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Predicted protein–protein interaction sites from local sequence information
Author(s) -
Ofran Yanay,
Rost Burkhard
Publication year - 2003
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1016/s0014-5793(03)00456-3
Subject(s) - sequence (biology) , protein–protein interaction , computational biology , protein sequencing , protein structure , interaction network , residue (chemistry) , chemistry , biology , peptide sequence , biophysics , biochemistry , gene
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.