Bayesian Modeling of the Yeast SH3 Domain Interactome Predicts Spatiotemporal Dynamics of Endocytosis Proteins

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Bayesian Modeling of the Yeast SH3 Domain Interactome Predicts Spatiotemporal Dynamics of Endocytosis Proteins

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dc.contributor.author Tonikian, Raffi
dc.contributor.author Xin, Xiaofeng
dc.contributor.author Toret, Christopher P.
dc.contributor.author Gfeller, David
dc.contributor.author Landgraf, Christiane
dc.contributor.author Panni, Simona
dc.contributor.author Paoluzi, Serena
dc.contributor.author Castagnoli, Luisa
dc.contributor.author Currell, Bridget
dc.contributor.author Seshagiri, Somasekar
dc.contributor.author Winsor, Barbara
dc.contributor.author Gerstein, Mark B.
dc.contributor.author Bader, Gary D.
dc.contributor.author Volkmer, Rudolf
dc.contributor.author Cesareni, Gianni
dc.contributor.author Drubin, David G.
dc.contributor.author Kim, Philip M.
dc.contributor.author Sidhu, Sachdev S.
dc.contributor.author Boone, Charles
dc.contributor.author Yu, Haiyuan
dc.contributor.author Vidal, Marc
dc.date.accessioned 2011-04-17T04:43:40Z
dc.date.issued 2009
dc.identifier.citation Tonikian, Raffi, Xiaofeng Xin, Christopher P. Toret, David Gfeller, Christiane Landgraf, Simona Panni, Serena Paoluzi, et al. 2009. Bayesian modeling of the yeast SH3 domain interactome predicts spatiotemporal dynamics of endocytosis proteins. PLoS Biology 7(10): e1000218. en_US
dc.identifier.issn 1544-9173 en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:4853387
dc.description.abstract SH3 domains are peptide recognition modules that mediate the assembly of diverse biological complexes. We scanned billions of phage-displayed peptides to map the binding specificities of the SH3 domain family in the budding yeast, Saccharomyces cerevisiae. Although most of the SH3 domains fall into the canonical classes I and II, each domain utilizes distinct features of its cognate ligands to achieve binding selectivity. Furthermore, we uncovered several SH3 domains with specificity profiles that clearly deviate from the two canonical classes. In conjunction with phage display, we used yeast twohybrid and peptide array screening to independently identify SH3 domain binding partners. The results from the three complementary techniques were integrated using a Bayesian algorithm to generate a high-confidence yeast SH3 domain interaction map. The interaction map was enriched for proteins involved in endocytosis, revealing a set of SH3-mediated interactions that underlie formation of protein complexes essential to this biological pathway. We used the SH3 domain interaction network to predict the dynamic localization of several previously uncharacterized endocytic proteins, and our analysis suggests a novel role for the SH3 domains of Lsb3p and Lsb4p as hubs that recruit and assemble several endocytic complexes. en_US
dc.language.iso en_US en_US
dc.publisher Public Library of Science en_US
dc.relation.isversionof doi:10.1371/journal.pbio.1000218 en_US
dc.relation.hasversion http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2756588/pdf/ en_US
dash.license LAA
dc.title Bayesian Modeling of the Yeast SH3 Domain Interactome Predicts Spatiotemporal Dynamics of Endocytosis Proteins en_US
dc.type Journal Article en_US
dc.description.version Version of Record en_US
dc.relation.journal PLoS Biology en_US
dash.depositing.author Yu, Haiyuan
dc.date.available 2011-04-17T04:43:40Z
dash.affiliation.other HMS^Genetics en_US
dash.affiliation.other HMS^Genetics en_US

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