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Prediction of enzyme function by combining sequence similarity and protein interactions

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dc.contributor.author Espadaler, Jordi
dc.contributor.author Eswar, Narayanan
dc.contributor.author Querol, Enrique
dc.contributor.author Avilés, Francesc Xavier
dc.contributor.author Sali, Andrej
dc.contributor.author Martí Renom, Marc A.
dc.contributor.author Oliva Miguel, Baldomero
dc.date.accessioned 2012-05-09T08:42:56Z
dc.date.available 2012-05-09T08:42:56Z
dc.date.issued 2008
dc.identifier.citation Espadaler J, Eswar N, Querol E, Avilés FX, Sali A, Marti-Renom MA, Oliva B. Prediction of enzyme function by combining sequence similarity and protein interactions. BMC Bioinformatics. 2008;9:249. DOI: 10.1186/1471-2105-9-249
dc.identifier.issn 1471-2105
dc.identifier.uri http://hdl.handle.net/10230/16432
dc.description.abstract Background: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. Results: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST. Conclusion: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.
dc.description.sponsorship JE was supported by predoctoral fellowship from the Generalitat de Catalunya and CERBA (Spain). EQ acknowledges grants from the Spanish Ministerio de Educación y Ciencia (BIO2007-67904-C02-01). FXA acknowledges grants from the Spanish Ministerio de Educación y Ciencia (BIO2007-68046). AS acknowledges the financial support by the Sandler Family Supporting Foundation, IBM, HP, Netapps, and Intel for hardware gifts, and NIH grants GM74945, GM74929, GM71790, and GM54762. MAM-R acknowledges support from the Spanish Ministerio de Educación y Ciencia (BIO2007-66670). BO acknowledges grants from Generalitat de Catalunya (CIDEM), Spanish Ministerio de Educación y Ciencia (MEC BIO2005-00533 and PROFIT PSE-010000-2007-1) and by European Union INFOBIOMED-NoE (IST-507585) and @NEURIST (IST-2004-027703)
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher BioMed Central
dc.relation.ispartof BMC Bioinformatics. 2008;9:249
dc.rights © 2008 Espadaler et al. Creative Commons Attribution License
dc.rights.uri http://creativecommons.org/licenses/by/2.0/
dc.subject.other Interaccions proteïna-proteïna
dc.subject.other Proteïnes -- Anàlisi
dc.title Prediction of enzyme function by combining sequence similarity and protein interactions
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1186/1471-2105-9-249
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PN/BIO2007-67904-C02-01
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PN/BIO2007-68046
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PN/BIO2007-66670
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP6/507585
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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