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Prediction of protein interaction sites from sequence profile and residue neighbor list
Author(s) -
Zhou HuanXiang,
Shan Yibing
Publication year - 2001
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.1099
Subject(s) - chemistry , sequence (biology) , solvent exposure , protein structure , protein sequencing , protein structure prediction , residue (chemistry) , crystallography , solvent , biological system , peptide sequence , biochemistry , biology , gene
Protein–protein interaction sites are predicted from a neural network with sequence profiles of neighboring residues and solvent exposure as input. The network was trained on 615 pairs of nonhomologous complex‐forming proteins. Tested on a different set of 129 pairs of nonhomologous complex‐forming proteins, 70% of the 11,004 predicted interface residues are actually located in the interfaces. These 7732 correctly predicted residues account for 65% of the 11,805 residues making up the 129 interfaces. The main strength of the network predictor lies in the fact that neighbor lists and solvent exposure are relatively insensitive to structural changes accompanying complex formation. As such, it performs equally well with bound or unbound structures of the proteins. For a set of 35 test proteins, when the input was calculated from the bound and unbound structures, the correct fractions of the predicted interface residues were 69 and 70%, respectively. Proteins 2001;44:336–343. © 2001 Wiley‐Liss, Inc.