Prediction of enzyme function by combining sequence similarity and protein interactions

TitlePrediction of enzyme function by combining sequence similarity and protein interactions
Publication TypeJournal Article
Year of Publication2008
AuthorsEspadaler, J, Eswar, N, Querol, E, Aviles, FX, Sali, A, Marti-Renom, MA, Oliva, B
JournalBMC Bioinformatics
KeywordsAmino Acid *Software Structure-Activity Relationship Substrate Specificity/genetics; Amino Acid Sequence/physiology Databases; Automated Predictive Value of Tests Protein Interaction Mapping Proteins/analysis/metabolism Sequence Alignment Sequence Analysis; Protein *Sequence Homology; Protein Enzymes/analysis/*metabolism Fuzzy Logic Pattern Recognition

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.


Espadaler, Jordi Eswar, Narayanan Querol, Enrique Aviles, Francesc X Sali, Andrej Marti-Renom, Marc A Oliva, Baldomero GM54762/GM/NIGMS NIH HHS/United States GM71790/GM/NIGMS NIH HHS/United States GM74929/GM/NIGMS NIH HHS/United States GM74945/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov’t England BMC bioinformatics BMC Bioinformatics. 2008 May 27;9:249.