and remodel membranes. We expect these methods are broadly applicable to other small GTPase/effector systems where investigation of membrane binding and remodeling is of interest. PMID:27632000

  8. Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

    Science.gov (United States)

    Du, Pufeng; Wang, Lusheng

    2014-01-01

    One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

  9. Construction and analysis of the protein-protein interaction networks based on gene expression profiles of Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Hindol Rakshit

    Full Text Available BACKGROUND: Parkinson's Disease (PD is one of the most prevailing neurodegenerative diseases. Improving diagnoses and treatments of this disease is essential, as currently there exists no cure for this disease. Microarray and proteomics data have revealed abnormal expression of several genes and proteins responsible for PD. Nevertheless, few studies have been reported involving PD-specific protein-protein interactions. RESULTS: Microarray based gene expression data and protein-protein interaction (PPI databases were combined to construct the PPI networks of differentially expressed (DE genes in post mortem brain tissue samples of patients with Parkinson's disease. Samples were collected from the substantia nigra and the frontal cerebral cortex. From the microarray data, two sets of DE genes were selected by 2-tailed t-tests and Significance Analysis of Microarrays (SAM, run separately to construct two Query-Query PPI (QQPPI networks. Several topological properties of these networks were studied. Nodes with High Connectivity (hubs and High Betweenness Low Connectivity (bottlenecks were identified to be the most significant nodes of the networks. Three and four-cliques were identified in the QQPPI networks. These cliques contain most of the topologically significant nodes of the networks which form core functional modules consisting of tightly knitted sub-networks. Hitherto unreported 37 PD disease markers were identified based on their topological significance in the networks. Of these 37 markers, eight were significantly involved in the core functional modules and showed significant change in co-expression levels. Four (ARRB2, STX1A, TFRC and MARCKS out of the 37 markers were found to be associated with several neurotransmitters including dopamine. CONCLUSION: This study represents a novel investigation of the PPI networks for PD, a complex disease. 37 proteins identified in our study can be considered as PD network biomarkers. These network

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

    Science.gov (United States)

    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…

  11. Insight into bacterial virulence mechanisms against host immune response via the Yersinia pestis-human protein-protein interaction network.

    Science.gov (United States)

    Yang, Huiying; Ke, Yuehua; Wang, Jian; Tan, Yafang; Myeni, Sebenzile K; Li, Dong; Shi, Qinghai; Yan, Yanfeng; Chen, Hui; Guo, Zhaobiao; Yuan, Yanzhi; Yang, Xiaoming; Yang, Ruifu; Du, Zongmin

    2011-11-01

    A Yersinia pestis-human protein interaction network is reported here to improve our understanding of its pathogenesis. Up to 204 interactions between 66 Y. pestis bait proteins and 109 human proteins were identified by yeast two-hybrid assay and then combined with 23 previously published interactions to construct a protein-protein interaction network. Topological analysis of the interaction network revealed that human proteins targeted by Y. pestis were significantly enriched in the proteins that are central in the human protein-protein interaction network. Analysis of this network showed that signaling pathways important for host immune responses were preferentially targeted by Y. pestis, including the pathways involved in focal adhesion, regulation of cytoskeleton, leukocyte transendoepithelial migration, and Toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling. Cellular pathways targeted by Y. pestis are highly relevant to its pathogenesis. Interactions with host proteins involved in focal adhesion and cytoskeketon regulation pathways could account for resistance of Y. pestis to phagocytosis. Interference with TLR and MAPK signaling pathways by Y. pestis reflects common characteristics of pathogen-host interaction that bacterial pathogens have evolved to evade host innate immune response by interacting with proteins in those signaling pathways. Interestingly, a large portion of human proteins interacting with Y. pestis (16/109) also interacted with viral proteins (Epstein-Barr virus [EBV] and hepatitis C virus [HCV]), suggesting that viral and bacterial pathogens attack common cellular functions to facilitate infections. In addition, we identified vasodilator-stimulated phosphoprotein (VASP) as a novel interaction partner of YpkA and showed that YpkA could inhibit in vitro actin assembly mediated by VASP.

  12. Predict drug-protein interaction in cellular networking.

    Science.gov (United States)

    Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

    2013-01-01

    Involved with many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, GPCRs (G-protein-coupled receptors) are the most frequent targets for drug development: over 50% of all prescription drugs currently on the market are actually acting by targeting GPCRs directly or indirectly. Found in every living thing and nearly all cells, ion channels play crucial roles for many vital functions in life, such as heartbeat, sensory transduction, and central nervous system response. Their dysfunction may have significant impact to human health, and hence ion channels are deemed as "the next GPCRs". To develop GPCR-targeting or ion-channel-targeting drugs, the first important step is to identify the interactions between potential drug compounds with the two kinds of protein receptors in the cellular networking. In this minireview, we are to introduce two predictors. One is called iGPCR-Drug accessible at http://www.jci-bioinfo.cn/iGPCR-Drug/; the other called iCDI-PseFpt at http://www.jci-bioinfo.cn/iCDI-PseFpt. The former is for identifying the interactions of drug compounds with GPCRs; while the latter for that with ion channels. In both predictors, the drug compound was formulated by the two-dimensional molecular fingerprint, and the protein receptor by the pseudo amino acid composition generated with the grey model theory, while the operation engine was the fuzzy K-nearest neighbor algorithm. For the convenience of most experimental pharmaceutical and medical scientists, a step-bystep guide is provided on how to use each of the two web-servers to get the desired results without the need to follow the complicated mathematics involved originally for their establishment.

  13. JiffyNet: a web-based instant protein network modeler for newly sequenced species.

    Science.gov (United States)

    Kim, Eiru; Kim, Hanhae; Lee, Insuk

    2013-07-01

    Revolutionary DNA sequencing technology has enabled affordable genome sequencing for numerous species. Thousands of species already have completely decoded genomes, and tens of thousands more are in progress. Naturally, parallel expansion of the functional parts list library is anticipated, yet genome-level understanding of function also requires maps of functional relationships, such as functional protein networks. Such networks have been constructed for many sequenced species including common model organisms. Nevertheless, the majority of species with sequenced genomes still have no protein network models available. Moreover, biologists might want to obtain protein networks for their species of interest on completion of the genome projects. Therefore, there is high demand for accessible means to automatically construct genome-scale protein networks based on sequence information from genome projects only. Here, we present a public web server, JiffyNet, specifically designed to instantly construct genome-scale protein networks based on associalogs (functional associations transferred from a template network by orthology) for a query species with only protein sequences provided. Assessment of the networks by JiffyNet demonstrated generally high predictive ability for pathway annotations. Furthermore, JiffyNet provides network visualization and analysis pages for wide variety of molecular concepts to facilitate network-guided hypothesis generation. JiffyNet is freely accessible at http://www.jiffynet.org.

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

    OpenAIRE

    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...

  15. Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information

    Directory of Open Access Journals (Sweden)

    Pedamallu Chandra Sekhar

    2010-08-01

    Full Text Available Abstract Background Protein-protein interactions are crucially important for cellular processes. Knowledge of these interactions improves the understanding of cell cycle, metabolism, signaling, transport, and secretion. Information about interactions can hint at molecular causes of diseases, and can provide clues for new therapeutic approaches. Several (usually expensive and time consuming experimental methods can probe protein - protein interactions. Data sets, derived from such experiments make the development of prediction methods feasible, and make the creation of protein-protein interaction network predicting tools possible. Methods Here we report the development of a simple open source program module (OpenPPI_predictor that can generate a putative protein-protein interaction network for target genomes. This tool uses the orthologous interactome network data from a related, experimentally studied organism. Results Results from our predictions can be visualized using the Cytoscape visualization software, and can be piped to downstream processing algorithms. We have employed our program to predict protein-protein interaction network for the human parasite roundworm Brugia malayi, using interactome data from the free living nematode Caenorhabditis elegans. Availability The OpenPPI_predictor source code is available from http://tools.neb.com/~posfai/.

  16. Perturbation waves in proteins and protein networks: Applications of percolation and game theories in signaling and drug design

    CERN Document Server

    Antal, Miklos A; Csermely, Peter

    2008-01-01

    The network paradigm is increasingly used to describe the dynamics of complex systems. Here we review the current results and propose future development areas in the assessment of perturbation waves, i.e. propagating structural changes in amino acid networks building individual protein molecules and in protein-protein interaction networks (interactomes). We assess the possibilities and critically review the initial attempts for the application of game theory to the often rather complicated process, when two protein molecules approach each other, mutually adjust their conformations via multiple communication steps and finally, bind to each other. We also summarize available data on the application of percolation theory for the prediction of amino acid network- and interactome-dynamics. Furthermore, we give an overview of the dissection of signals and noise in the cellular context of various perturbations. Finally, we propose possible applications of the reviewed methodologies in drug design.

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

    Directory of Open Access Journals (Sweden)

    Lei Hua

    2016-01-01

    Full Text Available 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.

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

    Science.gov (United States)

    Hua, Lei; 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.

  19. Construction of a protein-protein interaction network of Wilms' tumor and pathway prediction of molecular complexes.

    Science.gov (United States)

    Teng, W J; Zhou, C; Liu, L J; Cao, X J; Zhuang, J; Liu, G X; Sun, C G

    2016-05-23

    Wilms' tumor (WT), or nephroblastoma, is the most common malignant renal cancer that affects the pediatric population. Great progress has been achieved in the treatment of WT, but it cannot be cured at present. Nonetheless, a protein-protein interaction network of WT should provide some new ideas and methods. The purpose of this study was to analyze the protein-protein interaction network of WT. We screened the confirmed disease-related genes using the Online Mendelian Inheritance in Man database, created a protein-protein interaction network based on biological function in the Cytoscape software, and detected molecular complexes and relevant pathways that may be included in the network. The results showed that the protein-protein interaction network of WT contains 654 nodes, 1544 edges, and 5 molecular complexes. Among them, complex 1 is predicted to be related to the Jak-STAT signaling pathway, regulation of hematopoiesis by cytokines, cytokine-cytokine receptor interaction, cytokine and inflammatory responses, and hematopoietic cell lineage pathways. Molecular complex 4 shows a correlation of WT with colorectal cancer and the ErbB signaling pathway. The proposed method can provide the bioinformatic foundation for further elucidation of the mechanisms of WT development.

