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Structural characterization of proteins using residue environments
Author(s) -
Mooney Sean D.,
Liang Mike HsinPing,
DeConde Rob,
Altman Russ B.
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.20661
Subject(s) - protein data bank (rcsb pdb) , structural genomics , protein data bank , protein structure , amino acid , computational biology , amino acid residue , computer science , protein structure database , peptide sequence , k nearest neighbors algorithm , characterization (materials science) , structural classification of proteins database , chemistry , biology , artificial intelligence , biochemistry , gene , sequence database , materials science , nanotechnology
A primary challenge for structural genomics is the automated functional characterization of protein structures. We have developed a sequence‐independent method called S‐BLEST (Structure‐Based Local Environment Search Tool) for the annotation of previously uncharacterized protein structures. S‐BLEST encodes the local environment of an amino acid as a vector of structural property values. It has been applied to all amino acids in a nonredundant database of protein structures to generate a searchable structural resource. Given a query amino acid from an experimentally determined or modeled structure, S‐BLEST quickly identifies similar amino acid environments using a K‐nearest neighbor search. In addition, the method gives an estimation of the statistical significance of each result. We validated S‐BLEST on X‐ray crystal structures from the ASTRAL 40 nonredundant dataset. We then applied it to 86 crystallographically determined proteins in the protein data bank (PDB) with unknown function and with no significant sequence neighbors in the PDB. S‐BLEST was able to associate 20 proteins with at least one local structural neighbor and identify the amino acid environments that are most similar between those neighbors. Proteins 2005. © 2005 Wiley‐Liss, Inc.