Prediction of enzyme function by combining sequence similarity and protein interactions


Autoria(s): Espadaler, Jordi; Eswar, Narayanan; Querol, Enrique; Avilés, Francesc Xavier; Sali, Andrej; Martí Renom, Marc A.; Oliva, Baldomero
Data(s)

02/07/2013

Resumo

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.

Identificador

http://hdl.handle.net/10230/16432

Idioma(s)

eng

Publicador

BioMed Central

Direitos

(c) 2008 Espadaler et al. Creative Commons Attribution License

info:eu-repo/semantics/openAccess

<a href="http://creativecommons.org/licenses/by/2.0/">http://creativecommons.org/licenses/by/2.0/</a>

Palavras-Chave #Interaccions proteïna-proteïna #Proteïnes -- Anàlisi
Tipo

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion