Previously Uncharacterized Vacuolar-type ATPase Binding Site Discovered from Structurally Similar Compounds with Distinct Mechanisms of Action.

Using a comprehensive chemical genetics approach, we identified a member of the lignan natural product family, HTP-013, which exhibited significant cytotoxicity across various cancer cell lines. Correlation of compound activity across a panel of reporter gene assays suggested the vacuolar-type ATPase (v-ATPase) as a potential target for this compound. Additional cellular studies and a yeast haploinsufficiency screen strongly supported this finding. Competitive photoaffinity labeling experiments demonstrated that the ATP6V0A2 subunit of the v-ATPase complex binds directly to HTP-013, and further mutagenesis library screening identified resistance-conferring mutations in ATP6V0A2. The positions of these mutations suggest the molecule binds a novel pocket within the domain of the v-ATPase complex responsible for proton translocation. While other mechanisms of v-ATPase regulation have been described, such as dissociation of the complex or inhibition by natural products including bafilomycin A1 and concanamycin, this work provides detailed insight into a distinct binding pocket within the v-ATPase complex.

Evidence-Based and Quantitative Prioritization of Tool Compounds in Phenotypic Drug Discovery.

The use of potent and selective chemical tools with well-defined targets can help elucidate biological processes driving phenotypes in phenotypic screens. However, identification of selective compounds en masse to create targeted screening sets is non-trivial. A systematic approach is needed to prioritize probes, which prevents the repeated use of published but unselective compounds. Here we performed a meta-analysis of integrated large-scale, heterogeneous bioactivity data to create an evidence-based, quantitative metric to systematically rank tool compounds for targets. Our tool score (TS) was then tested on hundreds of compounds by assessing their activity profiles in a panel of 41 cell-based pathway assays. We demonstrate that high-TS tools show more reliably selective phenotypic profiles than lower-TS compounds. Additionally we highlight frequently tested compounds that are non-selective tools and distinguish target family polypharmacology from cross-family promiscuity. TS can therefore be used to prioritize compounds from heterogeneous databases for phenotypic screening.