  20. Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks

    Science.gov (United States)

    2012-09-21

    transduction components between organelle such as the nucleus and mitochondria as the cell strives to maintain homeostasis. Many of these communication... Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks Paulo Shakarian1*, J. Kenneth Wickiser2 1 Paulo Shakarian...pathogens on host protein networks for humans and Arabidopsis - noting striking similarities . Specifically, we preform k-shell decomposition analysis on

  1. Topology association analysis in weighted protein interaction network for gene prioritization

    Science.gov (United States)

    Wu, Shunyao; Shao, Fengjing; Zhang, Qi; Ji, Jun; Xu, Shaojie; Sun, Rencheng; Sun, Gengxin; Du, Xiangjun; Sui, Yi

    2016-11-01

    Although lots of algorithms for disease gene prediction have been proposed, the weights of edges are rarely taken into account. In this paper, the strengths of topology associations between disease and essential genes are analyzed in weighted protein interaction network. Empirical analysis demonstrates that compared to other genes, disease genes are weakly connected with essential genes in protein interaction network. Based on this finding, a novel global distance measurement for gene prioritization with weighted protein interaction network is proposed in this paper. Positive and negative flow is allocated to disease and essential genes, respectively. Additionally network propagation model is extended for weighted network. Experimental results on 110 diseases verify the effectiveness and potential of the proposed measurement. Moreover, weak links play more important role than strong links for gene prioritization, which is meaningful to deeply understand protein interaction network.

  2. Proteomic shifts in embryonic stem cells with gene dose modifications suggest the presence of balancer proteins in protein regulatory networks.

    Directory of Open Access Journals (Sweden)

    Lei Mao

    Full Text Available Large numbers of protein expression changes are usually observed in mouse models for neurodegenerative diseases, even when only a single gene was mutated in each case. To study the effect of gene dose alterations on the cellular proteome, we carried out a proteomic investigation on murine embryonic stem cells that either overexpressed individual genes or displayed aneuploidy over a genomic region encompassing 14 genes. The number of variant proteins detected per cell line ranged between 70 and 110, and did not correlate with the number of modified genes. In cell lines with single gene mutations, up and down-regulated proteins were always in balance in comparison to parental cell lines regarding number as well as concentration of differentially expressed proteins. In contrast, dose alteration of 14 genes resulted in an unequal number of up and down-regulated proteins, though the balance was kept at the level of protein concentration. We propose that the observed protein changes might partially be explained by a proteomic network response. Hence, we hypothesize the existence of a class of "balancer" proteins within the proteomic network, defined as proteins that buffer or cushion a system, and thus oppose multiple system disturbances. Through database queries and resilience analysis of the protein interaction network, we found that potential balancer proteins are of high cellular abundance, possess a low number of direct interaction partners, and show great allelic variation. Moreover, balancer proteins contribute more heavily to the network entropy, and thus are of high importance in terms of system resilience. We propose that the "elasticity" of the proteomic regulatory network mediated by balancer proteins may compensate for changes that occur under diseased conditions.

  3. Classification of protein-protein interaction full-text documents using text and citation network features.

    Science.gov (United States)

    Kolchinsky, Artemy; Abi-Haidar, Alaa; Kaur, Jasleen; Hamed, Ahmed Abdeen; Rocha, Luis M

    2010-01-01

    We participated (as Team 9) in the Article Classification Task of the Biocreative II.5 Challenge: binary classification of full-text documents relevant for protein-protein interaction. We used two distinct classifiers for the online and offline challenges: 1) the lightweight Variable Trigonometric Threshold (VTT) linear classifier we successfully introduced in BioCreative 2 for binary classification of abstracts and 2) a novel Naive Bayes classifier using features from the citation network of the relevant literature. We supplemented the supplied training data with full-text documents from the MIPS database. The lightweight VTT classifier was very competitive in this new full-text scenario: it was a top-performing submission in this task, taking into account the rank product of the Area Under the interpolated precision and recall Curve, Accuracy, Balanced F-Score, and Matthew's Correlation Coefficient performance measures. The novel citation network classifier for the biomedical text mining domain, while not a top performing classifier in the challenge, performed above the central tendency of all submissions, and therefore indicates a promising new avenue to investigate further in bibliome informatics.

  4. Kit- and Fc epsilonRI-induced differential phosphorylation of the transmembrane adaptor molecule NTAL/LAB/LAT2 allows flexibility in its scaffolding function in mast cells

    DEFF Research Database (Denmark)

    Iwaki, Shoko; Spicka, Jiri; Tkaczyk, Christine;

    2008-01-01

    The transmembrane adaptor protein (TRAP), NTAL, is phosphorylated in mast cells following FcvarepsilonRI aggregation whereby it cooperates with LAT to induce degranulation. The Kit ligand, stem cell factor (SCF), enhances antigen-induced degranulation and this also appears to be NTAL......-knock down-human mast cells. The observations reported herein support the conclusion that NTAL may be differentially utilized by specific receptors for relaying alternative signals and this suggests a flexibility in the function of TRAPs not previously appreciated....

  5. ATM-Dependent Phosphorylation of All Three Members of the MRN Complex: From Sensor to Adaptor.

    Science.gov (United States)

    Lavin, Martin F; Kozlov, Sergei; Gatei, Magtouf; Kijas, Amanda W

    2015-10-23

    The recognition, signalling and repair of DNA double strand breaks (DSB) involves the participation of a multitude of proteins and post-translational events that ensure maintenance of genome integrity. Amongst the proteins involved are several which when mutated give rise to genetic disorders characterised by chromosomal abnormalities, cancer predisposition, neurodegeneration and other pathologies. ATM (mutated in ataxia-telangiectasia (A-T) and members of the Mre11/Rad50/Nbs1 (MRN complex) play key roles in this process. The MRN complex rapidly recognises and locates to DNA DSB where it acts to recruit and assist in ATM activation. ATM, in the company of several other DNA damage response proteins, in turn phosphorylates all three members of the MRN complex to initiate downstream signalling. While ATM has hundreds of substrates, members of the MRN complex play a pivotal role in mediating the downstream signalling events that give rise to cell cycle control, DNA repair and ultimately cell survival or apoptosis. Here we focus on the interplay between ATM and the MRN complex in initiating signaling of breaks and more specifically on the adaptor role of the MRN complex in mediating ATM signalling to downstream substrates to control different cellular processes.

  6. A new method for predicting essential proteins based on dynamic network topology and complex information.

    Science.gov (United States)

    Luo, Jiawei; Kuang, Ling

    2014-10-01

    Predicting essential proteins is highly significant because organisms can not survive or develop even if only one of these proteins is missing. Improvements in high-throughput technologies have resulted in a large number of available protein-protein interactions. By taking advantage of these interaction data, researchers have proposed many computational methods to identify essential proteins at the network level. Most of these approaches focus on the topology of a static protein interaction network. However, the protein interaction network changes with time and condition. This important inherent dynamics of the protein interaction network is overlooked by previous methods. In this paper, we introduce a new method named CDLC to predict essential proteins by integrating dynamic local average connectivity and in-degree of proteins in complexes. CDLC is applied to the protein interaction network of Saccharomyces cerevisiae. The results show that CDLC outperforms five other methods (Degree Centrality (DC), Local Average Connectivity-based method (LAC), Sum of ECC (SoECC), PeC and Co-Expression Weighted by Clustering coefficient (CoEWC)). In particular, CDLC could improve the prediction precision by more than 45% compared with DC methods. CDLC is also compared with the latest algorithm CEPPK, and a higher precision is achieved by CDLC. CDLC is available as Supplementary materials. The default settings of active threshold and alpha-parameter are 0.8 and 0.1, respectively.

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

    Science.gov (United States)

    2013-05-07

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

  8. A network biology approach to understanding the importance of chameleon proteins in human physiology and pathology.

    Science.gov (United States)

    Bahramali, Golnaz; Goliaei, Bahram; Minuchehr, Zarrin; Marashi, Sayed-Amir

    2017-02-01

    Chameleon proteins are proteins which include sequences that can adopt α-helix-β-strand (HE-chameleon) or α-helix-coil (HC-chameleon) or β-strand-coil (CE-chameleon) structures to operate their crucial biological functions. In this study, using a network-based approach, we examined the chameleon proteins to give a better knowledge on these proteins. We focused on proteins with identical chameleon sequences with more than or equal to seven residues long in different PDB entries, which adopt HE-chameleon, HC-chameleon, and CE-chameleon structures in the same protein. One hundred and ninety-one human chameleon proteins were identified via our in-house program. Then, protein-protein interaction (PPI) networks, Gene ontology (GO) enrichment, disease network, and pathway enrichment analyses were performed for our derived data set. We discovered that there are chameleon sequences which reside in protein-protein interaction regions between two proteins critical for their dual function. Analysis of the PPI networks for chameleon proteins introduced five hub proteins, namely TP53, EGFR, HSP90AA1, PPARA, and HIF1A, which were presented in four PPI clusters. The outcomes demonstrate that the chameleon regions are in critical domains of these proteins and are important in the development and treatment of human cancers. The present report is the first network-based functional study of chameleon proteins using computational approaches and might provide a new perspective for understanding the mechanisms of diseases helping us in developing new medical therapies along with discovering new proteins with chameleon properties which are highly important in cancer.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. Protein modularity, cooperative binding, and hybrid regulatory states underlie transcriptional network diversification.

    Science.gov (United States)

    Baker, Christopher R; Booth, Lauren N; Sorrells, Trevor R; Johnson, Alexander D

    2012-09-28

    We examine how different transcriptional network structures can evolve from an ancestral network. By characterizing how the ancestral mode of gene regulation for genes specific to a-type cells in yeast species evolved from an activating paradigm to a repressing one, we show that regulatory protein modularity, conversion of one cis-regulatory sequence to another, distribution of binding energy among protein-protein and protein-DNA interactions, and exploitation of ancestral network features all contribute to the evolution of a novel regulatory mode. The formation of this derived mode of regulation did not disrupt the ancestral mode and thereby created a hybrid regulatory state where both means of transcription regulation (ancestral and derived) contribute to the conserved expression pattern of the network. Finally, we show how this hybrid regulatory state has resolved in different ways in different lineages to generate the diversity of regulatory network structures observed in modern species.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  13. Protein signaling networks from single cell fluctuations and information theory profiling.

    Science.gov (United States)

    Shin, Young Shik; Remacle, F; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R D; Heath, James R

    2011-05-18

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network.

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

    Science.gov (United States)

    Mannakee, Brian K; Gutenkunst, Ryan N

    2016-07-01

    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.

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

    Directory of Open Access Journals (Sweden)

    Brian K Mannakee

    2016-07-01

    Full Text Available 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.

  16. Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

    Science.gov (United States)

    Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

    2011-01-01

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

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

    Directory of Open Access Journals (Sweden)

    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.

