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Predicting Binding Free Energies in a Large Combinatorial Chemical Space Using Multisite ? Dynamics.


ABSTRACT: In this study, we demonstrate the extensive scalability of the biasing potential replica exchange multisite ? dynamics (BP-REX MS?D) free energy method by calculating binding affinities for 512 inhibitors to HIV Reverse Transcriptase (HIV-RT). This is the largest exploration of chemical space using free energy methods known to date, requires only a few simulations, and identifies 55 new inhibitor designs against HIV-RT predicted to be at least as potent as a tight binding reference compound (i.e., as potent as 56 nM). We highlight that BP-REX MS?D requires an order of magnitude less computational resources than conventional free energy methods while maintaining a similar level of precision, overcomes the inherent poor scalability of conventional free energy methods, and enables the exploration of combinatorially large chemical spaces in the context of in silico drug discovery.

SUBMITTER: Vilseck JZ 

PROVIDER: S-EPMC6091208 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Predicting Binding Free Energies in a Large Combinatorial Chemical Space Using Multisite λ Dynamics.

Vilseck Jonah Z JZ   Armacost Kira A KA   Hayes Ryan L RL   Goh Garrett B GB   Brooks Charles L CL  

The journal of physical chemistry letters 20180606 12


In this study, we demonstrate the extensive scalability of the biasing potential replica exchange multisite λ dynamics (BP-REX MSλD) free energy method by calculating binding affinities for 512 inhibitors to HIV Reverse Transcriptase (HIV-RT). This is the largest exploration of chemical space using free energy methods known to date, requires only a few simulations, and identifies 55 new inhibitor designs against HIV-RT predicted to be at least as potent as a tight binding reference compound (i.e  ...[more]

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