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Statistical mechanics and molecular dynamics in evaluating thermodynamic properties of biomolecular recognition

Published online by Cambridge University Press:  15 November 2011

Jeff Wereszczynski  and
J. Andrew McCammon
Jeff Wereszczynski*
Affiliation:
Department of Chemistry and Biochemistry, University of California, San Diego, CA, USA
J. Andrew McCammon
Affiliation:
Department of Chemistry and Biochemistry, Department of Pharmacology, Howard Hughes Medical Institute, Chevy Chase, MD, USA
*
*Author for correspondence: J. Wereszczynski, Department of Chemistry and Biochemistry, University of California, San Diego, CA, USA. Tel.: 858.822.0169; Fax: 858.534.4974; Email: [email protected]
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Abstract

Molecular recognition plays a central role in biochemical processes. Although well studied, understanding the mechanisms of recognition is inherently difficult due to the range of potential interactions, the molecular rearrangement associated with binding, and the time and length scales involved. Computational methods have the potential for not only complementing experiments that have been performed, but also in guiding future ones through their predictive abilities. In this review, we discuss how molecular dynamics (MD) simulations may be used in advancing our understanding of the thermodynamics that drive biomolecular recognition. We begin with a brief review of the statistical mechanics that form a basis for these methods. This is followed by a description of some of the most commonly used methods: thermodynamic pathways employing alchemical transformations and potential of mean force calculations, along with end-point calculations for free energy differences, and harmonic and quasi-harmonic analysis for entropic calculations. Finally, a few of the fundamental findings that have resulted from these methods are discussed, such as the role of configurational entropy and solvent in intermolecular interactions, along with selected results of the model system T4 lysozyme to illustrate potential and current limitations of these methods.

Type
Review Article
Information
Quarterly Reviews of Biophysics , Volume 45 , Issue 1 , February 2012 , pp. 1 - 25
Copyright
Copyright © Cambridge University Press 2011

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