Integrating Quantum Mechanics into Protein-Ligand Docking: Toward Higher Accuracy and Reliability

Integrating Quantum Mechanics into Protein-Ligand Docking: Toward Higher Accuracy and Reliability | 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 Integrating Quantum Mechanics into Protein-Ligand Docking: Toward Higher Accuracy and Reliability Laszlo Fusti-Molnar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5433993/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract I introduce two new methods, QFVina and QFVinardo, for protein-ligand docking that leverage precomputed high-quality conformational libraries with QM-optimized geometries and ab initio DFT-D4-based conformational rankings and strain energies. These methods provide greater accuracy in docking-based virtual screening by addressing the inaccuracies in intramolecular relative energies of conformations, a critical component often misrepresented in flexible ligand docking calculations. I demonstrate that numerous force field-based methods widely used today exhibit substantial errors in conformational relative energies, and that it is unrealistic to expect better accuracy from the faster scoring functions typically employed in docking. Consistent with these findings, I show that traditional flexible ligand docking often produces geometries with significant strain energies and large deviations, with magnitudes comparable to the protein-ligand binding energies themselves and much larger than the differences we aim to estimate in docking hitlists. By using physically realistic ligand conformations with accurate strain energies in the scoring function, QFVina and QFVinardo produce markedly different docking results, even with the same docking parameters and scoring functions for protein-ligand interaction energies. I analyzed these differences in docking hitlists and selected protein-ligand interactions using three protein targets from COVID-19 research. Full Text Additional Declarations No competing interests reported. Supplementary Files QFDockingCovid19Paper1CSVs.tar.gz Cite Share Download PDF Status: Posted 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. 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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-5433993","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":385030193,"identity":"c807cf6d-103c-4111-b4a6-6b9a24b1e5a3","order_by":0,"name":"Laszlo Fusti-Molnar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYBACAxDxgMGGgb2BgeEA8VoSGNIYeA6QqOUwWAuRDmM//vhDQsV52R7+ww8PfNxhJyffwPzw0Q18WnhyDAwSztw27pFIMzg480yyscEBNmPjHLwOy2FISGy7nbhfgofhMG/bgcQNDDxs0ni18D9/cCCx7VxiD/8ZhsN/2w7Uz28gpEUiwbAhEWh4D9C6w4xtBxIYDhDU8saYIQHoBbBfetuSDTccJuAX+/70xx8+VNiBQuzxh59tdvLy7c0PH+PTAgOMDXAmMxHK0bSMglEwCkbBKEADAFiAT7U3tTvfAAAAAElFTkSuQmCC","orcid":"","institution":"QuantumFuture Scientific Buda","correspondingAuthor":true,"prefix":"","firstName":"Laszlo","middleName":"","lastName":"Fusti-Molnar","suffix":""}],"badges":[],"createdAt":"2024-11-11 18:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5433993/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5433993/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73243922,"identity":"8f517a94-a79f-4538-9d90-139b5208727e","added_by":"auto","created_at":"2025-01-08 06:46:59","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2869525,"visible":true,"origin":"","legend":"","description":"","filename":"QFDocking1v2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5433993/v1_covered_6a8605ea-90dc-409f-bcae-1c47aec673aa.pdf"},{"id":70660691,"identity":"2d7ac94a-04bd-494d-b355-a507b2196210","added_by":"auto","created_at":"2024-12-05 10:51:35","extension":"gz","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":9454,"visible":true,"origin":"","legend":"","description":"","filename":"QFDockingCovid19Paper1CSVs.tar.gz","url":"https://assets-eu.researchsquare.com/files/rs-5433993/v1/d9b9bed971e9f558673209ba.gz"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrating Quantum Mechanics into Protein-Ligand Docking: Toward Higher Accuracy and Reliability","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-5433993/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5433993/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eI introduce two new methods, QFVina and QFVinardo, for protein-ligand docking that leverage precomputed high-quality conformational libraries with QM-optimized geometries and \u003cem\u003eab initio\u003c/em\u003e DFT-D4-based conformational rankings and strain energies. 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