6eln

Publication Abstract from PubMed

Drug-target residence time (tau), one of the main determinants of drug efficacy, remains highly challeng-ing to predict computationally and, therefore, is usually not considered in the early stages of drug de-sign. Here, we present an efficient computational method, tau-random acceleration molecular dynamics (tauRAMD), for the ranking of drug candidates by their residence time and obtaining insights into ligand-target dissociation mechanisms. We assessed tauRAMD on a dataset of 70 diverse drug-like ligands of the N-terminal domain of HSP90alpha, a pharmaceutically important target with a highly flexible binding site, obtaining computed relative residence times with an accuracy of about 2.3tau for 78% of the compounds and less than 2.0tau within congeneric series. Analysis of dissociation trajectories reveals features that af-fect ligand unbinding rates, including transient polar interactions and steric hindrance. These results sug-gest that tauRAMD will be widely applicable as a computationally efficient aid to improving drug resi-dence times during lead optimization.

Estimation of drug-target residence times by tau -random acceleration molecular dynamics simulations.,Kokh DB, Amaral M, Bomke J, Gradler U, Musil D, Buchstaller HP, Dreyer MK, Frech M, Lowinski M, Vallee F, Bianciotto M, Rak A, Wade RC J Chem Theory Comput. 2018 May 16. doi: 10.1021/acs.jctc.8b00230. PMID:29768913^[3]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.