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A Comparison of Methods to Compute the Potential of Mean Force
Author(s) -
Trzesniak Daniel,
Kunz AnnaPitschna E.,
van Gunsteren Wilfred F.
Publication year - 2007
Publication title -
chemphyschem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 140
eISSN - 1439-7641
pISSN - 1439-4235
DOI - 10.1002/cphc.200600527
Subject(s) - potential of mean force , cartesian coordinate system , constraint (computer aided design) , reaction coordinate , measure (data warehouse) , degrees of freedom (physics and chemistry) , potential energy , statistical physics , energy (signal processing) , physics , mathematics , chemistry , classical mechanics , molecule , thermodynamics , computational chemistry , quantum mechanics , geometry , computer science , database
Most processes occurring in a system are determined by the relative free energy between two or more states because the free energy is a measure of the probability of finding the system in a given state. When the two states of interest are connected by a pathway, usually called reaction coordinate, along which the free‐energy profile is determined, this profile or potential of mean force (PMF) will also yield the relative free energy of the two states. Twelve different methods to compute a PMF are reviewed and compared, with regard to their precision, for a system consisting of a pair of methane molecules in aqueous solution. We analyze all combinations of the type of sampling (unbiased, umbrella‐biased or constraint‐biased), how to compute free energies (from density of states or force averaging) and the type of coordinate system (internal or Cartesian) used for the PMF degree of freedom. The method of choice is constraint‐bias simulation combined with force averaging for either an internal or a Cartesian PMF degree of freedom.