Ranking of Ligand Binding Kinetics using a Weighted Ensemble Approach and Comparison with Milestoning

Abstract

In order to improve lead optimization efforts in finding the right ligand, pharmaceutical industries need to know the ligand's binding kinetics, such as binding and unbinding rate constants, which are known to be good indicators of the ligand's efficacy in vivo. To predict binding kinetics quickly, enhanced sampling methods, such as milestoning and the weighted ensemble (WE) method, have been used in molecular dynamics (MD) simulations of these systems. However, a direct comparison of the enhanced sampling methods in ranking ligands has not been done. Hence, a WE approach called the concurrent adaptive sampling (CAS) algorithm was used to rank seven ligands for beta-cyclodextrin, a system in which a milestoning approach called simulation enabled estimation of kinetic rates (SEEKR) was also used. Overall, the CAS algorithm can successfully rank ligands using the unbinding rate constants koff's and binding free energies, as SEEKR did, with reduced computational cost that is about the same as SEEKR. We discuss "best practices" for using WE approaches like the CAS algorithm and pros and cons of each enhanced sampling method for future use.