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Prediction of enzyme function by combining sequence similarity and protein interactions
Espadaler, Jordi; Eswar, Narayanan; Querol, Enrique; Avilés, Francesc Xavier; Sali, Andrej; Martí Renom, Marc A.; Oliva, Baldomero
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.
02-07-2013
Interaccions proteïna-proteïna
Proteïnes -- Anàlisi
(c) 2008 Espadaler et al. Creative Commons Attribution License
http://creativecommons.org/licenses/by/2.0/
Artículo
info:eu-repo/semantics/publishedVersion
BioMed Central
         

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