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Optimizing both on-target and off-target potencies is essential for developing effective and selective small-molecule therapeutics. Free energy calculations offer rapid potency predictions, usually within hours and with experimental accuracy and thus enables efficient identification of promising compounds for synthesis, accelerating early-stage drug discovery campaigns. While free energy predictions are routinely applied to individual proteins, here, we present a free energy framework for efficiently achieving kinome-wide selectivity that led to the discovery of selective Wee1 kinase inhibitors. Ligand-based relative binding free energy calculations rapidly identified multiple novel potent chemical scaffolds. Subsequent protein residue mutation free energy calculations that modified the Wee1 gatekeeper residue, significantly reduced their off-target liabilities across the kinome. Thus, with judicious use of this gatekeeper residue selectivity handle, applying this computational strategy streamlined the optimization of both on-target and off-target potencies, offering a roadmap to expedite drug discovery timelines by decreasing unanticipated off-target toxicities. Free energy calculations are an essential tool to identify targets for individual proteins. Here, authors describe free energy perturbation (FEP+) calculations to optimise on target and off-target potencies for the discovery of potent Wee1 inhibitors with kinome-wide selectivity.

Identifying effective therapeutic targets for Parkinson’s disease (PD) is challenging, with no current disease-modifying therapies available. To address this, The Michael J. Fox Foundation for Parkinson’s Research launched the Targets to Therapies (T2T) initiative, uniting experts to prioritize and validate promising targets. T2T aims to develop validation strategies, create comprehensive target data profiles, and build tools to support drug development, ultimately accelerating the discovery of new therapies for PD patients.