Quantitative Ranking of Ligand Binding Kinetics with a Multiscale Milestoning Simulation Approach.

ABSTRACT: Efficient prediction and ranking of small molecule binders by their kinetic ( k_on and k_off) and thermodynamic ( Δ G) properties can be a valuable metric for drug lead optimization, as these quantities are often indicators of in vivo efficacy. We have previously described a hybrid molecular dynamics, Brownian dynamics, and milestoning model, Simulation Enabled Estimation of Kinetic Rates (SEEKR), that can predict k_on's, k_off's, and Δ G's. Here we demonstrate the effectiveness of this approach for ranking a series of seven small molecule compounds for the model system, β-cyclodextrin, based on predicted k_on's and k_off's. We compare our results using SEEKR to experimentally determined rates as well as rates calculated using lon

SUBMITTER: Jagger BR 

PROVIDER: S-EPMC6443090 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature