Designs Ras isoform-specific binders using deep learning, enhancing understanding of Ras roles in cancer.
RAS proto-oncogenes encode four major isoforms with substantial sequence homology and similar in vitrobiochemical properties. There is considerable interest in investigating the roles of these proteins independently as their association with different cancers vary, but there are few Ras isoform-specific binding reagents because the only significant sequence differences are in their disordered and highly charged C-termini, which have been difficult to elicit antibodies against. To overcome this limitation, we use deep learning-based methods to design Ras isoform-specific binders (RIBs) for all major Ras isoforms de novo by targeting the Ras C-terminus. The RIBs bind to their target Ras isoforms both in vitro and in cells with remarkable specificity, disrupting their membrane localization, and inhibiting Ras activity. Used as specific inhibitors, the RIBs helped dissect the distinct roles of Ras isoforms during RasG12C inhibitor resistance, illuminating their utility in understanding Ras biology and disease and suggesting potential therapeutic applications. Overall, this study demonstrates the utility of designing proteins as chemical biology tools for understanding basic biology. Citation Format: Jason Z. Zhang. De novo design of Ras isoform selective binders [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RAS Oncogenesis and Therapeutics; 2026 Mar 5-8; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(5_Suppl_1):Abstract nr PR016.
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Jason Z. Zhang (2026) studied this question.
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