Shuheng Huang, Duo Zhang, Hu Mei, MuliadiYeremia Kevin, Sujun Qu, Xianchao Pan, and Laichun Lu (2019).
Journal of chemical information and modeling, 59, 159-169.   (PubMed)

Recent research has increasingly suggested that the crucial factors affecting drug potencies are related not only to the thermodynamic properties but also to the kinetic properties. Therefore, in silico prediction of ligand-binding kinetic properties, especially the dissociation rate constant ( koff), has aroused more and more attention. However, there are still a lot of challenges that need to be addressed. In this paper, steered molecular dynamics (SMD) combined with residue-based energy decomposition was employed to predict the dissociation rate constants of 37 HIV-1 protease inhibitors (HIV-1 PIs). For the first time, a predictive model of the dissociation rate constant was established by using the interaction-energy fingerprints sampled along the ligand dissociation pathway. On the basis of the key fingerprints extracted it can be inferred that the dissociation rates of 37 HIV-1 PIs are basically determined in the first half of the dissociation processes and that the H-bond interactions with active-site Asp25 and van der Waals interactions with flap-region Ile47 and Ile50 have important influences on the dissociation processes. In general, the strategy established in this paper can provide an efficient way for the prediction of dissociation rate constants as well as the unbinding mechanism research.

This work describes an example of using Steered molecular dynamics in kinetic calculations.