title: Biased fragment distribution in MC simulation of protein folding.
abstract: Monte Carlo (MC) methods play an important role in simulations of protein folding. These methods rely on a random sampling of moves on a potential energy surface. To improve the efficiency of the sampling, we propose a new selection of trial moves based on an empirical distribution of three-residue (triplet) conformations. This selection is compared to random combinations of the preferred conformations of the three amino acids, and it is shown that the new trial moves lead to finding structures closer to the native conformation.
authors.affiliation: Université de Montréal, Département de Chimie, Québec, Canada. emartineau@neurochem.com
authors.forename: Eric
authors.initials: E
authors.lastname: Martineau
authors.forename: Pierre-Jean
authors.initials: PJ
authors.lastname: L'Heureux
authors.forename: John R
authors.initials: JR
authors.lastname: Gunn
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry; D003198:Computer Simulation; D008958:Models, Molecular; D009010:Monte Carlo Method; D009211:Myoglobin / Q000737:chemistry; D017510:Protein Folding; D017434:Protein Structure, Tertiary; D013816:Thermodynamics
chemical_list: D000596:Amino Acids; D009211:Myoglobin