Free Energy Methods in Drug Discovery—Introduction

 vol. 1397  p. 1-38  DOI: 10.1021/bk-2021-1397.ch001   ISBN: 9780841298057   Published: 2021-11-19 

Zoe Cournia, Christophe Chipot, Benoît Roux, Darrin M. York [ ] , Woody Sherman

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Complete understanding of most, if not all chemical processes requires at its very core the knowledge of the underlying free-energy change. In computer-aided drug design, for instance, such processes as binding of a drug to a protein or its spontaneous partitioning across the cell membrane cannot be predicted reliably without considering how the associated free energy varies. Owing to relentless theoretical developments, which have benefited from ever-growing computational resources, free-energy calculations leaning on statistical-mechanics simulations are now part of the arsenal of robust and well-characterized modeling tools. However, as will be explained below and touched upon throughout the chapters of this book, it is still challenging to obtain accurate and reliable free-energy predictions for biomolecules due to the many nuances in the system setup and the unknown unknowns such as whether a given simulation is globally converged or only locally converged, perhaps in an incorrect free-energy basin. In all but the simplest cases, free-energy simulations still require experts in the field to prepare the system, run the calculations, and analyze the results in order to obtain robust predictions that can be confidently used to make decisions in drug discovery campaigns.