Monte Carlo sampling algorithm for searching a scale-transformed energy space of polypeptides.
A Monte Carlo sampling algorithm for searching a scale-transformed conformational energy space of polypeptides is presented. This algorithm is based on the assumption that energy barriers can be overcome by a uniform sampling of the logarithmically transformed energy space. This algorithm is tested with Met-enkephalin. For comparison, the entropy sampling Monte Carlo (ESMC) simulation is performed. First, the global minimum is easily found by the optimization of a scale-transformed energy space. With a new Monte Carlo sampling, energy barriers of 3000 kcal/mol are frequently overcome, and low-energy conformations are sampled more efficiently than with ESMC simulations. Several thermodynamic quantities are calculated with good accuracy.
Nakamura
Hideaki
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Department of Functional Materials Engineering, Fukuoka Institute of Technology, 3-30-1 Wajirohigashi, Higashi-ku, Fukuoka 811-0295, Japan.
D000465:Algorithms; D000818:Animals; D004744:Enkephalin, Methionine / Q000737:chemistry*; D006801:Humans; D009010:Monte Carlo Method; D010455:Peptides / Q000737:chemistry*; D011487:Protein Conformation; D013816:Thermodynamics
D010455:Peptides; D004744:Enkephalin, Methionine