Stochastic Dynamics with a Potential of Mean Force

STOCHASTIC DYNAMICS WITH A POTENTIAL OF MEAN FORCE 

The dynamical aspects of the solvent are approximated by including stochastic and dissipative forces in the equations of motion. 

To treat the effects of solvent in a simple fashion, the Langevin equation 

Stochastic dynamics has been found to be particularly useful for introducing simplified descriptions of the internal motions of complex systems. When applied to small systems (e.g., a peptide or an amino acid sidechain) it is possible to do simulations that extend into the microsecond range, where many important phenomena occur. Simulation studies using this method have been carried out, for example, to explore solvent effects on the dynamics of internal soft degrees of freedom in small biopolymers, e.g., the dynamics of dihedral angle rotations in the alanine dipeptide (see Chapt. IX.B.l). 

Clearly, the present approach precludes the detailed study of the dynamics of explicit solute-solvent interactions because the solvent (bath) degrees of freedom have been eliminated. Also, as in the stochastic boundary model, 

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D. STOCHASTIC DYNAMICS WITH A POTENTIAL OF MEAN FORCE... 

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