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Estimation of Conformational Entropy in Protein–Ligand Interactions: A Computational Perspective

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Computational Drug Discovery and Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 819))

Abstract

Conformational entropy is an important component of the change in free energy upon binding of a ligand to its target protein. As a consequence, development of computational techniques for reliable estimation of conformational entropies is currently receiving an increased level of attention in the context of computational drug design. Here, we review the most commonly used techniques for conformational entropy estimation from classical molecular dynamics simulations. Although by-and-large still not directly used in practical drug design, these techniques provide a golden standard for developing other, computationally less-demanding methods for such applications, in addition to furthering our understanding of protein–ligand interactions in general. In particular, we focus on the quasi-harmonic approximation and discuss different approaches that can be used to go beyond it, most notably, when it comes to treating anharmonic and/or correlated motions. In addition to reviewing basic theoretical formalisms, we provide a concrete set of steps required to successfully calculate conformational entropy from molecular dynamics simulations, as well as discuss a number of practical issues that may arise in such calculations.

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Authors and Affiliations

  1. Laboratory of Computational Biophysics, Department of Structural and Computational Biology, Max Perutz Laboratories, Vienna, Austria

    Anton A. Polyansky, Ruben Zubac & Bojan Zagrovic

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  1. Anton A. Polyansky
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  2. Ruben Zubac
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Correspondence to Bojan Zagrovic .

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  1. University of Utah, 30 South 2000 East Rm 307, Salt Lake City, 84112-5820, California, USA

    Riccardo Baron

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Polyansky, A.A., Zubac, R., Zagrovic, B. (2012). Estimation of Conformational Entropy in Protein–Ligand Interactions: A Computational Perspective. In: Baron, R. (eds) Computational Drug Discovery and Design. Methods in Molecular Biology, vol 819. Springer, New York, NY. https://doi.org/10.1007/978-1-61779-465-0_21

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  • DOI: https://doi.org/10.1007/978-1-61779-465-0_21

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