  18. The organisational structure of protein networks: revisiting the centrality-lethality hypothesis.

    Science.gov (United States)

    Raman, Karthik; Damaraju, Nandita; Joshi, Govind Krishna

    2014-03-01

    Protein networks, describing physical interactions as well as functional associations between proteins, have been unravelled for many organisms in the recent past. Databases such as the STRING provide excellent resources for the analysis of such networks. In this contribution, we revisit the organisation of protein networks, particularly the centrality-lethality hypothesis, which hypothesises that nodes with higher centrality in a network are more likely to produce lethal phenotypes on removal, compared to nodes with lower centrality. We consider the protein networks of a diverse set of 20 organisms, with essentiality information available in the Database of Essential Genes and assess the relationship between centrality measures and lethality. For each of these organisms, we obtained networks of high-confidence interactions from the STRING database, and computed network parameters such as degree, betweenness centrality, closeness centrality and pairwise disconnectivity indices. We observe that the networks considered here are predominantly disassortative. Further, we observe that essential nodes in a network have a significantly higher average degree and betweenness centrality, compared to the network average. Most previous studies have evaluated the centrality-lethality hypothesis for Saccharomyces cerevisiae and Escherichia coli; we here observe that the centrality-lethality hypothesis hold goods for a large number of organisms, with certain limitations. Betweenness centrality may also be a useful measure to identify essential nodes, but measures like closeness centrality and pairwise disconnectivity are not significantly higher for essential nodes.

  19. Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets.

    Science.gov (United States)

    Vinayagam, Arunachalam; Gibson, Travis E; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

    2016-05-03

    The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

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

    Institute of Scientific and Technical Information of China (English)

    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.

  4. SEBINI-CABIN: An Analysis Pipeline for Biological Network Inference, with a Case Study in Protein-Protein Interaction Network Reconstruction

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-12-01

    One of the core tasks of the emerging discipline of systems biology is the reconstruction of the various biological networks in an organism. The importance of understanding such regulatory, interaction, and signaling networks has fueled the development by bioinformatics researchers of many inference algorithms for determining their structure. The Software Environment for BIological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment, testing, and improvement of algorithms used to reconstruct the structures of regulatory and interaction networks from high-throughput expression data. Networks inferred from the SEBINI software platform can be further analyzed using the Collective Analysis of Biological Interaction Networks (CABIN) tool, a software package for exploratory data analysis that allows basic integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources. Thus, the combined SEBINI–CABIN platform aids in the more accurate determination of biological networks, in less time, with less effort. In this paper, we present a case study demonstrating the use of the SEBINI and CABIN tools for protein-protein interaction network reconstruction. Incorporating the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro) algorithm into the SEBINI toolkit, we have created a pipeline for structural inference and supplemental analysis of protein-protein interaction networks from sets of mass spectrometry bait-prey experiment data. To the best of our knowledge the pipeline so designed is the first to be publicly available for such use. A demonstration web site for SEBINI can be accessed from https://www.emsl.pnl.gov/NIT/NIT.html. Source code and PostgreSQL database schema are available under open source license. Contact: ronald.taylor@pnl.gov. For commercial use, some algorithms included in SEBINI require licensing from the original developers. The

  5. The use of Gene Ontology terms for predicting highly-connected 'hub' nodes in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Cherkasov Artem

    2008-09-01

    Full Text Available Abstract Background Protein-protein interactions mediate a wide range of cellular functions and responses and have been studied rigorously through recent large-scale proteomics experiments and bioinformatics analyses. One of the most important findings of those endeavours was the observation that 'hub' proteins participate in significant numbers of protein interactions and play critical roles in the organization and function of cellular protein interaction networks (PINs 12. It has also been demonstrated that such hub proteins may constitute an important pool of attractive drug targets. Thus, it is crucial to be able to identify hub proteins based not only on experimental data but also by means of bioinformatics predictions. Results A hub protein classifier has been developed based on the available interaction data and Gene Ontology (GO annotations for proteins in the Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster and Homo sapiens genomes. In particular, by utilizing the machine learning method of boosting trees we were able to create a predictive bioinformatics tool for the identification of proteins that are likely to play the role of a hub in protein interaction networks. Testing the developed hub classifier on external sets of experimental protein interaction data in Methicillin-resistant Staphylococcus aureus (MRSA 252 and Caenorhabditis elegans demonstrated that our approach can predict hub proteins with a high degree of accuracy. A practical application of the developed bioinformatics method has been illustrated by the effective protein bait selection for large-scale pull-down experiments that aim to map complete protein-protein interaction networks for several species. Conclusion The successful development of an accurate hub classifier demonstrated that highly-connected proteins tend to share certain relevant functional properties reflected in their Gene Ontology annotations. It is anticipated that the developed

  6. Integration and visualization of non-coding RNA and protein interaction networks

    DEFF Research Database (Denmark)

    Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian;

    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 integrating ncRNA and protein networks, RAIN provides a more complete picture of the cell’s complex......) co-occurrences found by text mining Medline abstracts. Each resource was assigned a reliability score by assessing its agreement with a gold standard set of microRNA-target interactions. RAIN is available at: http://rth.dk/resources/rain...

  7. Prioritization of potential candidate disease genes by topological similarity of protein-protein interaction network and phenotype data.

    Science.gov (United States)

    Luo, Jiawei; Liang, Shiyu

    2015-02-01

    Identifying candidate disease genes is important to improve medical care. However, this task is challenging in the post-genomic era. Several computational approaches have been proposed to prioritize potential candidate genes relying on protein-protein interaction (PPI) networks. However, the experimental PPI network is usually liable to contain a number of spurious interactions. In this paper, we construct a reliable heterogeneous network by fusing multiple networks, a PPI network reconstructed by topological similarity, a phenotype similarity network and known associations between diseases and genes. We then devise a random walk-based algorithm on the reliable heterogeneous network called RWRHN to prioritize potential candidate genes for inherited diseases. The results of leave-one-out cross-validation experiments show that the RWRHN algorithm has better performance than the RWRH and CIPHER methods in inferring disease genes. Furthermore, RWRHN is used to predict novel causal genes for 16 diseases, including breast cancer, diabetes mellitus type 2, and prostate cancer, as well as to detect disease-related protein complexes. The top predictions are supported by literature evidence.

  8. The adaptor molecule SAP plays essential roles during invariant NKT cell cytotoxicity and lytic synapse formation.

    Science.gov (United States)

    Das, Rupali; Bassiri, Hamid; Guan, Peng; Wiener, Susan; Banerjee, Pinaki P; Zhong, Ming-Chao; Veillette, André; Orange, Jordan S; Nichols, Kim E

    2013-04-25

    The adaptor molecule signaling lymphocytic activation molecule-associated protein (SAP) plays critical roles during invariant natural killer T (iNKT) cell ontogeny. As a result, SAP-deficient humans and mice lack iNKT cells. The strict developmental requirement for SAP has made it difficult to discern its possible involvement in mature iNKT cell functions. By using temporal Cre recombinase-mediated gene deletion to ablate SAP expression after completion of iNKT cell development, we demonstrate that SAP is essential for T-cell receptor (TCR)-induced iNKT cell cytotoxicity against T-cell and B-cell leukemia targets in vitro and iNKT-cell-mediated control of T-cell leukemia growth in vivo. These findings are not restricted to the murine system: silencing RNA-mediated suppression of SAP expression in human iNKT cells also significantly impairs TCR-induced cytolysis. Mechanistic studies reveal that iNKT cell killing requires the tyrosine kinase Fyn, a known SAP-binding protein. Furthermore, SAP expression is required within iNKT cells to facilitate their interaction with T-cell targets and induce reorientation of the microtubule-organizing center to the immunologic synapse (IS). Collectively, these studies highlight a novel and essential role for SAP during iNKT cell cytotoxicity and formation of a functional IS.

  9. The clathrin adaptor AP-1 complex and Arf1 regulate planar cell polarity in vivo.

    Science.gov (United States)

    Carvajal-Gonzalez, Jose Maria; Balmer, Sophie; Mendoza, Meg; Dussert, Aurore; Collu, Giovanna; Roman, Angel-Carlos; Weber, Ursula; Ciruna, Brian; Mlodzik, Marek

    2015-04-07

    A key step in generating planar cell polarity (PCP) is the formation of restricted junctional domains containing Frizzled/Dishevelled/Diego (Fz/Dsh/Dgo) or Van Gogh/Prickle (Vang/Pk) complexes within the same cell, stabilized via Flamingo (Fmi) across cell membranes. Although models have been proposed for how these complexes acquire and maintain their polarized localization, the machinery involved in moving core PCP proteins around cells remains unknown. We describe the AP-1 adaptor complex and Arf1 as major regulators of PCP protein trafficking in vivo. AP-1 and Arf1 disruption affects the accumulation of Fz/Fmi and Vang/Fmi complexes in the proximo-distal axis, producing severe PCP phenotypes. Using novel tools, we demonstrate a direct and specific Arf1 involvement in Fz trafficking in vivo. Moreover, we uncover a conserved Arf1 PCP function in vertebrates. Our data support a model whereby the trafficking machinery plays an important part during PCP establishment, promoting formation of polarized PCP-core complexes in vivo.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Kyunghyun Park

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

  13. Landscape mapping of functional proteins in insulin signal transduction and insulin resistance: a network-based protein-protein interaction analysis.

    Directory of Open Access Journals (Sweden)

    Chiranjib Chakraborty

    Full Text Available The type 2 diabetes has increased rapidly in recent years throughout the world. The insulin signal transduction mechanism gets disrupted sometimes and it's known as insulin-resistance. It is one of the primary causes associated with type-2 diabetes. The signaling mechanisms involved several proteins that include 7 major functional proteins such as INS, INSR, IRS1, IRS2, PIK3CA, Akt2, and GLUT4. Using these 7 principal proteins, multiple sequences alignment has been created. The scores between sequences also have been developed. We have constructed a phylogenetic tree and modified it with node and distance. Besides, we have generated sequence logos and ultimately developed the protein-protein interaction network. The small insulin signal transduction protein arrangement shows complex network between the functional proteins.

  14. Sub-cellular distribution of UNC-104(KIF1A) upon binding to adaptors as UNC-16(JIP3), DNC-1(DCTN1/Glued) and SYD-2(Liprin-α) in C. elegans neurons.

    Science.gov (United States)

    Hsu, C-C; Moncaleano, J D; Wagner, O I

    2011-03-10

    The accumulation of cargo (tau, amyloid precursor protein, neurofilaments etc.) in neurons is a hallmark of various neurodegenerative diseases while we have only little knowledge how axonal transport is regulated. Kinesin-3 UNC-104(KIF1A) is the major transporter of synaptic vesicles and recent reports suggest that a cargo itself can affect the motor's activity. Inspecting an interactome map, we identify three putative UNC-104 interactors, namely UNC-16(JIP3), DNC-1(DCTN1/Glued) and SYD-2(Liprin-α), known to be adaptors in essential neuronal protein complexes. We then employed the novel method bimolecular fluorescence complementation (BiFC) assay to visualize motor-adaptor complexes in the nervous system of living C. elegans. Interestingly, the binding of UNC-104 to each adaptor protein results in different sub-cellular distributions and has distinctive effects on the motor's motility. Specifically, if UNC-104 bound to UNC-16, the motor is primarily localized in the soma of neurons while bound to DNC-1, the motor is basically found in axonal termini. On the other hand, if UNC-104 is bound to SYD-2 we identify motor populations mostly along axons. Therefore, these three adaptors inherit different functions in steering the motor to specific sub-cellular locations in the neuron.

