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Web Tools for Predicting Metal Binding Sites in Proteins
Author(s) -
Sobolev Vladimir,
Edelman Marvin
Publication year - 2013
Publication title -
israel journal of chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.908
H-Index - 54
eISSN - 1869-5868
pISSN - 0021-2148
DOI - 10.1002/ijch.201200084
Subject(s) - chemistry , computational biology , binding site , single nucleotide polymorphism , protein function , metal , gene , biochemistry , genotype , biology , organic chemistry
Abstract Approximately one third of proteins bind metal ions for stability and/or enzymatic function. However, on a structural level, only a small fraction of binding sites have been resolved. Metal binding site predictions can serve as a first step in putative function assignment for many unannotated proteins. Sequence based and structure based methods for metal binding site predictions are reviewed here. The CHED and SeqCHED methods of prediction from apo protein structures and translated gene sequences, respectively, are described in detail, including their web server applications. The relevance of SeqCHED to the analysis of single nucleotide polymorphisms (SNPs) associated with disease related metal binding sites is illustrated.