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Prediction of protein–ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations

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Abstract

Many limitations of current computer-aided drug design arise from the difficulty of reliably predicting the binding affinity of a small molecule to a biological target. There is thus a strong interest in novel computational methodologies that claim predictions of greater accuracy than current scoring functions, and at a throughput compatible with the rapid pace of drug discovery in the pharmaceutical industry. Notably, computational methodologies firmly rooted in statistical thermodynamics have received particular attention in recent years. Yet free energy calculations can be daunting to learn for a novice user because of numerous technical issues and various approaches advocated by experts in the field. The purpose of this article is to provide an overview of the current capabilities of free energy calculations and to discuss the applicability of this technology to drug discovery.

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Acknowledgments

This research was partially supported (J.M.) by a Marie Curie International Outgoing Fellowship within the 7th European Community Framework Programme (FP7-PEOPLE-2008-4-1-IOF, 234796-PPIdesign).

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  1. Institute of Structural and Molecular Biology, The University of Edinburgh, Edinburgh, EH9 3JR, UK

    Julien Michel

  2. Department of Chemistry, Yale University, New Haven, CT, 06520, USA

    Julien Michel

  3. School of Chemistry, University of Southampton, Highfield, Southampton, SO17 1BJ, UK

    Jonathan W. Essex

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Michel, J., Essex, J.W. Prediction of protein–ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations. J Comput Aided Mol Des 24, 639–658 (2010). https://doi.org/10.1007/s10822-010-9363-3

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