  15. Convolutional LSTM Networks for Subcellular Localization of Proteins

    DEFF Research Database (Denmark)

    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) mod...

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

    KAUST Repository

    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

    Energy Technology Data Exchange (ETDEWEB)

    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. Increasing the efficiency of SAGE adaptor ligation by directed ligation chemistry

    Science.gov (United States)

    So, Austin P.; Turner, Robin F. B.; Haynes, Charles A.

    2004-01-01

    The ability of Serial Analysis of Gene Expression (SAGE) to provide a quantitative picture of global gene expression relies not only on the depth and accuracy of sequencing into the SAGE library, but also on the efficiency of each step required to generate the SAGE library from the starting mRNA material. The first critical step is the ligation of adaptors containing a Type IIS recognition sequence to the anchored 3′ end cDNA population that permits the release of short sequence tags (SSTs) from defined sites within the 3′ end of each transcript. Using an in vitro transcript as a template, we observed that only a small fraction of anchored 3′ end cDNA are successfully ligated with added SAGE adaptors under typical reaction conditions currently used in the SAGE protocol. Although the introduction of ∼500-fold molar excess of adaptor or the inclusion of 15% (w/v) PEG-8000 increased the yield of the adaptor-modified product, complete conversion to the desired adaptor:cDNA hetero-ligation product is not achieved. An alternative method of ligation, termed as directed ligation, is described which exploits a favourable mass-action condition created by the presence of NlaIII during ligation in combination with a novel SAGE adaptor containing a methylated base within the ligation site. Using this strategy, we were able to achieve near complete conversion of the anchored 3′ end cDNA into the desired adaptor-modified product. This new protocol therefore greatly increases the probability that a SST will be generated from every transcript, greatly enhancing the fidelity of SAGE. Directed ligation also provides a powerful means to achieve near-complete ligation of any appropriately designed adaptor to its respective target. PMID:15247329

  19. Relations between rheological properties and network structure of soy protein gels

    NARCIS (Netherlands)

    Renkema, J.M.S.

    2004-01-01

    This paper focuses on the relations between network structure and rheological properties of soy protein gels as a function of pH and ionic strength. Network structure has been characterized independently by permeability measurements and confocal scanning laser microscopy in terms of coarseness. Resu

  20. Small-World Effect of Complex Network and Its Application toProtein Folding

    Institute of Scientific and Technical Information of China (English)

    卢全国; 陈宝方; 彭华魁; 祖巧红

    2004-01-01

    The famous "six letters" experiment carried out by Milgram demonstrated the existence of small-world effect in a complex network. One vertex tends to be connected to another by a shortest path through network because of the small-world effect. This paper uses the small-world effect to study protein folding pathway.

  1. Emergence of Complexity in Protein Functions and Metabolic Networks

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Jun Pan

    2014-01-01

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

  3. Networks of ProteinProtein Interactions: From Uncertainty to Molecular Details.

    Science.gov (United States)

    Garcia-Garcia, Javier; Bonet, Jaume; Guney, Emre; Fornes, Oriol; Planas, Joan; Oliva, Baldo

    2012-05-01

    Proteins are the bricks and mortar of cells. The work of proteins is structural and functional, as they are the principal element of the organization of the cell architecture, but they also play a relevant role in its metabolism and regulation. To perform all these functions, proteins need to interact with each other and with other bio-molecules, either to form complexes or to recognize precise targets of their action. For instance, a particular transcription factor may activate one gene or another depending on its interactions with other proteins and not only with DNA. Hence, the ability of a protein to interact with other bio-molecules, and the partners they have at each particular time and location can be crucial to characterize the role of a protein. Proteins rarely act alone; they rather constitute a mingled network of physical interactions or other types of relationships (such as metabolic and regulatory) or signaling cascades. In this context, understanding the function of a protein implies to recognize the members of its neighborhood and to grasp how they associate, both at the systemic and atomic level. The network of physical interactions between the proteins of a system, cell or organism, is defined as the interactome. The purpose of this review is to deepen the description of interactomes at different levels of detail: from the molecular structure of complexes to the global topology of the network of interactions. The approaches and techniques applied experimentally and computationally to attain each level are depicted. The limits of each technique and its integration into a model network, the challenges and actual problems of completeness of an interactome, and the reliability of the interactions are reviewed and summarized. Finally, the application of the current knowledge of protein-protein interactions on modern network medicine and protein function annotation is also explored.

  4. The topology and dynamics of protein complexes: insights from intra- molecular network theory.

    Science.gov (United States)

    Hu, Guang; Zhou, Jianhong; Yan, Wenying; Chen, Jiajia; Shen, Bairong

    2013-03-01

    Intra-molecular interactions within complex systems play a pivotal role in the biological function. They form a major challenge to computational structural proteomics. The network paradigm treats any system as a set of nodes linked by edges corresponding to the relations existing between the nodes. It offers a computationally efficient tool to meet this challenge. Here, we review the recent advances in the use of network theory to study the topology and dynamics of protein- ligand and protein-nucleic acid complexes. The study of protein complexes networks not only involves the topological classification in term of network parameters, but also reveals the consistent picture of intrinsic functional dynamics. Current dynamical analysis focuses on a plethora of functional phenomena: the process of allosteric communication, the binding induced conformational changes, prediction and identification of binding sites of protein complexes, which will give insights into intra-protein complexes interactions. Furthermore, such computational results may elucidate a variety of known biological processes and experimental data, and thereby demonstrate a huge potential for applications such as drug design and functional genomics. Finally we describe some web-based resources for protein complexes, as well as protein network servers and related bioinformatics tools.

  5. Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803.

    Science.gov (United States)

    Pei, Guangsheng; Chen, Lei; Wang, Jiangxin; Qiao, Jianjun; Zhang, Weiwen

    2014-01-01

    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 need 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 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 weighted gene co-expression 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.

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

    KAUST Repository

    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. Probing the Extent of Randomness in Protein Interaction Networks

    Science.gov (United States)

    2008-07-11

    elegans [16], Plasmodium falciparum [17], Campylobacter jejuni [18], and Homo sapiens [7]. A number of efforts to compile and, in some cases, curate the...Weighted Connectivity in Two PPI Networks. (A) Helicobacter pylori and (B) Campylobacter jejuni . For k1k2.10, probabilities of interaction P(k1,k2) were...Four PPI Networks and their DCDW Equivalents. (A) Drosophila melanogaster, (B) Campylobacter jejuni , (C) Escherichia coli (HT2), and (D) Escherichia

  8. Control of Cellular Structural Networks Through Unstructured Protein Domains

    Science.gov (United States)

    2016-07-01

    structural and mechanical networks in cells. The research plan seeks to determine the role of molecular­scale steric forces on the assembly, mechanics...Distribution Unlimited UU UU UU UU 01-07-2016 1-Oct-2009 30-Sep-2015 Final Report: WHITEPAPER; Research Area 8; Control of cellular structural networks ...any other aspect of this collection of information, including suggesstions for reducing this burden, to Washington Headquarters Services , Directorate

  9. A Common Variant in the Adaptor Mal Regulates Interferon Gamma Signaling.

    Science.gov (United States)

    Ní Cheallaigh, Clíona; Sheedy, Frederick J; Harris, James; Muñoz-Wolf, Natalia; Lee, Jinhee; West, Kim; McDermott, Eva Palsson; Smyth, Alicia; Gleeson, Laura E; Coleman, Michelle; Martinez, Nuria; Hearnden, Claire H A; Tynan, Graham A; Carroll, Elizabeth C; Jones, Sarah A; Corr, Sinéad C; Bernard, Nicholas J; Hughes, Mark M; Corcoran, Sarah E; O'Sullivan, Mary; Fallon, Ciara M; Kornfeld, Hardy; Golenbock, Douglas; Gordon, Stephen V; O'Neill, Luke A J; Lavelle, Ed C; Keane, Joseph

    2016-02-16

    Humans that are heterozygous for the common S180L polymorphism in the Toll-like receptor (TLR) adaptor Mal (encoded by TIRAP) are protected from a number of infectious diseases, including tuberculosis (TB), whereas those homozygous for the allele are at increased risk. The reason for this difference in susceptibility is not clear. We report that Mal has a TLR-independent role in interferon-gamma (IFN-γ) receptor signaling. Mal-dependent IFN-γ receptor (IFNGR) signaling led to mitogen-activated protein kinase (MAPK) p38 phosphorylation and autophagy. IFN-γ signaling via Mal was required for phagosome maturation and killing of intracellular Mycobacterium tuberculosis (Mtb). The S180L polymorphism, and its murine equivalent S200L, reduced the affinity of Mal for the IFNGR, thereby compromising IFNGR signaling in macrophages and impairing responses to TB. Our findings highlight a role for Mal outside the TLR system and imply that genetic variation in TIRAP may be linked to other IFN-γ-related diseases including autoimmunity and cancer.

  10. A Method for Community Detection in Protein Networks Using Spectral Optimization

    Directory of Open Access Journals (Sweden)

    Sminu Izudheen

    2011-12-01

    Full Text Available Identification of community structures in complex networks has been a challenge in many domain and discipline. In protein networks these community interactions play a vital role in identifying the outcome of many cellular mechanisms. This paper reports the use of spectral optimization of triangular modularity as an effective method to identify these community structures. The algorithm has been carefully tested on real biological data and the results acknowledge that this is a powerful method for extracting community structures from protein networks.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. Determination of Signaling Pathways in Proteins through Network Theory: Importance of the Topology.

    Science.gov (United States)

    Ribeiro, Andre A S T; Ortiz, Vanessa

    2014-04-08

    Network theory methods are being increasingly applied to proteins to investigate complex biological phenomena. Residues that are important for signaling processes can be identified by their condition as critical nodes in a protein structure network. This analysis involves modeling the protein as a graph in which each residue is represented as a node and edges are drawn between nodes that are deemed connected. In this paper, we show that the results obtained from this type of network analysis (i.e., signaling pathways, key residues for signal transmission, etc.) are profoundly affected by the topology of the network, with normally used determination of network edges by geometrical cutoff schemes giving rise to substantial statistical errors. We propose a method of determining protein structure networks by calculating inter-residue interaction energies and show that it gives an accurate and reliable description of the signal-propagation properties of a known allosteric enzyme. We also show that including covalent interactions in the network topology is essential for accurate results to be obtained.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    DEFF Research Database (Denmark)

    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...

