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Simulation of peptide folding with explicit water—a mean solvation method
Author(s) -
Wu XiongWu,
Sung ShenShu
Publication year - 1999
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/(sici)1097-0134(19990215)34:3<295::aid-prot3>3.0.co;2-t
Subject(s) - solvation , molecular dynamics , chemistry , potential of mean force , monte carlo method , solvent , macromolecule , aqueous solution , folding (dsp implementation) , dipeptide , molecule , umbrella sampling , computational chemistry , implicit solvation , protein folding , chemical physics , peptide , organic chemistry , mathematics , biochemistry , statistics , engineering , electrical engineering
A new approach to efficiently calculate solvent effect in computer simulation of macromolecular systems has been developed. Explicit solvent molecules are included in the simulation to provide a mean solvation force for the solute conformational search. Simulations of an alanine dipeptide in aqueous solution showed that the new approach is significantly more efficient than conventional molecular dynamics method in conformational search, mainly because the mean solvation force reduced the solvent damping effect. This approach allows the solute and solvent to be simulated separately with different methods. For the macromolecule, the rigid fragment constraint dynamics method we developed previously allows large time‐steps. For the solvent, a combination of a modified force‐bias Monte Carlo method and a preferential sampling can efficiently sample the conformational space. A folding simulation of a 16‐residue peptide in water showed high efficiency of the new approach. Proteins 1999;34:295–302. © 1999 Wiley‐Liss, Inc.