Programmable Protein Stabilization with Language Model-Derived Peptide Guides

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Programmable Protein Stabilization with Language Model-Derived Peptide Guides | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Programmable Protein Stabilization with Language Model-Derived Peptide Guides Lauren Hong, Tianzheng Ye, Tian Wang, Divya Srijay, Lin Zhao, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4670386/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Apr, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Dysregulated protein degradation via the ubiquitin-proteasomal pathway can induce numerous disease phenotypes, including cancer, neurodegeneration, and diabetes. Stabilizing improperly ubiquitinated proteins via target-specific deubiquitination is thus a critical therapeutic goal. Building off the major advances in targeted protein degradation (TPD) using bifunctional small-molecule degraders, targeted protein stabilization (TPS) modalities have been described recently. However, these rely on a limited set of chemical linkers and warheads, which are difficult to generate de novo for new targets and do not exist for classically “undruggable” targets. To address the limited reach of small molecule-based degraders, we previously engineered ubiquibodies (uAbs) by fusing computationally-designed “guide” peptides to E3 ubiquitin ligase domains for modular, CRISPR-analogous TPD. Here, we expand the TPS target space by engineering “deubiquibodies” (duAbs) via fusion of computationally-designed guides to the catalytic domain of the potent OTUB1 deubiquitinase. In human cells, duAbs effectively stabilize exogenous and endogenous proteins in a DUB-dependent manner. To demonstrate duAb modularity, we swap in new target-binding peptides designed via our generative language models to stabilize diverse target proteins, including key tumor suppressor proteins such as p53 and WEE1, as well as heavily-disordered fusion oncoproteins, such as PAX3::FOXO1. In total, our duAb system represents a simple, programmable, CRISPR-analogous strategy for TPS. Biological sciences/Biochemistry/Proteins/Ubiquitylated proteins Biological sciences/Biotechnology/Molecular engineering/Protein design Full Text Additional Declarations Yes there is potential Competing Interest. P.C., L.H., and M.P.D. are listed as inventors on US Patent Application 63/541,921: “Peptide-Guided Protein Stabilizers and Uses Thereof”. P.C. and M.D. are co-founded of UbiquiTx, Inc., which commercializes genetically-encoded proteome editing technologies, and are co-inventors of duAb patents. P.C.’s interests are reviewed and managed by Duke University in accordance with their conflict-of-interest policies. M.P.D.’s interests are reviewed and managed by Cornell University in accordance with their conflict-of-interest policies. Supplementary Files duAbsupplement.pdf Supplementary Information Cite Share Download PDF Status: Published Journal Publication published 15 Apr, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4670386","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":331349496,"identity":"c739a8af-a2ce-40cc-b93a-518d14e21802","order_by":0,"name":"Lauren Hong","email":"","orcid":"https://orcid.org/0000-0002-1675-4806","institution":"Duke University","correspondingAuthor":false,"prefix":"","firstName":"Lauren","middleName":"","lastName":"Hong","suffix":""},{"id":331349497,"identity":"946811a1-4df2-43f2-b8e8-4d6aab5a3a4f","order_by":1,"name":"Tianzheng Ye","email":"","orcid":"","institution":"Cornell 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