  15. A human phenome-interactome network of protein complexes implicated in genetic disorders

    DEFF Research Database (Denmark)

    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, co...

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

    DEFF Research Database (Denmark)

    Hjerrild, M.; Stensballe, A.; Rasmussen, T.E.;

    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...

  17. The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis.

    Directory of Open Access Journals (Sweden)

    Matthew D Dyer

    Full Text Available BACKGROUND: Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion. METHODOLOGY: In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity. SIGNIFICANCE: These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions.

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

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    Anna Delprato

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

  19. Expression Profiling of Human Genetic and Protein Interaction Networks in Type 1 Diabetes

    DEFF Research Database (Denmark)

    Brunak, Søren; Bergholdt, R; Brorsson, C;

    2009-01-01

    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...... in each of the four interaction networks to evaluate evidence of significant association at network level. This method provided additional support, in an independent data set, that two of the interaction networks could be involved in T1D and highlights the following processes as risk factors: oxidative......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...

  20. Controlling for gene expression changes in transcription factor protein networks.

    Science.gov (United States)

    Banks, Charles A S; Lee, Zachary T; Boanca, Gina; Lakshminarasimhan, Mahadevan; Groppe, Brad D; Wen, Zhihui; Hattem, Gaye L; Seidel, Chris W; Florens, Laurence; Washburn, Michael P

    2014-06-01

    The development of affinity purification technologies combined with mass spectrometric analysis of purified protein mixtures has been used both to identify new protein-protein interactions and to define the subunit composition of protein complexes. Transcription factor protein interactions, however, have not been systematically analyzed using these approaches. Here, we investigated whether ectopic expression of an affinity tagged transcription factor as bait in affinity purification mass spectrometry experiments perturbs gene expression in cells, resulting in the false positive identification of bait-associated proteins when typical experimental controls are used. Using quantitative proteomics and RNA sequencing, we determined that the increase in the abundance of a set of proteins caused by overexpression of the transcription factor RelA is not sufficient for these proteins to then co-purify non-specifically and be misidentified as bait-associated proteins. Therefore, typical controls should be sufficient, and a number of different baits can be compared with a common set of controls. This is of practical interest when identifying bait interactors from a large number of different baits. As expected, we found several known RelA interactors enriched in our RelA purifications (NFκB1, NFκB2, Rel, RelB, IκBα, IκBβ, and IκBε). We also found several proteins not previously described in association with RelA, including the small mitochondrial chaperone Tim13. Using a variety of biochemical approaches, we further investigated the nature of the association between Tim13 and NFκB family transcription factors. This work therefore provides a conceptual and experimental framework for analyzing transcription factor protein interactions.

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Ascent Heating Thermal Analysis on Spacecraft Adaptor Fairings

    Science.gov (United States)

    Wang, Xiao Yen; Yuko, James; Motil, Brian

    2011-01-01

    When the Crew Exploration Vehicle (CEV) is launched, the spacecraft adaptor (SA) fairings that cover the CEV service module (SM) are exposed to aero heating. Thermal analysis is performed to compute the fairing temperatures and to investigate whether the temperatures are within the material limits for nominal ascent aeroheating case. The ascent heating is analyzed by using computational fluid dynamics (CFD) and engineering codes at Marshall Space Flight Center. The aeroheating environment data used for this work is known as Thermal Environment 3 (TE3) heating data. One of the major concerns is with the SA fairings covering the CEV SM and the SM/crew launch vehicle (CLV) flange interface. The TE3 heating rate is a function of time, wall temperature, and the spatial locations. The implementation of the TE3 heating rate as boundary conditions in the thermal analysis becomes challenging. The ascent heating thermal analysis on SA fairings and SM/CLV flange interface are performed using two commercial software packages: Cullimore & Ring (C&R) Thermal Desktop (TD) 5.1 and MSC Patran 2007r1 b. TD is the pre-and post-processor for SINDA, which is a finite-difference-based solver. In TD, the geometry is built and meshed, the boundary conditions are defined, and then SINDA is used to compute temperatures. MSC Pthermal is a finite-element- based thermal solver. MSC Patran is the pre- and post-processor for Pthermal. Regarding the boundary conditions, the convection, contact resistance, and heat load can be imposed in different ways in both programs. These two software packages are used to build the thermal model for the same analysis to validate each other and show the differences in the modeling details.

  3. Intracellular Trafficking Network of Protein Nanocapsules: Endocytosis, Exocytosis and Autophagy

    Science.gov (United States)

    Zhang, Jinxie; Zhang, Xudong; Liu, Gan; Chang, Danfeng; Liang, Xin; Zhu, Xianbing; Tao, Wei; Mei, Lin

    2016-01-01

    The inner membrane vesicle system is a complex transport system that includes endocytosis, exocytosis and autophagy. However, the details of the intracellular trafficking pathway of nanoparticles in cells have been poorly investigated. Here, we investigate in detail the intracellular trafficking pathway of protein nanocapsules using more than 30 Rab proteins as markers of multiple trafficking vesicles in endocytosis, exocytosis and autophagy. We observed that FITC-labeled protein nanoparticles were internalized by the cells mainly through Arf6-dependent endocytosis and Rab34-mediated micropinocytosis. In addition to this classic pathway: early endosome (EEs)/late endosome (LEs) to lysosome, we identified two novel transport pathways: micropinocytosis (Rab34 positive)-LEs (Rab7 positive)-lysosome pathway and EEs-liposome (Rab18 positive)-lysosome pathway. Moreover, the cells use slow endocytosis recycling pathway (Rab11 and Rab35 positive vesicles) and GLUT4 exocytosis vesicles (Rab8 and Rab10 positive) transport the protein nanocapsules out of the cells. In addition, protein nanoparticles are observed in autophagosomes, which receive protein nanocapsules through multiple endocytosis vesicles. Using autophagy inhibitor to block these transport pathways could prevent the degradation of nanoparticles through lysosomes. Using Rab proteins as vesicle markers to investigation the detail intracellular trafficking of the protein nanocapsules, will provide new targets to interfere the cellular behaver of the nanoparticles, and improve the therapeutic effect of nanomedicine. PMID:27698943

  4. Virus host protein interaction network analysis reveals that the HEV ORF3 protein may interrupt the blood coagulation process.

    Directory of Open Access Journals (Sweden)

    Yansheng Geng

    Full Text Available Hepatitis E virus (HEV is endemic worldwide and a major cause of acute liver disease in developing countries. However, the molecular mechanisms of liver pathology and clinical disease are not well understood for HEV infection. Open reading frame 3 (ORF3 of HEV encodes a small phosphoprotein, which is assumed to be involved in liver pathology and clinical disease. In this study, the interactions between the HEV ORF3 protein and human proteins were investigated using a stringent, high-throughput yeast two-hybrid (Y2H analysis. Thirty two proteins were shown to interact with genotype 1 ORF3, 28 of which have not been reported previously. These novel interactions were evaluated by coimmunoprecipitation of protein complexes from transfected cells. We found also that the ORF3 proteins of genotype 4 and rabbit HEV interacted with all of the human proteins identified by the genotype 1 ORF3 protein. However, the putative ORF3 protein derived from avian HEV did not interact with the majority of these human proteins. The identified proteins were used to infer an overall interaction map linking the ORF3 protein with components of the host cellular networks. Analysis of this interaction map, based on functional annotation with the Gene Ontology features and KEGG pathways, revealed an enrichment of host proteins involved in complement coagulation, cellular iron ion homeostasis and oxidative stress. Additional canonical pathway analysis highlighted the enriched biological pathways relevant to blood coagulation and hemostasis. Consideration of the clinical manifestations of hepatitis E reported previously and the results of biological analysis from this study suggests that the ORF3 protein is likely to lead to an imbalance of coagulation and fibrinolysis by interacting with host proteins and triggering the corresponding pathological processes. These results suggest critical approaches to further study of the pathogenesis of the HEV ORF3 protein.

  5. Predicting important residues and interaction pathways in proteins using Gaussian Network Model: binding and stability of HLA proteins.

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    Turkan Haliloglu

    Full Text Available A statistical thermodynamics approach is proposed to determine structurally and functionally important residues in native proteins that are involved in energy exchange with a ligand and other residues along an interaction pathway. The structure-function relationships, ligand binding and allosteric activities of ten structures of HLA Class I proteins of the immune system are studied by the Gaussian Network Model. Five of these models are associated with inflammatory rheumatic disease and the remaining five are properly functioning. In the Gaussian Network Model, the protein structures are modeled as an elastic network where the inter-residue interactions are harmonic. Important residues and the interaction pathways in the proteins are identified by focusing on the largest eigenvalue of the residue interaction matrix. Predicted important residues match those known from previous experimental and clinical work. Graph perturbation is used to determine the response of the important residues along the interaction pathway. Differences in response patterns of the two sets of proteins are identified and their relations to disease are discussed.

  6. Functional features and protein network of human sperm-egg interaction.

    Science.gov (United States)

    Sabetian, Soudabeh; Shamsir, Mohd Shahir; Abu Naser, Mohammed

    2014-12-01

    Elucidation of the sperm-egg interaction at the molecular level is one of the unresolved problems in sexual reproduction, and understanding the molecular mechanism is crucial in solving problems in infertility and failed in vitro fertilization (IVF). Many molecular interactions in the form of protein-protein interactions (PPIs) mediate the sperm-egg membrane interaction. Due to the complexity of the problem such as difficulties in analyzing in vivo membrane PPIs, many efforts have failed to comprehensively elucidate the fusion mechanism and the molecular interactions that mediate sperm-egg membrane fusion. The main purpose of this study was to reveal possible protein interactions and associated molecular function during sperm-egg interaction using a protein interaction network approach. Different databases have been used to construct the human sperm-egg interaction network. The constructed network revealed new interactions. These included CD151 and CD9 in human oocyte that interact with CD49 in sperm, and CD49 and ITGA4 in sperm that interact with CD63 and CD81, respectively, in the oocyte. These results showed that the different integrins in sperm may be involved in human sperm-egg interaction. It was also suggested that sperm ADAM2 plays a role as a protein candidate involved in sperm-egg membrane interaction by interacting with CD9 in the oocyte. Interleukin-4 receptor activity, receptor signaling protein tyrosine kinase activity, and manganese ion transmembrane transport activity are the major molecular functions in sperm-egg interaction protein network. The disease association analysis indicated that sperm-egg interaction defects are also reflected in other disease networks such as cardiovascular, hematological, and breast cancer diseases. By analyzing the network, we identified the major molecular functions and disease association genes in sperm-egg interaction protein. Further experimental studies will be required to confirm the significance of these new

  7. Dynamical analysis of yeast protein interaction network during the sake brewing process.

    Science.gov (United States)

    Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

    2011-12-01

    Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.

