Accelerating Alchemical Free Energy Prediction Using a Multistate Method: Application to Multiple Kinases
Abstract
lchemical free-energy methods based on molecular dynamics (MD) simulations have become important tools to identify modifications of small organic molecules that improve their protein binding affinity during lead optimization. The routine application of pairwise free-energy methods to rank potential binders from best to worst is impacted by the combinatorial increase of calculations to perform when the number of molecules to assess grows. To address this fundamental limitation, our group has developed replica-exchange enveloping distribution sampling (RE-EDS), a pathway-independent multistate method, enabling the calculation of alchemical free-energy differences between multiple ligands (N > 2) from a single MD simulation. In this work, we apply the method to a set of four kinases with diverse binding pockets, and their corresponding inhibitors (42 in total), chosen to showcase the general applicability of RE-EDS in prospective drug design campaigns. We show that for the targets studied, RE-EDS is able to model up to 13 ligands simultaneously with high sampling efficiency, leading to a substantial decrease in computational cost when compared to pairwise methods. Show more
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https://doi.org/10.3929/ethz-b-000640321Publication status
publishedExternal links
Journal / series
ChemRxivPublisher
Cambridge University PressEdition / version
Version 2Subject
Free energy calculation; Kinase; Multistate methodsOrganisational unit
09458 - Riniker, Sereina Z. / Riniker, Sereina Z.
Funding
212732 - Combining Molecular Dynamics and Machine Learning for Free Energy Calculation with Quantum-Mechanical Accuracy (SNF)
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Is previous version of: https://doi.org/10.3929/ethz-b-000649076
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