Equilibrium molecular thermodynamics from Kirkwood sampling.

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Somani, Sandeep 
Okamoto, Yuko 
Ballard, Andrew J 
Wales, David J 

We present two methods for barrierless equilibrium sampling of molecular systems based on the recently proposed Kirkwood method (J. Chem. Phys. 2009, 130, 134102). Kirkwood sampling employs low-order correlations among internal coordinates of a molecule for random (or non-Markovian) sampling of the high dimensional conformational space. This is a geometrical sampling method independent of the potential energy surface. The first method is a variant of biased Monte Carlo, where Kirkwood sampling is used for generating trial Monte Carlo moves. Using this method, equilibrium distributions corresponding to different temperatures and potential energy functions can be generated from a given set of low-order correlations. Since Kirkwood samples are generated independently, this method is ideally suited for massively parallel distributed computing. The second approach is a variant of reservoir replica exchange, where Kirkwood sampling is used to construct a reservoir of conformations, which exchanges conformations with the replicas performing equilibrium sampling corresponding to different thermodynamic states. Coupling with the Kirkwood reservoir enhances sampling by facilitating global jumps in the conformational space. The efficiency of both methods depends on the overlap of the Kirkwood distribution with the target equilibrium distribution. We present proof-of-concept results for a model nine-atom linear molecule and alanine dipeptide.

Algorithms, Dipeptides, Molecular Conformation, Monte Carlo Method, Thermodynamics
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J Phys Chem B
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American Chemical Society (ACS)
Engineering and Physical Sciences Research Council (EP/I001352/1)
This research was funded by the European Research Council and EPSRC grant EP/I001352/1. Y.O. was supported, in part, by the JSPS Grant-in-Aid for Scientific Research on Innovative Areas (“Dynamical Ordering and Integrated Functions”).