Drug-target residence time (τ), one of the main determinants of drug efficacy, remains highly challenging to predict computationally and, therefore, is usually not considered in the early stages of drug design. Here, we present an efficient computational method, τ-random acceleration molecular dynamics (τRAMD), for the ranking of drug candidates by their residence time and obtaining insights into ligand-target dissociation mechanisms. We assessed τRAMD on a data set of 70 diverse drug-like ligands of the N-terminal domain of HSP90α, a pharmaceutically important target with a highly flexible binding site, obtaining computed relative residence times with an accuracy of about 2.3τ for 78% of the compounds and less than 2.0τ within congeneric series. Analysis of dissociation trajectories reveals features that affect ligand unbinding rates, including transient polar interactions and steric hindrance. These results suggest that τRAMD will be widely applicable as a computationally efficient aid to improving drug residence times during lead optimization.

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Sorting nexins (SNXs) form a family of proteins known to interact with components in the endosomal system and to regulate various steps of vesicle transport. Sorting nexin 9 (SNX9) is involved in the late stages of clathrin-mediated endocytosis in non-neuronal cells, where together with the GTPase dynamin, it participates in the formation and scission of the vesicle neck. We report here crystal structures of the functional membrane-remodeling unit of SNX9 and show that it efficiently tubulates lipid membranes in vivo and in vitro. Elucidation of the protein superdomain structure, together with mutational analysis and biochemical and cell biological experiments, demonstrated how the SNX9 PX and BAR domains work in concert in targeting and tubulation of phosphoinositide-containing membranes. The study provides insights into the SNX9-induced membrane modulation mechanism.

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