期刊
FEBS LETTERS
卷 544, 期 1-3, 页码 236-239出版社
WILEY
DOI: 10.1016/S0014-5793(03)00456-3
关键词
protein-protein interaction; neural network; data mining; sequence analysis; protein function; protein structure; bioinformatics
资金
- NIGMS NIH HHS [R01-GM63029-01, 1-P50-GM62413-01] Funding Source: Medline
Protein-protein interactions are facilitated by a myriad of residue-residue contacts on the interacting proteins. Identifying the site of interaction in the protein is a key for deciphering its functional mechanisms, and is crucial for drug development. Many studies indicate that the compositions of contacting residues are unique. Here, we describe a neural network that identifies protein-protein interfaces from sequence. For the most strongly predicted sites (in 34 of 333 proteins), 94% of the predictions were confirmed experimentally. When 70% of our predictions were right, we correctly predicted at least one interaction site in 20% of the complexes (66/333). These results indicate that the prediction of some interaction sites from sequence alone is possible. Incorporating evolutionary and predicted structural information may improve our method. However, even at this early stage, our tool might already assist wet-lab biology. (C) 2003 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.
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