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

摘要: In this study, we demonstrate the extensive scalability of 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 largest exploration chemical space using methods known date, requires only a few simulations, and identifies 55 new inhibitor designs against HIV-RT predicted be at least as potent tight reference compound (i.e., 56 nM). We highlight that BP-REX MSλD an order magnitude less computational resources than conventional while maintaining similar level precision, overcomes inherent poor methods, enables combinatorially large spaces in context silico drug discovery.