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

    Directory of Open Access Journals (Sweden)

    Gregorio eAlanis-Lobato

    2015-09-01

    Full Text Available 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 aetiology. 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.

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

    KAUST Repository

    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.

  10. Large-scale identification of human protein function using topological features of interaction network

    Science.gov (United States)

    Li, Zhanchao; Liu, Zhiqing; Zhong, Wenqian; Huang, Menghua; Wu, Na; Xie, Yun; Dai, Zong; Zou, Xiaoyong

    2016-11-01

    The annotation of protein function is a vital step to elucidate the essence of life at a molecular level, and it is also meritorious in biomedical and pharmaceutical industry. Developments of sequencing technology result in constant expansion of the gap between the number of the known sequences and their functions. Therefore, it is indispensable to develop a computational method for the annotation of protein function. Herein, a novel method is proposed to identify protein function based on the weighted human protein-protein interaction network and graph theory. The network topology features with local and global information are presented to characterise proteins. The minimum redundancy maximum relevance algorithm is used to select 227 optimized feature subsets and support vector machine technique is utilized to build the prediction models. The performance of current method is assessed through 10-fold cross-validation test, and the range of accuracies is from 67.63% to 100%. Comparing with other annotation methods, the proposed way possesses a 50% improvement in the predictive accuracy. Generally, such network topology features provide insights into the relationship between protein functions and network architectures. The source code of Matlab is freely available on request from the authors.

  11. Evidence of Probabilistic Behaviour in Protein Interaction Networks

    Science.gov (United States)

    2008-01-31

    cerevisiae by mass spectrometry. Nature 2002, 415(6868):180-183. 6. Zhu H, Bilgin M, Bangham R, Hall D, Casamayor A, Bertone P, Lan N, Jansen R, Bidlingmaier...Doucette-Stamm L, Gunsalus KC, Harper JW, Cusick ME, Roth FP , Hill DE, Vidal M: A map of the interactome network of the metazoan C. elegans

  12. Prediction of Protein Thermostability by an Efficient Neural Network Approach

    Directory of Open Access Journals (Sweden)

    Jalal Rezaeenour

    2016-10-01

    Full Text Available Introduction: Manipulation of protein stability is important for understanding the principles that govern protein thermostability, both in basic research and industrial applications. Various data mining techniques exist for prediction of thermostable proteins. Furthermore, ANN methods have attracted significant attention for prediction of thermostability, because they constitute an appropriate approach to mapping the non-linear input-output relationships and massive parallel computing. Method: An Extreme Learning Machine (ELM was applied to estimate thermal behavior of 1289 proteins. In the proposed algorithm, the parameters of ELM were optimized using a Genetic Algorithm (GA, which tuned a set of input variables, hidden layer biases, and input weights, to and enhance the prediction performance. The method was executed on a set of amino acids, yielding a total of 613 protein features. A number of feature selection algorithms were used to build subsets of the features. A total of 1289 protein samples and 613 protein features were calculated from UniProt database to understand features contributing to the enzymes’ thermostability and find out the main features that influence this valuable characteristic. Results:At the primary structure level, Gln, Glu and polar were the features that mostly contributed to protein thermostability. At the secondary structure level, Helix_S, Coil, and charged_Coil were the most important features affecting protein thermostability. These results suggest that the thermostability of proteins is mainly associated with primary structural features of the protein. According to the results, the influence of primary structure on the thermostabilty of a protein was more important than that of the secondary structure. It is shown that prediction accuracy of ELM (mean square error can improve dramatically using GA with error rates RMSE=0.004 and MAPE=0.1003. Conclusion: The proposed approach for forecasting problem

  13. A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

    Science.gov (United States)

    Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

    2015-01-01

    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 percent 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 attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test dataset of 198 proteins, achieving a Q3 accuracy of 80.7 percent and a Sov accuracy of 74.2 percent.

  14. Discovery of intramolecular signal transduction network based on a new protein dynamics model of energy dissipation.

    Directory of Open Access Journals (Sweden)

    Cheng-Wei Ma

    Full Text Available A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins.

  15. Exploring the Ligand-Protein Networks in Traditional Chinese Medicine: Current Databases, Methods, and Applications

    Directory of Open Access Journals (Sweden)

    Mingzhu Zhao

    2013-01-01

    Full Text Available The traditional Chinese medicine (TCM, which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the “multicomponent-multitarget” and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    DEFF Research Database (Denmark)

    Ehrlich, L.; Reczko, M.; Bohr, Henrik;

    1998-01-01

    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 t...... provide insight into the mutual interdependencies between the location of ordered water sites and the structural and chemical characteristics of the protein residues.......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...... structure and solvent accessibility and, using actual values of these properties, redidue hydration can be predicted to 77% accuracy with a Metthews coefficient of 0.43. However, predicted property data with an accuracy of 60-70% result in less than half the improvement in predictive performance observed...

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  20. Yeast Interacting Proteins Database: YCL032W, YLR423C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    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

  1. RRW: repeated random walks on genome-scale protein networks for local cluster discovery

    Directory of Open Access Journals (Sweden)

    Can Tolga

    2009-09-01

    Full Text Available Abstract Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL, and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters.

  2. Regulation of lifespan, metabolism, and stress responses by the Drosophila SH2B protein, Lnk.

    Directory of Open Access Journals (Sweden)

    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

  3. Fuel combustion test in constant volume combustion chamber with built-in adaptor

    Institute of Scientific and Technical Information of China (English)

    JEONG; DongSoo; CHO; GyuBack; CHOI; SuJin; LEE; JinSoo

    2010-01-01

    Combustion tests of pre-mixture of methane and air in constant volume combustion chamber(CVCC) have been carried out by means of flame propagation photo and gas pressure measurement,the effects of CVCC body temperature,intake pressure of pre-mixture of methane and air,equivalence ratio and location of the built-in adaptor have been investigated.The whole combustion chamber can be divided into two parts,i.e.the upper combustion chamber and the lower combustion chamber,by the built-in adaptor with through hole.Owing to the built-in adaptor with through hole,jet ignition or compression ignition(auto-ignition) phenomena may occur in the lower combustion chamber,which is helpful to getting higher flame propagation velocity,higher combustion peak pressure,low cycle-to-cycle variation and more stable combustion process.

  4. Multiplex matrix network analysis of protein complexes in the human TCR signalosome.

    Science.gov (United States)

    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

    2016-08-02

    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.

  5. Functional protein networks unifying limb girdle muscular dystrophy

    NARCIS (Netherlands)

    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

  6. Building and analyzing protein interactome networks by cross-species comparisons

    Directory of Open Access Journals (Sweden)

    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.

  7. Membrane tubule formation by banana-shaped proteins with or without transient network structure

    Science.gov (United States)

    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.

  8. Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn.

    Directory of Open Access Journals (Sweden)

    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.

  9. A Study on Protein Residue Contacts Prediction by Recurrent Neural Network

    Institute of Scientific and Technical Information of China (English)

    Liu Gui-xia; Zhu Yuan-xian; Zhou Wen-gang; Huang Yan-xin; Zhou Chun-guang; Wang Rong-xing

    2005-01-01

    A new method was described for using a recurrent neural network with bias units to predict contact maps in proteins.The main inputs to the neural network include residues pairwise, residue classification according to hydrophobicity, polar,acidic, basic and secondary structure information and residue separation between two residues. In our work, a dataset was used which was composed of 53 globulin proteins of known 3D structure. An average predictive accuracy of 0. 29 was obtained. Our results demonstrate the viability of the approach for predicting contact maps.

  10. Rigidity and flexibility in protein-protein interaction networks: a case study on neuromuscular disorders

    OpenAIRE

    2014-01-01

    Mutations in proteins can have deleterious effects on a protein's stability and function, which ultimately causes particular diseases. Genetically inherited muscular dystrophies (MDs) include several genetic diseases, which cause increasing weakness in muscles and disability to perform muscular functions progressively. Different types of mutations in the gene coding translates into defunct proteins cause different neuro-muscular diseases. Defunct protein interactions in human proteome may cau...

  11. Topological robustness analysis of protein interaction networks reveals key targets for overcoming chemotherapy resistance in glioma

    Science.gov (United States)

    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.

  12. ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    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

  13. HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

    Science.gov (United States)

    Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

    2015-04-01

    The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks.

  14. AtPID: the overall hierarchical functional protein interaction network interface and analytic platform for Arabidopsis.

    Science.gov (United States)

    Li, Peng; Zang, Weidong; Li, Yuhua; Xu, Feng; Wang, Jigang; Shi, Tieliu

    2011-01-01

    Protein interactions are involved in important cellular functions and biological processes that are the fundamentals of all life activities. With improvements in experimental techniques and progress in research, the overall protein interaction network frameworks of several model organisms have been created through data collection and integration. However, most of the networks processed only show simple relationships without boundary, weight or direction, which do not truly reflect the biological reality. In vivo, different types of protein interactions, such as the assembly of protein complexes or phosphorylation, often have their specific functions and qualifications. Ignorance of these features will bring much bias to the network analysis and application. Therefore, we annotate the Arabidopsis proteins in the AtPID database with further information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways. The latest updated AtPID database is available at http://www.megabionet.org/atpid/.

  15. Knowledge base and neural network approach for protein secondary structure prediction.

    Science.gov (United States)

    Patel, Maulika S; Mazumdar, Himanshu S

    2014-11-21

    Protein structure prediction is of great relevance given the abundant genomic and proteomic data generated by the genome sequencing projects. Protein secondary structure prediction is addressed as a sub task in determining the protein tertiary structure and function. In this paper, a novel algorithm, KB-PROSSP-NN, which is a combination of knowledge base and modeling of the exceptions in the knowledge base using neural networks for protein secondary structure prediction (PSSP), is proposed. The knowledge base is derived from a proteomic sequence-structure database and consists of the statistics of association between the 5-residue words and corresponding secondary structure. The predicted results obtained using knowledge base are refined with a Backpropogation neural network algorithm. Neural net models the exceptions of the knowledge base. The Q3 accuracy of 90% and 82% is achieved on the RS126 and CB396 test sets respectively which suggest improvement over existing state of art methods.

  16. The Oncogenic Palmitoyi-Protein Network in Prostate Cancer

    Science.gov (United States)

    2015-06-01

    Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions...searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments...proteins are contained in large oncosomes secreted by PCa cells and that the palmitoyl-proteome in large oncosomes is different from that in exosomes

  17. Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins

    Science.gov (United States)

    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.

