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Predicting Ligand Binding Kinetics Using a Markovian Milestoning with Voronoi Tessellations Multiscale Approach

submitted on 12.05.2020, 17:26 and posted on 12.05.2020, 05:55 by Benjamin Jagger, Anupam Anand Ojha, Rommie Amaro

Accurate and efficient computational predictions of ligand binding kinetics can be useful to inform drug discovery campaigns, particularly in the screening and lead optimization phases. Simulation Enabled Estimation of Kinetic Rates, SEEKR, is a multiscale molecular dynamics, Brownian dynamics, and milestoning simulation approach for calculating receptor-ligand association and dissociation rates. Here we present the implementation of a Markovian milestoning with Voronoi tessellations approach that significantly reduces the simulation cost of calculations as well as further improving their parallelizability. The new approach is applied to a host-guest system to assess its effectiveness for rank-ordering compounds by kinetic rates and to the model protein system, trypsin, with the noncovalent inhibitor benzamidine. For both applications, we demonstrate that the new approach requires up to a factor of 10 less simulation time to achieve results with comparable or increased accuracy.


NIH T32-GM008326

NIH P41 GM103426

NIH DP2 OD007237


Email Address of Submitting Author


University of California San Diego


United States

ORCID For Submitting Author


Declaration of Conflict of Interest

No conflict of interests to declare

Version Notes

Submitted version, 8-May 2020