Accelerating Dissociative Events in Molecular Dynamics Simulations by Selective Potential Scaling

Indrajit Deb, Aaron T. Frank (Lead / Corresponding author)

Research output: Working paper/PreprintPreprint

Abstract

Molecular dynamics (or MD) simulations can be a powerful tool for modeling complex dissociative processes such as ligand unbinding. However, many biologically relevant dissociative processes occur on timescales that far exceed the timescales of typical MD simulations. Here, we implement and apply an enhanced sampling method in which specific energy terms in the potential energy function are selectively “scaled” to accelerate dissociative events during simulations. Using ligand unbinding as an example of a complex dissociative process, we selectively scaled-up ligand-water interactions in an attempt to increase the rate of ligand unbinding. By applying our selectively scaled MD (or ssMD) approach to three cyclin-dependent kinase 2 (CDK2)-inhibitor complexes, we were able to significantly accelerate ligand unbinding thereby allowing, in some cases, unbinding events to occur within as little as 2 ns. Moreover, we found that we could make realistic estimates of the unbinding as well as the binding free energies (∆Gsim) of the three inhibitors from our ssMD simulation data. To accomplish this, we employed a previously described Kramers’-based rate extrapolation (KRE) method and a newly described free energy extrapolation (FEE) method. Because our ssMD approach is general, it should find utility as an easy-to-deploy, enhanced sampling method for modeling other dissociative processes.
Original languageEnglish
PublisherBioRxiv
Number of pages13
DOIs
Publication statusPublished - 19 Feb 2019

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