  18. Supervised maximum-likelihood weighting of composite protein networks for complex prediction

    Directory of Open Access Journals (Sweden)

    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

  19. Identifying disease-specific genes based on their topological significance in protein networks

    Directory of Open Access Journals (Sweden)

    Cherba David

    2009-03-01

    Full Text Available Abstract Background The identification of key target nodes within complex molecular networks remains a common objective in scientific research. The results of pathway analyses are usually sets of fairly complex networks or functional processes that are deemed relevant to the condition represented by the molecular profile. To be useful in a research or clinical laboratory, the results need to be translated to the level of testable hypotheses about individual genes and proteins within the condition of interest. Results In this paper we describe novel computational methodology capable of predicting key regulatory genes and proteins in disease- and condition-specific biological networks. The algorithm builds shortest path network connecting condition-specific genes (e.g. differentially expressed genes using global database of protein interactions from MetaCore. We evaluate the number of all paths traversing each node in the shortest path network in relation to the total number of paths going via the same node in the global network. Using these numbers and the relative size of the initial data set, we determine the statistical significance of the network connectivity provided through each node. We applied this method to gene expression data from psoriasis patients and identified many confirmed biological targets of psoriasis and suggested several new targets. Using predicted regulatory nodes we were able to reconstruct disease pathways that are in excellent agreement with the current knowledge on the pathogenesis of psoriasis. Conclusion The systematic and automated approach described in this paper is readily applicable to uncovering high-quality therapeutic targets, and holds great promise for developing network-based combinational treatment strategies for a wide range of diseases.

  20. A multilayer protein-protein interaction network analysis of different life stages in Caenorhabditis elegans

    Science.gov (United States)

    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.

  1. A network model to investigate structural and electrical properties of proteins

    CERN Document Server

    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...

  2. Integration of relational and hierarchical network information for protein function prediction

    Directory of Open Access Journals (Sweden)

    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

  3. Proteomic dissection of biological pathways/processes through profiling protein-protein interaction networks

    Institute of Scientific and Technical Information of China (English)

    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.

  4. Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins

    Directory of Open Access Journals (Sweden)

    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.

  5. The effect of oil type on network formation by protein aggregates into oleogels

    NARCIS (Netherlands)

    Vries, de Auke; Lopez Gomez, Yuly; Linden, van der Erik; Scholten, Elke

    2017-01-01

    The aim of this study was to assess the effect of oil type on the network formation of heat-set protein aggregates in liquid oil. The gelling properties of such aggregates to structure oil into so-called ‘oleogels’ are related to both the particle-particle and particle-solvent interactions. To ch

  6. Critical controllability in proteome-wide protein interaction network integrating transcriptome

    Science.gov (United States)

    Ishitsuka, Masayuki; Akutsu, Tatsuya; Nacher, Jose C.

    2016-04-01

    Recently, the number of essential gene entries has considerably increased. However, little is known about the relationships between essential genes and their functional roles in critical network control at both the structural (protein interaction network) and dynamic (transcriptional) levels, in part because the large size of the network prevents extensive computational analysis. Here, we present an algorithm that identifies the critical control set of nodes by reducing the computational time by 180 times and by expanding the computable network size up to 25 times, from 1,000 to 25,000 nodes. The developed algorithm allows a critical controllability analysis of large integrated systems composed of a transcriptome- and proteome-wide protein interaction network for the first time. The data-driven analysis captures a direct triad association of the structural controllability of genes, lethality and dynamic synchronization of co-expression. We believe that the identified optimized critical network control subsets may be of interest as drug targets; thus, they may be useful for drug design and development.

  7. Critical controllability in proteome-wide protein interaction network integrating transcriptome.

    Science.gov (United States)

    Ishitsuka, Masayuki; Akutsu, Tatsuya; Nacher, Jose C

    2016-04-04

    Recently, the number of essential gene entries has considerably increased. However, little is known about the relationships between essential genes and their functional roles in critical network control at both the structural (protein interaction network) and dynamic (transcriptional) levels, in part because the large size of the network prevents extensive computational analysis. Here, we present an algorithm that identifies the critical control set of nodes by reducing the computational time by 180 times and by expanding the computable network size up to 25 times, from 1,000 to 25,000 nodes. The developed algorithm allows a critical controllability analysis of large integrated systems composed of a transcriptome- and proteome-wide protein interaction network for the first time. The data-driven analysis captures a direct triad association of the structural controllability of genes, lethality and dynamic synchronization of co-expression. We believe that the identified optimized critical network control subsets may be of interest as drug targets; thus, they may be useful for drug design and development.

  8. Enhancing the prioritization of disease-causing genes through tissue specific protein interaction networks.

    Directory of Open Access Journals (Sweden)

    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.

  9. Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism.

    Science.gov (United States)

    Corominas, Roser; Yang, Xinping; Lin, Guan Ning; Kang, Shuli; Shen, Yun; Ghamsari, Lila; Broly, Martin; Rodriguez, Maria; Tam, Stanley; Trigg, Shelly A; Fan, Changyu; Yi, Song; Tasan, Murat; Lemmens, Irma; Kuang, Xingyan; Zhao, Nan; Malhotra, Dheeraj; Michaelson, Jacob J; Vacic, Vladimir; Calderwood, Michael A; Roth, Frederick P; Tavernier, Jan; Horvath, Steve; Salehi-Ashtiani, Kourosh; Korkin, Dmitry; Sebat, Jonathan; Hill, David E; Hao, Tong; Vidal, Marc; Iakoucheva, Lilia M

    2014-04-11

    Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.

  10. Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

    Science.gov (United States)

    Al-Anzi, Bader; Arpp, Patrick; Gerges, Sherif; Ormerod, Christopher; Olsman, Noah; Zinn, Kai

    2015-05-01

    An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

  11. Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

    Directory of Open Access Journals (Sweden)

    Bader Al-Anzi

    2015-05-01

    Full Text Available An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae. A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

  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)

    DEFF Research Database (Denmark)

    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....... sequestration through interactions, mainly with the C-terminal intracellular tails of the receptors. A library of tails from 59 representative members of the super family of seven-transmembrane receptors was probed as glutathione S-transferase fusion proteins for interactions with four different adaptor...

  13. Using sequence similarity networks for visualization of relationships across diverse protein superfamilies.

    Directory of Open Access Journals (Sweden)

    Holly J Atkinson

    Full Text Available The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.

  14. Elastic network model of allosteric regulation in protein kinase PDK1

    Directory of Open Access Journals (Sweden)

    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.

  15. Salivary Defense Proteins: Their Network and Role in Innate and Acquired Oral Immunity

    Directory of Open Access Journals (Sweden)

    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.

  16. Prioritizing cancer-related genes with aberrant methylation based on a weighted protein-protein interaction network

    Directory of Open Access Journals (Sweden)

    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

  17. Scalable rule-based modelling of allosteric proteins and biochemical networks.

    Directory of Open Access Journals (Sweden)

    Julien F Ollivier

    Full Text Available Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

  18. Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

    Science.gov (United States)

    Chai, H; Huang, H H; Jiang, H K; Liang, Y; Xia, L Y

    2016-07-25

    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.

  19. The G protein-coupled receptor heterodimer network (GPCR-HetNet) and its hub components.

    Science.gov (United States)

    Borroto-Escuela, Dasiel O; Brito, Ismel; Romero-Fernandez, Wilber; Di Palma, Michael; Oflijan, Julia; Skieterska, Kamila; Duchou, Jolien; Van Craenenbroeck, Kathleen; Suárez-Boomgaard, Diana; Rivera, Alicia; Guidolin, Diego; Agnati, Luigi F; Fuxe, Kjell

    2014-05-14

    G protein-coupled receptors (GPCRs) oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.

  20. The G Protein-Coupled Receptor Heterodimer Network (GPCR-HetNet and Its Hub Components

    Directory of Open Access Journals (Sweden)

    Dasiel O. Borroto-Escuela

    2014-05-01

    Full Text Available G protein-coupled receptors (GPCRs oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.

  1. POINeT: protein interactome with sub-network analysis and hub prioritization

    Directory of Open Access Journals (Sweden)

    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

  2. Transport vesicle tethering at the trans Golgi network: coiled coil proteins in action

    Directory of Open Access Journals (Sweden)

    Pak-yan Patricia Cheung

    2016-03-01

    Full Text Available The Golgi complex is decorated with so-called Golgin proteins that share a common feature: a large proportion of their amino acid sequences are predicted to form coiled-coil structures. The possible presence of extensive coiled coils implies that these proteins are highly elongated molecules that can extend a significant distance from the Golgi surface. This property would help them to capture or trap inbound transport vesicles and to tether Golgi mini-stacks together. This review will summarize our current understanding of coiled coil tethers that are needed for the receipt of transport vesicles at the trans Golgi network. How do long tethering proteins actually catch vesicles? Golgi-associated, coiled coil tethers contain numerous binding sites for small GTPases, SNARE proteins, and vesicle coat proteins. How are these interactions coordinated and are any or all of them important for the tethering process? Progress towards understanding these questions and remaining, unresolved mysteries will be discussed.

  3. Protein sequence for clustering DNA based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Gamal. F. Elhadi

    2012-01-01

    Full Text Available DNA is a nucleic acid that contains the genetic instructions used in the development and functioning of all known living organisms and some viruses. Clustering is a process that groups a set of objects into clusters so that the similarity among objects in the same cluster is high, while that among the objects in different clusters is low. In this paper, we proposed an approach for clustering DNA sequences using Self-Organizing Map (SOM algorithm and Protein Sequence. The main objective is to analyze biological data and to bunch DNA to many clusters more easily and efficiently. We use the proposed approach to analyze both large and small amount of input DNA sequences. The results show that the similarity of the sequences does not depend on the amount of input sequences. Our approach depends on evaluating the degree of the DNA sequences similarity using the hierarchal representation Dendrogram. Representing large amount of data using hierarchal tree gives the ability to compare large sequences efficiently

  4. Local network topology in human protein interaction data predicts functional association.

    Directory of Open Access Journals (Sweden)

    Hua Li

    Full Text Available The use of high-throughput techniques to generate large volumes of protein-protein interaction (PPI data has increased the need for methods that systematically and automatically suggest functional relationships among proteins. In a yeast PPI network, previous work has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional association. In this study we improved the prediction scheme by developing a new algorithm and applied it on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting function-associated protein pairs. We used the annotations of the Gene Ontology (GO and the Kyoto Encyclopedia of Genes and Genomes (KEGG as benchmarks to compare and evaluate the function relevance. The application of our algorithms to human PPI data yielded 4,233 significant functional associations among 1,754 proteins. Further functional comparisons between them allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made functional inferences from detailed analysis on one subcluster highly enriched in the TGF-beta signaling pathway (P<10(-50. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotation in this post-genomic era.

  5. Getting to the Edge: Protein dynamical networks as a new frontier in plant-microbe interactions

    Directory of Open Access Journals (Sweden)

    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.

  6. EAT-2, a SAP-like adaptor, controls NK cell activation through phospholipase Cγ, Ca++, and Erk, leading to granule polarization.

