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BMC Bioinformatics. 2008 May 27;9:249. doi: 10.1186/1471-2105-9-249.

Prediction of enzyme function by combining sequence similarity and protein interactions.

Author information

  • 1Laboratori de Bioinformàtica Estructural (GRIB), Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra-IMIM, 08003-Barcelona, Catalonia, Spain. wisl@bioinf.uab.es

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.

PMID:
18505562
PMCID:
PMC2430716
DOI:
10.1186/1471-2105-9-249
[PubMed - indexed for MEDLINE]
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