Harnessing free energy calculations for kinome-wide selectivity in drug discovery campaigns with a Wee1 case study

Jennifer Lynn Knight (), Anthony J. Clark, Jiashi Wang, Andrew Placzek, Pieter H. Bos, Sathesh Bhat, Jeffrey A. Bell, Sarah Silvergleid, Wu Yin, Felicia Gray, Shaoxian Sun, Karen Akinsanya, Robert Abel and Aleksey I. Gerasyuto ()
Additional contact information
Jennifer Lynn Knight: Inc.
Anthony J. Clark: Inc.
Jiashi Wang: Inc.
Andrew Placzek: Inc.
Pieter H. Bos: Inc.
Sathesh Bhat: Inc.
Jeffrey A. Bell: Inc.
Sarah Silvergleid: Inc.
Wu Yin: Inc.
Felicia Gray: Inc.
Shaoxian Sun: Inc.
Karen Akinsanya: Inc.
Robert Abel: Inc.
Aleksey I. Gerasyuto: Inc.

Nature Communications, 2025, vol. 16, issue 1, 1-16

Abstract: Abstract 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.

Date: 2025
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DOI: 10.1038/s41467-025-62722-w

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