Monte Carlo simulations of biomolecules: The MC module in CHARMM.
We describe the implementation of a general and flexible Monte Carlo (MC) module for the program CHARMM, which is used widely for modeling biomolecular systems with empirical energy functions. Construction and use of an almost arbitrary move set with only a few commands is made possible by providing several predefined types of moves that can be combined. Sampling can be enhanced by noncanonical acceptance criteria, automatic optimization of step sizes, and energy minimization. A systematic procedure for improving MC move sets is introduced and applied to simulations of two peptides. The resulting move sets allow MC to sample the configuration spaces of these systems much more rapidly than Langevin dynamics. The rate of convergence of the difference in free energy between ethane and methanol in explicit solvent is also examined, and comparable performances are observed for MC and the Nosé-Hoover algorithm. Its ease of use combined with its sampling efficiency make the MC module in CHARMM an attractive alternative for exploring the behavior of biomolecular systems.
Hu
Jie
J
Department of Chemistry, The University of Chicago, Chicago, Illinois 60637, USA.
Ma
Ao
A
Dinner
Aaron R
AR
D000409:Alanine / Q000737:chemistry*; D000465:Algorithms; D003198:Computer Simulation; D004151:Dipeptides / Q000737:chemistry*; D004980:Ethane / Q000737:chemistry; D000432:Methanol / Q000737:chemistry; D008956:Models, Chemical; D008958:Models, Molecular; D009010:Monte Carlo Method; D009842:Oligopeptides / Q000737:chemistry*; D012985:Software Design; D012997:Solvents / Q000737:chemistry; D013816:Thermodynamics; D013997:Time Factors
D004151:Dipeptides; D009842:Oligopeptides; D012997:Solvents; D004980:Ethane; D000409:Alanine; D000432:Methanol