Rational ab initio Design of a Humanized Nanobody against KRAS using the PIA Method

Rational ab initio Design of a Humanized Nanobody against KRAS using the PIA Method | 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 Research Article Rational ab initio Design of a Humanized Nanobody against KRAS using the PIA Method José Ignacio Peinador Sala This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7239936/v3 This work is licensed under a CC BY 4.0 License Status: Posted Version 3 posted You are reading this latest preprint version Show more versions Abstract The KRAS oncoprotein remains a therapeutic challenge due to the limitations of current covalent inhibitors. This work presents the rational design of PIAKRASv2- Nb, a 100 % humanized nanobody generated via the Protein Interaction Architect (PIA) method, which binds to the DEYDPTIEDS epitope in the Switch I region of KRAS with a high predicted affinity (ipTM = 0.78). Unlike classical approaches, the VHH scaold of PIA-KRASv2-Nb emerged intrinsically humanized (VH3 family, Hu-mAb score = 1.0), eliminating the need for a posteriori engineering. Molecular dynamics simulations, extended up to 10 ns, confirm the persistence of the binding pose and reveal a three-phase mechanism: rapid anchoring, interface maturation, and convergence to a stable equilibrium state with 30 residue-residue contacts. These dynamic metrics are consistent with those observed in successful therapeutic nanobodies like Caplacizumab or VHH72, consolidating the profile of PIA-KRASv2-Nb (seed 72) as a pan-mutant therapeutic candidate against KRAS. This study demonstrates that the PIA method can generate therapeutically optimal nanobodies ab initio, combining high affinity, intrinsic humanization, and conformational reproducibility, with direct implications for tackling targets traditionally considered "undruggable." Biochemical Research Methods Immunology Biophysics Oncology Structural Biology Drug Discovery, Design, & Development Bioinformatics Computational Biology KRAS nanobody computational design protein-protein interactions cancer therapeutics AlphaFold structural biology humanized antibodies switch region in silico validation drug discovery oncoproteins biotherapeutics molecular modeling VH3 framework Full Text Additional Declarations The authors declare no competing interests. Supplementary Files rmsdanalysis10.0ns.csv contactanalysisresiduelevel10.0nsCORRECTED.csv Electrostaticpose.ipynb INTERACTIONANALYSYS.ipynb MDANALYSIS.ipynb MDSIMULATION.ipynb PIAKRASv2NbReportESP.pdf Cite Share Download PDF Status: Posted Version 3 posted You are reading this latest preprint version Show more versions 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. 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Method\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"KRAS, nanobody, computational design, protein-protein interactions, cancer therapeutics, AlphaFold, structural biology, humanized antibodies, switch region, in silico validation, drug discovery, oncoproteins, biotherapeutics, molecular modeling, VH3 framework","lastPublishedDoi":"10.21203/rs.3.rs-7239936/v3","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7239936/v3","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe KRAS oncoprotein remains a therapeutic challenge due to the limitations\u003c/p\u003e\n\u003cp\u003eof current covalent inhibitors. This work presents the rational design of PIAKRASv2-\u003c/p\u003e\n\u003cp\u003eNb, a 100 % humanized nanobody generated via the Protein Interaction\u003c/p\u003e\n\u003cp\u003eArchitect (PIA) method, which binds to the DEYDPTIEDS epitope in the\u003c/p\u003e\n\u003cp\u003eSwitch I region of KRAS with a high predicted affinity (ipTM = 0.78). Unlike\u003c/p\u003e\n\u003cp\u003eclassical approaches, the VHH sca\u001bold of PIA-KRASv2-Nb emerged intrinsically\u003c/p\u003e\n\u003cp\u003ehumanized (VH3 family, Hu-mAb score = 1.0), eliminating the need for a posteriori\u003c/p\u003e\n\u003cp\u003eengineering.\u003c/p\u003e\n\u003cp\u003eMolecular dynamics simulations, extended up to 10 ns, confirm the persistence\u003c/p\u003e\n\u003cp\u003eof the binding pose and reveal a three-phase mechanism: rapid anchoring, interface\u003c/p\u003e\n\u003cp\u003ematuration, and convergence to a stable equilibrium state with \u001830 residue-residue\u003c/p\u003e\n\u003cp\u003econtacts. These dynamic metrics are consistent with those observed in successful\u003c/p\u003e\n\u003cp\u003etherapeutic nanobodies like Caplacizumab or VHH72, consolidating the profile of\u003c/p\u003e\n\u003cp\u003ePIA-KRASv2-Nb (seed 72) as a pan-mutant therapeutic candidate against\u003c/p\u003e\n\u003cp\u003eKRAS.\u003c/p\u003e\n\u003cp\u003eThis study demonstrates that the PIA method can generate therapeutically\u003c/p\u003e\n\u003cp\u003eoptimal nanobodies ab initio, combining high affinity, intrinsic humanization, and\u003c/p\u003e\n\u003cp\u003econformational reproducibility, with direct implications for tackling targets traditionally\u003c/p\u003e\n\u003cp\u003econsidered \"undruggable.\"\u003c/p\u003e","manuscriptTitle":"Rational ab initio Design of a Humanized Nanobody against KRAS using the PIA Method","msid":"","msnumber":"","nonDraftVersions":[{"code":3,"date":"2025-10-07 19:23:35","doi":"10.21203/rs.3.rs-7239936/v3","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":2,"date":"2025-08-29 15:00:04","doi":"10.21203/rs.3.rs-7239936/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2025-07-30 06:43:26","doi":"10.21203/rs.3.rs-7239936/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"413529c8-4c3a-4e78-9a5a-8f934459f15a","owner":[],"postedDate":"October 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55923059,"name":"Biochemical Research Methods"},{"id":55923060,"name":"Immunology"},{"id":55923061,"name":"Biophysics"},{"id":55923062,"name":"Oncology"},{"id":55923063,"name":"Structural Biology"},{"id":55923064,"name":"Drug Discovery, Design, \u0026 Development"},{"id":55923065,"name":"Bioinformatics"},{"id":55923066,"name":"Computational Biology"}],"tags":[],"updatedAt":"2025-07-30T06:43:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-07 19:23:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v3","identity":"rs-7239936","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7239936","identity":"rs-7239936","version":["v3"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}