Prediction of enzyme function by combining sequence similarity and protein interactions
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Updated: Jul 5, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Jordi Espadaler1, Narayanan Eswar, Enrique Querol
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
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.
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