Structural characterization of proteins using residue environments.
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.
Mooney
Sean D
SD
Department of Genetics, Stanford University, Stanford, California, USA. sdmooney@iupui.edu
Liang
Mike Hsin-Ping
MH
DeConde
Rob
R
Altman
Russ B
RB
D000596:Amino Acids / Q000737:chemistry*; D019295:Computational Biology; D030562:Databases, Protein; D007700:Kinetics; D008958:Models, Molecular; D015394:Molecular Structure; D011487:Protein Conformation; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*
D000596:Amino Acids; D011506:Proteins