Prediction of enzyme function by combining sequence similarity and protein interactions

• Main Authors: Sali Andrej, Avilés Francesc X, Querol Enrique, Eswar Narayanan, Espadaler Jordi, Marti-Renom Marc A, Oliva Baldomero
• Format: Article
• Language: English
• Published: BMC 2008-05-01
• Series: BMC Bioinformatics
• Online Access: http://www.biomedcentral.com/1471-2105/9/249

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p>