Protein language model-based fitness estimates facilitate resistance mutation identification

作者：Dominik Schwarz, Sven Giese, Akansha Gupta, Paulina J. Dziubańska-Kusibab, Santiago D. Villalba, Andrew Cherniack, Xiaoping Yang, David E. Root, Gizem Karsli-Uzunbas, Heidi Greulich, Franziska Siegel, Atanas Kamburov, Ekaterina Nevedomskaya, Clara D. Christ, Matteo Aldeghi, Jérémie Mortier · 发表于：ChemRxiv · 年份：2026 · DOI：10.26434/chemrxiv.15000911/v1 · 研究领域：Cancer Genomics and Diagnostics、Evolution and Genetic Dynamics、Computational Drug Discovery Methods

Drug resistance is a major challenge in cancer therapy. Cancer cells with pre-existing or acquired mutations that confer resistance to a given drug treatment outgrow the susceptible cell population and cause cancer recurrence after initial successful treatment response. Knowledge about resistance mutations before they occur in the clinic could prevent unnecessary patient treatment with ineffective drugs, in clinical trials as well as clinical practice, or potentially speed-up the development of follow-up compounds. Here, we focused on on-target amino acid mutations that confer resistance to an inhibitor compound with a known binding mode. We evaluated if a combination of physics-based free energy perturbation (FEP) affinity estimates and protein language model-based protein fitness estimates could improve the in silico identification of resistance mutations. Validation was done with data from deep mutational scanning (DMS) experiments that tested for resistance of single amino acid mutations. A public dataset testing ERK2 resistance against the inhibitor SCH772984 and an internal dataset testing resistance of an EGFR_exon20 mutant against a Bayer small molecule inhibitor were used. Our results show that protein fitness estimates can facilitate the identification of resistance mutations by filtering mutations with low estimated fitness. Even though FEP has flagged such mutations as affinity-decreasing, and thus potentially resistant, they were not resistant according to the DM...