title: LMProt: an efficient algorithm for Monte Carlo sampling of protein conformational space.
abstract: A new and efficient Monte Carlo algorithm for sampling protein configurations in the continuous space is presented; the efficiency of this algorithm, named Local Moves for Proteins (LMProt), was compared to other alternative algorithms. For this purpose, we used an intrachain interaction energy function that is proportional to the root mean square deviation (rmsd) with respect to alpha-carbons from native structures of real proteins. For phantom chains, the LMProt method is approximately 10(4) and 20 times faster than the algorithms Thrashing (no local moves) and Sevenfold Way (local moves), respectively. Additionally, the LMProt was tested for real chains (excluded-volume all-atoms model); proteins 5NLL (138 residues) and 1BFF (129 residues) were used to determine the folding success xi as a function of the number eta of residues involved in the chain movements, and as a function of the maximum amplitude of atomic displacement delta r(max). Our results indicate that multiple local moves associated with relative chain flexibility, controlled by appropriate adjustments for eta and delta r(max), are essential for configurational search efficiency.
authors.affiliation: Departamento de Química, Faculdade de Filosofia Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-903 Ribeirão Preto, São Paulo, Brazil. roos@obelix.ffclrp.usp.br
authors.forename: Roosevelt Alves
authors.initials: RA
authors.lastname: da Silva
authors.forename: Léo
authors.initials: L
authors.lastname: Degrève
authors.forename: Antonio
authors.initials: A
authors.lastname: Caliri
mesh_terms: D000465:Algorithms; D015233:Models, Statistical; D009010:Monte Carlo Method; D016011:Normal Distribution; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D011506:Proteins