title: Enhanced sampling near the native conformation using statistical potentials for local side-chain and backbone interactions.
abstract: In the preceding article in this issue of Proteins, an empirical energy function consisting of 4 statistical potentials that quantify local side-chain-backbone and side-chain-side-chain interactions has been demonstrated to successfully identify the native conformations of short sequence fragments and the native structure within large sets of high-quality decoys. Because this energy function consists entirely of interactions between residues separated by fewer than 5 positions, it can be used at the earliest stage of ab initio structure prediction to enhance the efficiency of conformational search. In this article, protein fragments are generated de novo by recombining very short segments of protein structures (2, 4, or 6 residues), either selected at random or optimized with respect this local energy function. When local energy is optimized in selected fragments, more efficient sampling of conformational space near the native conformation is consistently observed for 450 randomly selected single turn fragments, with turn lengths varying from 3 to 12 residues and all 4 combinations of flanking secondary structure. These results further demonstrate the energetic significance of local interactions in protein conformations. When used in combination with longer range energy functions, application of these potentials should lead to more accurate prediction of protein structure.
authors.affiliation: Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
authors.forename: Qiaojun
authors.initials: Q
authors.lastname: Fang
authors.forename: David
authors.initials: D
authors.lastname: Shortle
mesh_terms: D019295:Computational Biology; D004151:Dipeptides / Q000737:chemistry; D019077:Helix-Turn-Helix Motifs; D015233:Models, Statistical; D009842:Oligopeptides / Q000737:chemistry; D011487:Protein Conformation; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*
chemical_list: D004151:Dipeptides; D009842:Oligopeptides; D011506:Proteins