The accurate prediction of the binding affinities of inhibitors (drugs) to proteins is a major goal in pharmaceutical drug discovery and clinical personalised medicine. We have developed a computational tool, called the Binding Affinity Calculator, which ranks the binding affinities of small molecules to their target proteins rapidly, accurately and reproducibly. The approach uses molecular dynamics based free energy calculations to determine the binding affinities. BAC employs a range of free energy techniques, including thermodynamic integration (TI) and the molecular mechanics Poisson-Boltzmann surface area methods along with variants.<br/><br/>We have previously demonstrated that an ensemble based approach, namely “enhanced sampling of molecular dynamics with approximation of continuum solvent (ESMACS)”, provides a route to reliable predictions of free energies which meets the requirements of accuracy, precision and reliability. Here we present an equivalent methodology based on the TI approach, which is called “thermodynamic integration with enhanced sampling (TIES)”. We report the performance of the TIES method when applied to a diverse set of protein targets and ligands including uncertainty quantification. The results show that the protocol is capable of generating binding affinity differences within a few hours accurately, precisely and reproducibly, with error bars of the order of 0.5 kcal/mol or less. Integration and automation are central to the feasibility and reliability of the method, ensuring that the results are reproducible and can be delivered rapidly.

Rapid, accurate, precise and reliable relative free energy prediction using ensemble based thermodynamic integration

253rd National Meeting (2017)

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