Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies

Rhys Evans, Ladislav Hovan, Gareth Tribello, Benjamin Cossins, Carolina Estarellas, Francesco Gervasio

Research output: Contribution to journalArticle

Abstract

Calculating absolute binding free energies is challenging and important. In this paper, we test some recently-developed metadynamics-based methods and develop a new combination with a Hamiltonian replica-exchange approach. The methods were tested on 18 chemically-diverse ligands with a wide range of different binding affinities to a complex target; namely, human soluble epoxide hydrolase. The results suggest that metadynamics with a funnel-shaped restraint can be used to calcu-late, in a computationally affordable and relatively accurate way, the absolute binding free energy for small fragments. When used in combination with an optimal path-like variable obtained using machine learning; or with the Hamiltonian replica-exchange algorithm SWISH; this method can achieve reasonably accurate results for increasingly complex ligands, with a good balance of computational cost and speed. An additional benefit of using the combination of metadynamics and SWISH is that it also provides useful information about the role of water in the binding mechanism.
Original languageEnglish
JournalJournal of chemical theory and computation
Early online date19 May 2020
DOIs
Publication statusEarly online date - 19 May 2020

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