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Direct methods for computing single‐molecule entropies from molecular simulations
Author(s) -
Suárez Dimas,
Díaz Natalia
Publication year - 2014
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.1195
Subject(s) - nonparametric statistics , statistical physics , computer science , entropy (arrow of time) , molecular dynamics , parametric statistics , gaussian , computational chemistry , chemistry , mathematics , physics , thermodynamics , econometrics , statistics
Assessing the actual role of entropic forces in controlling both the stability and activity of flexible molecules and macromolecules is a theoretical challenge that is gradually gaining more attention. The continuous improvements in computational algorithms and in hardware technologies are greatly expanding the sampling capability of molecular simulations, thereby making a direct positive impact on the feasibility and reliability of entropy predictions. However, more sophisticated theoretical approaches are also required in order to make substantial progress in the type and accuracy of entropy calculations. Focusing on the evaluation of the configurational entropy of single molecules, we highlight recent advances in different methodologies including Gaussian parametric approaches, nonparametric methods and normal mode calculations. For the nonparametric methodologies, we analyze more specifically the importance of correlation effects, the various formulations of the expansion approaches, the combination of nonparametric estimations of conformational entropy with normal mode calculations, the convenience of including bias corrections for mitigating the impact of insufficient sampling and, finally, their close relationship with the experimental measures of conformational motion. The overall consideration of these and other aspects shows that addition of the direct entropy methods to the standard palette of tools used in molecular modeling for data analysis and property estimation, will increase both the level of detail of the computer simulations and our understanding of molecular functions. WIREs Comput Mol Sci 2015, 5:1–26. doi: 10.1002/wcms.1195 This article is categorized under: Structure and Mechanism > Molecular Structures Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods

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