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Bioinformatics. 2001 May;17(5):455-60.

Predicting protein--protein interactions from primary structure.

Author information

  • 1Department of Bioengineering, 9500 Gilman Drive, University of California, San Diego, La Jolla, CA 92093-0412, USA.

Abstract

MOTIVATION:

An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. The expectation is that this will provide a fuller appreciation of cellular processes and networks at the protein level, ultimately leading to a better understanding of disease mechanisms and suggesting new means for intervention. This paper addresses the question: can protein-protein interactions be predicted directly from primary structure and associated data? Using a diverse database of known protein interactions, a Support Vector Machine (SVM) learning system was trained to recognize and predict interactions based solely on primary structure and associated physicochemical properties.

RESULTS:

Inductive accuracy of the trained system, defined here as the percentage of correct protein interaction predictions for previously unseen test sets, averaged 80% for the ensemble of statistical experiments. Future proteomics studies may benefit from this research by proceeding directly from the automated identification of a cell's gene products to prediction of protein interaction pairs.

PMID:
11331240
[PubMed - indexed for MEDLINE]
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