Harnessing free energy calculations for kinome-wide selectivity in drug discovery campaigns with a Wee1 case study
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.
Authors
- Aleksey I. Gerasyuto
- Robert Abel (ORCID: https://orcid.org/0000-0003-2945-3145)
- Pieter H. Bos (ORCID: https://orcid.org/0000-0002-8710-4771)
- Sathesh Bhat (ORCID: https://orcid.org/0000-0003-1819-5726)
- Felicia Gray
- Sarah Silvergleid (ORCID: https://orcid.org/0009-0000-0282-6664)
- Andrew Placzek
- Shaoxian Sun (ORCID: https://orcid.org/0000-0003-4751-3025)
- Jeffrey A. Bell (ORCID: https://orcid.org/0000-0002-8310-0183)
- Anthony J. Clark (ORCID: https://orcid.org/0009-0002-9425-0221)
- Jennifer L. Knight (ORCID: https://orcid.org/0000-0002-9113-0921)
- Wu Yin
- Karen Akinsanya
- Jiashi Wang
Institutions
- Schrodinger (United States) (US)
- Schrodinger (United States) (US)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-08-26
- DOI
- https://doi.org/10.1038/s41467-025-62722-w
- Citations
- 2
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 3.01