Rugged Metropolis sampling with simultaneous updating of two dynamical variables.
The rugged Metropolis (RM) algorithm is a biased updating scheme which aims at directly hitting the most likely configurations in a rugged free-energy landscape. Details of the one-variable ( RM1 ) implementation of this algorithm are presented. This is followed by an extension to simultaneous updating of two dynamical variables ( RM2 ). In a test with the brain peptide Met-Enkephalin in vacuum RM2 improves conventional Metropolis simulations by a factor of about 4. Correlations between three or more dihedral angles appear to prevent larger improvements at low temperatures. We also investigate a multihit Metropolis scheme, which spends more CPU time on variables with large autocorrelation times.
Berg
Bernd A
BA
Department of Physics, Florida State University, Tallahassee, Florida 32306-4350, USA.
Zhou
Huan-Xiang
HX
D000465:Algorithms; D000818:Animals; D001703:Biophysics / Q000379:methods*; D001921:Brain / Q000378:metabolism; D003198:Computer Simulation; D003201:Computers; D004744:Enkephalin, Methionine / Q000737:chemistry; D006801:Humans; D008956:Models, Chemical; D015233:Models, Statistical; D008962:Models, Theoretical; D008968:Molecular Conformation; D009010:Monte Carlo Method; D010455:Peptides / Q000737:chemistry*; D011487:Protein Conformation; D017510:Protein Folding; D013696:Temperature; D013816:Thermodynamics; D013997:Time Factors
D010455:Peptides; D004744:Enkephalin, Methionine