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Hydrogen-deuterium eXchange mass spectrometry (HDX-MS) is increasingly used in drug development to locate binding sites and to identify allosteric effects in drug/target interactions. However, the potential of this technique to quantitatively analyze drug candidate libraries remains largely unexplored. Here, a collection of 13 WDR5-targeting small molecules with surface plasmon resonance (SPR) dissociation coefficients ( K D ) ranging from 20 nM to ∼116 μM were characterized using differential HDX-MS (ΔHDX-MS). Conventional qualitative analysis of the ΔHDX-MS data set revealed the binding interfaces for all compounds and allosteric effects where present. We then demonstrated that ΔHDX-MS signal-to-noise (S/N) not only can rank library-relative affinity but also can accurately predict K D from a calibration curve constructed from high-quality SPR data. Three methods for S/N calculation are explored, each suitable for libraries with different characteristics. Our results demonstrate the potential for ΔHDX-MS use in drug candidate library affinity validation and/or determination while simultaneously characterizing structure.

Helicases have emerged as promising targets for the development of antiviral drugs; however, the family remains largely undrugged. To support the focused development of viral helicase inhibitors we identified, collected, and integrated all chemogenomics data for all available helicases from the ChEMBL database. After thoroughly curating and enriching the data with relevant annotations we have created a derivative database of helicase inhibitors which we dubbed Heli-SMACC (Helicase-targeting SMAll Molecule Compound Collection). The current version of Heli-SMACC contains 20,432 bioactivity entries for viral, human, and bacterial helicases. We have selected 30 compounds with promising viral helicase activity and tested them in a SARS-CoV-2 NSP13 ATPase assay. Twelve compounds demonstrated ATPase inhibition and a consistent dose-response curve. The Heli-SMACC database may serve as a reference for virologists and medicinal chemists working on the development of novel helicase inhibitors. Heli-SMACC is publicly available at https://smacc.mml.unc.edu., Competing Interests: Conflict of interest AT and ENM are co-founders of Predictive, LLC, which develops novel alternative methods and software for toxicity prediction. All other authors have nothing to disclose.

We herewith applied a priori a generic hit identification method (POEM) for difficult targets of known three-dimensional structure, relying on the simple knowledge of physicochemical and topological properties of a user-selected cavity. Searching for local similarity to a set of fragment-bound protein microenvironments of known structure, a point cloud registration algorithm is first applied to align known subpockets to the target cavity. The resulting alignment then permits us to directly pose the corresponding seed fragments in a target cavity space not typically amenable to classical docking approaches. Last, linking potentially connectable atoms by a deep generative linker enables full ligand enumeration. When applied to the WD40 repeat (WDR) central cavity of leucine-rich repeat kinase 2 (LRRK2), an unprecedented binding site, POEM was able to quickly propose 94 potential hits, five of which were subsequently confirmed to bind in vitro to LRRK2-WDR.