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Exploiting the potential energy landscape to sample free energy
Author(s) -
Ballard Andrew J.,
Martiniani Stefano,
Stevenson Jacob D.,
Somani Sandeep,
Wales David J.
Publication year - 2015
Publication title -
wiley interdisciplinary reviews: computational molecular science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.126
H-Index - 81
eISSN - 1759-0884
pISSN - 1759-0876
DOI - 10.1002/wcms.1217
Subject(s) - maxima and minima , replica , energy landscape , sampling (signal processing) , computer science , energy (signal processing) , superposition principle , exploit , statistical physics , configuration space , mechanism (biology) , umbrella sampling , mathematical optimization , molecular dynamics , physics , mathematics , geography , quantum mechanics , mathematical analysis , computer security , archaeology , filter (signal processing) , computer vision , thermodynamics
We review a number of recently developed strategies for enhanced sampling of complex systems based on knowledge of the potential energy landscape. We describe four approaches, replica exchange, Kirkwood sampling, superposition‐enhanced nested sampling, and basin sampling, and show how each of them can exploit information for low‐lying potential energy minima obtained using basin‐hopping global optimization. Characterizing these minima is generally much faster than equilibrium thermodynamic sampling, because large steps in configuration space between local minima can be used without concern for maintaining detailed balance. WIREs Comput Mol Sci 2015, 5:273–289. doi: 10.1002/wcms.1217 This article is categorized under: Structure and Mechanism > Molecular Structures Structure and Mechanism > Computational Biochemistry and Biophysics Structure and Mechanism > Computational Materials Science