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Prediction of disulfide connectivity from protein sequences
Author(s) -
Chen YuChing,
Hwang JennKang
Publication year - 2005
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.20627
Subject(s) - disulfide bond , sequence (biology) , cysteine , computational biology , chemistry , peptide sequence , protein sequencing , computer science , biochemistry , biology , gene , enzyme
The difficulties in predicting disulfide connectivity from protein sequences lie in the nonlocal properties of the disulfide bridges that involve cysteine pairs at large sequence separation. Though some progress has been recently made in the prediction of disulfide connectivity, the current methods predict less than half of the disulfide patterns for the data set sharing less than 30% sequence identity. In this report, we use the support vector machines based on sequence features such as the coupling between the local sequence environments of cysteine pair, the cysteines sequence separations, and the global sequence descriptor, such as amino acid content. Our approach is able to predict 55% of the disulfide patterns of proteins with two to five disulfide bridges, which is 11–26% higher than other methods in the literature. Proteins 2005. © 2005 Wiley‐Liss, Inc.