Enhanced-Sampling Simulations for the Estimation of Ligand Binding Kinetics: Current Status and Perspective

The dissociation rate (k(off)) associated with ligand unbinding events from proteins is a parameter of fundamental importance in drug design. Here we review recent major advancements in molecular simulation methodologies for the prediction of k(off). Next, we discuss the impact of the potential energy function models on the accuracy of calculated k(off) values. Finally, we provide a perspective from high-performance computing and machine learning which might help improve such predictions.

Automated summary

This article reviews recent advancements in molecular simulation methodologies for predicting the dissociation rate of ligands from proteins (k(off)). It discusses the impact of potential energy function models on the accuracy of calculated k(off) values and provides a perspective on improving such predictions through high-performance computing and machine learning.