Abstract
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.