    Science.gov (United States)

    Pérez-Quintero, Luis-Alberto; Roncagalli, Romain; Guo, Huaijian; Latour, Sylvain; Davidson, Dominique; Veillette, André

    2014-04-07

    Ewing's sarcoma-associated transcript 2 (EAT-2) is an Src homology 2 domain-containing intracellular adaptor related to signaling lymphocytic activation molecule (SLAM)-associated protein (SAP), the X-linked lymphoproliferative gene product. Both EAT-2 and SAP are expressed in natural killer (NK) cells, and their combined expression is essential for NK cells to kill abnormal hematopoietic cells. SAP mediates this function by coupling SLAM family receptors to the protein tyrosine kinase Fyn and the exchange factor Vav, thereby promoting conjugate formation between NK cells and target cells. We used a variety of genetic, biochemical, and imaging approaches to define the molecular and cellular mechanisms by which EAT-2 controls NK cell activation. We found that EAT-2 mediates its effects in NK cells by linking SLAM family receptors to phospholipase Cγ, calcium fluxes, and Erk kinase. These signals are triggered by one or two tyrosines located in the carboxyl-terminal tail of EAT-2 but not found in SAP. Unlike SAP, EAT-2 does not enhance conjugate formation. Rather, it accelerates polarization and exocytosis of cytotoxic granules toward hematopoietic target cells. Hence, EAT-2 promotes NK cell activation by molecular and cellular mechanisms distinct from those of SAP. These findings explain the cooperative and essential function of these two adaptors in NK cell activation.

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

    DEFF Research Database (Denmark)

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

    1997-01-01

    Several receptors are downregulated by internalization after ligand binding. Regulation of T cell receptor (TCR) expression is an important step in T cell activation, desensitization, and tolerance induction. One way T cells regulate TCR expression is by phosphorylation/dephosphorylation of the TCR...

  8. Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

    LENUS (Irish Health Repository)

    Casey, Fergal

    2011-08-22

    Abstract Background Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks. Results We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter. Conclusion We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.

  9. Intrinsic Disorder in Male Sex Determination: Disorderedness of Proteins from the Sry Transcriptional Network.

    Science.gov (United States)

    Merone, Jean; Nwogu, Onyekahi; Redington, Jennifer M; Uversky, Vladimir N

    2016-10-28

    Sex differentiation is a complex process where sexually indifferent embryo progressively acquires male or female characteristics via tightly controlled, perfectly timed, and sophisticatedly intertwined chain of events. This process is controlled and regulated by a set of specific proteins, with one of the first steps in sex differentiation being the activation of the Y-chromosomal Sry gene (sex-determining region Y) in males that acts as a switch from undifferentiated gonad somatic cells to testis development. There are several key players in this process, which constitute the Sry transcriptional network, and collective action of which governs testis determination. Although it is accepted now that many proteins engaged in signal transduction as well as regulation and control of various biological processes are intrinsically disordered (i.e., do not have unique structure and remain unstructured, or incompletely structured, under physiological conditions), the roles and profusion of intrinsic disorder in proteins involved in the male sex determination have not been accessed as of yet. The goal of this study is to cover this gap by analyzing some key players of the Sry transcriptional network. To this end, we employed a broad set of computational tools for intrinsic disorder analysis and conducted intensive literature search in order to gain information on the structural peculiarities of the Sry network-related proteins, their intrinsic disorder predispositions, and the roles of intrinsic disorder in their functions.

  10. A mathematical model for generating bipartite graphs and its application to protein networks

    Energy Technology Data Exchange (ETDEWEB)

    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.

  11. The intriguing realm of protein biogenesis: Facing the green co-translational protein maturation networks.

    Science.gov (United States)

    Breiman, Adina; Fieulaine, Sonia; Meinnel, Thierry; Giglione, Carmela

    2016-05-01

    The ribosome is the cell's protein-making factory, a huge protein-RNA complex, that is essential to life. Determining the high-resolution structures of the stable "core" of this factory was among the major breakthroughs of the past decades, and was awarded the Nobel Prize in 2009. Now that the mysteries of the ribosome appear to be more traceable, detailed understanding of the mechanisms that regulate protein synthesis includes not only the well-known steps of initiation, elongation, and termination but also the less comprehended features of the co-translational events associated with the maturation of the nascent chains. The ribosome is a platform for co-translational events affecting the nascent polypeptide, including protein modifications, folding, targeting to various cellular compartments for integration into membrane or translocation, and proteolysis. These events are orchestrated by ribosome-associated protein biogenesis factors (RPBs), a group of a dozen or more factors that act as the "welcoming committee" for the nascent chain as it emerges from the ribosome. In plants these factors have evolved to fit the specificity of different cellular compartments: cytoplasm, mitochondria and chloroplast. This review focuses on the current state of knowledge of these factors and their interaction around the exit tunnel of dedicated ribosomes. Particular attention has been accorded to the plant system, highlighting the similarities and differences with other organisms.

  12. Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

    Directory of Open Access Journals (Sweden)

    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

  13. TMBETADISC-RBF: Discrimination of beta-barrel membrane proteins using RBF networks and PSSM profiles.

    Science.gov (United States)

    Ou, Yu-Yen; Gromiha, M Michael; Chen, Shu-An; Suwa, Makiko

    2008-06-01

    Discriminating outer membrane proteins (OMPs) from other folding types of globular and membrane proteins is an important task both for identifying OMPs from genomic sequences and for the successful prediction of their secondary and tertiary structures. We have developed a method based on radial basis function networks and position specific scoring matrix (PSSM) profiles generated by PSI-BLAST and non-redundant protein database. Our approach with PSSM profiles has correctly predicted the OMPs with a cross-validated accuracy of 96.4% in a set of 1251 proteins, which contain 206 OMPs, 667 globular proteins and 378 alpha-helical inner membrane proteins. Furthermore, we applied our method on a dataset containing 114 OMPs, 187 TMH proteins and 195 globular proteins obtained with less than 20% sequence identity and obtained the cross-validated accuracy of 95%. This accuracy of discriminating OMPs is higher than other methods in the literature and our method could be used as an effective tool for dissecting OMPs from genomic sequences. We have developed a prediction server, TMBETADISC-RBF, which is available at http://rbf.bioinfo.tw/~sachen/OMP.html.

  14. RNA regulatory networks diversified through curvature of the PUF protein scaffold.

    Science.gov (United States)

    Wilinski, Daniel; Qiu, Chen; Lapointe, Christopher P; Nevil, Markus; Campbell, Zachary T; Tanaka Hall, Traci M; Wickens, Marvin

    2015-09-14

    Proteins bind and control mRNAs, directing their localization, translation and stability. Members of the PUF family of RNA-binding proteins control multiple mRNAs in a single cell, and play key roles in development, stem cell maintenance and memory formation. Here we identified the mRNA targets of a S. cerevisiae PUF protein, Puf5p, by ultraviolet-crosslinking-affinity purification and high-throughput sequencing (HITS-CLIP). The binding sites recognized by Puf5p are diverse, with variable spacer lengths between two specific sequences. Each length of site correlates with a distinct biological function. Crystal structures of Puf5p-RNA complexes reveal that the protein scaffold presents an exceptionally flat and extended interaction surface relative to other PUF proteins. In complexes with RNAs of different lengths, the protein is unchanged. A single PUF protein repeat is sufficient to induce broadening of specificity. Changes in protein architecture, such as alterations in curvature, may lead to evolution of mRNA regulatory networks.

  15. Functional equivalency inferred from "authoritative sources" in networks of homologous proteins.

    Directory of Open Access Journals (Sweden)

    Shreedhar Natarajan

    Full Text Available A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods.

  16. Adhesion protein networks reveal functions proximal and distal to cell-matrix contacts.

    Science.gov (United States)

    Byron, Adam; Frame, Margaret C

    2016-04-01

    Cell adhesion to the extracellular matrix is generally mediated by integrin receptors, which bind to intracellular adhesion proteins that form multi-molecular scaffolding and signalling complexes. The networks of proteins, and their interactions, are dynamic, mechanosensitive and extremely complex. Recent efforts to characterise adhesions using a variety of technologies, including imaging, proteomics and bioinformatics, have provided new insights into their composition, organisation and how they are regulated, and have also begun to reveal unexpected roles for so-called adhesion proteins in other cellular compartments (for example, the nucleus or centrosomes) in diseases such as cancer. We believe this is opening a new chapter on understanding the wider functions of adhesion proteins, both proximal and distal to cell-matrix contacts.

  17. Hybridization characteristics of biomolecular adaptors, covalent DNA streptavidin conjugates

    NARCIS (Netherlands)

    Niemeyer, CM; Burger, W; Hoedemakers, RMJ

    1998-01-01

    Semisynthetic, covalent streptavidin-DNA adducts are versatile molecular connectors for the fabrication of both nano-and microstructured protein arrays by use of DNA hybridization. In this study, the hybridization characteristics of six adduct species, each containing a different DNA sequence of 21

  18. k-Partite cliques of protein interactions: A novel subgraph topology for functional coherence analysis on PPI networks.

    Science.gov (United States)

    Liu, Qian; Chen, Yi-Ping Phoebe; Li, Jinyan

    2014-01-07

    Many studies are aimed at identifying dense clusters/subgraphs from protein-protein interaction (PPI) networks for protein function prediction. However, the prediction performance based on the dense clusters is actually worse than a simple guilt-by-association method using neighbor counting ideas. This indicates that the local topological structures and properties of PPI networks are still open to new theoretical investigation and empirical exploration. We introduce a novel topological structure called k-partite cliques of protein interactions-a functionally coherent but not-necessarily dense subgraph topology in PPI networks-to study PPI networks. A k-partite protein clique is a maximal k-partite clique comprising two or more nonoverlapping protein subsets between any two of which full interactions are exhibited. In the detection of PPI's maximal k-partite cliques, we propose to transform PPI networks into induced K-partite graphs where edges exist only between the partites. Then, we present a maximal k-partite clique mining (MaCMik) algorithm to enumerate maximal k-partite cliques from K-partite graphs. Our MaCMik algorithm is then applied to a yeast PPI network. We observed interesting and unusually high functional coherence in k-partite protein cliques-the majority of the proteins in k-partite protein cliques, especially those in the same partites, share the same functions, although k-partite protein cliques are not restricted to be dense compared with dense subgraph patterns or (quasi-)cliques. The idea of k-partite protein cliques provides a novel approach of characterizing PPI networks, and so it will help function prediction for unknown proteins.

  19. The Interactorium: visualising proteins, complexes and interaction networks in a virtual 3-D cell.

    Science.gov (United States)

    Widjaja, Yose Y; Pang, Chi Nam Ignatius; Li, Simone S; Wilkins, Marc R; Lambert, Tim D

    2009-12-01

    Here, we describe the Interactorium, a tool in which a Virtual Cell is used as the context for the seamless visualisation of the yeast