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Potential for assessing quality of protein structure based on contact number prediction
Author(s) -
Ishida Takashi,
Nakamura Shugo,
Shimizu Kentaro
Publication year - 2006
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.21047
Subject(s) - protein structure prediction , decoy , protein structure , residue (chemistry) , amino acid residue , protein secondary structure , statistical potential , biological system , peptide sequence , chemistry , biology , biochemistry , receptor , gene
We developed a novel knowledge‐based residue environment potential for assessing the quality of protein structures in protein structure prediction. The potential uses the contact number of residues in a protein structure and the absolute contact number of residues predicted from its amino acid sequence using a new prediction method based on a support vector regression (SVR). The contact number of an amino acid residue in a protein structure is defined by the number of residues around a given residue. First, the contact number of each residue is predicted using SVR from an amino acid sequence of a target protein. Then, the potential of the protein structure is calculated from the probability distribution of the native contact numbers corresponding to the predicted ones. The performance of this potential is compared with other score functions using decoy structures to identify both native structure from other structures and near‐native structures from nonnative structures. This potential improves not only the ability to identify native structures from other structures but also the ability to discriminate near‐native structures from nonnative structures. Proteins 2006. © 2006 Wiley‐Liss, Inc.