Rational Computational Workflow for Structure-Guided Discovery of a Novel USP7 Inhibitor

Abstract

Rationally applied, structurally guided computational methods hold the promise of identifying potent and distinct chemotypes while enabling the precise targeting of structural determinants. Here, we implemented a computational workflow combining insights from cocrystal poses and monitoring the dynamical structural determinants from our previous studies for the identification of potential candidates against USP7. We identified and tested several diverse chemical scaffolds, which underwent in vitro validation across six cancer cell lines. Among these hits, compound M15, belonging to the benzothiazole chemical class, exhibited remarkable anticancer activities, demonstrating dose-dependent reduction in cancer cell viability across all cell lines and indicating that it is a promising candidate to explore as a potent anticancer drug. Biophysical binding confirms binding of M15 on USP7. M15 also exhibited certain USP7 inhibitory activity, as observed in the enzymatic assay. A comparative cocrystal mining of reported USP7 inhibitors unveiled a distinct binding mode of M15, which nicely cross-corroborated with MD and binding-pose metadynamics simulations. Notably, M15 occupies both the determinants, i.e., BL1 and the allosteric checkpoint, which has not yet been underscored as a druggable site. In essence, our study presents a robust and multifaceted computational method for the discovery and characterization of a novel inhibitor scaffold, exemplified by the identification and mechanistic elucidation of M15 against USP7. This integrated approach not only advances our understanding of USP7 inhibition and underscores mechanistic determinants but also offers promising avenues for the discovery of target-specific therapeutic intervention.