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

摘要

Molecular recognition plays a central role in biochemical processes. Althoughwell studied, understanding the mechanisms of recognition is inherently difficult due to therange of potential interactions, the molecular rearrangement associated with binding, and thetime and length scales involved. Computational methods have the potential for not onlycomplementing experiments that have been performed, but also in guiding future onesthrough their predictive abilities. In this review, we discuss how molecular dynamics (MD)simulations may be used in advancing our understanding of the thermodynamics that drivebiomolecular recognition. We begin with a brief review of the statistical mechanics that form abasis for these methods. This is followed by a description of some of the most commonly usedmethods: thermodynamic pathways employing alchemical transformations and potential ofmean force calculations, along with end-point calculations for free energy differences, andharmonic and quasi-harmonic analysis for entropic calculations. Finally, a few of thefundamental findings that have resulted from these methods are discussed, such as the role ofconfigurational entropy and solvent in intermolecular interactions, along with selected results ofthe model system 14 lysozyme to illustrate potential and current limitations of these methods.