Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control

Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control | 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 Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control Denis POMPON, Luis F. GARCIA-ALLES, Philippe URBAN This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5197791/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Mar, 2025 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Cytochrome P450 1A2, as many isoenzymes, can generate multiple metabolites from a single substrate. A loose coupling between substrate binding and oxygen activation makes possible substrate reorientations at the active site prior to catalysis. In the present work, caffeine oxidation to alternative bioactive compounds was used to decipher this pluripotency. A model involving two interacting subsites capable of sequentially accommodating one or two caffeine molecules was considered. Molecular dynamics was used to characterize subsite interactions and feed a dedicated geometric encoding of trajectories that was coupled to dimensional reductions and differential machine learning. The two subsites differentially control caffeine orientations and can exchange substrate through a phenylalanine gated mechanism. This exchange can be locked by the presence of a second bound molecule. Complementary roles of subsites in progressively determining the caffeine orientation during its approach to active oxygen were examined. Interestingly, substrate face flipping becomes impaired upon entry into the rather flat active site. This makes the mechanisms that define the orientation of caffeine relative to active oxygen dependent on the substrate face oriented toward heme. Globally, this evidenced that P450 1A2 regioselectivity results from local determinants combined with subsite interactions and caffeine face preselection at a longer distance Biological sciences/Biochemistry Biological sciences/Computational biology and bioinformatics deep learning molecular dynamic geometric encoding P450 caffeine regioselectivity Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementInformPOMPOND.docx Cite Share Download PDF Status: Published Journal Publication published 03 Mar, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 03 Dec, 2024 Reviews received at journal 29 Nov, 2024 Reviews received at journal 21 Nov, 2024 Reviewers agreed at journal 15 Nov, 2024 Reviews received at journal 04 Nov, 2024 Reviewers agreed at journal 26 Oct, 2024 Reviewers agreed at journal 24 Oct, 2024 Reviewers invited by journal 24 Oct, 2024 Editor assigned by journal 21 Oct, 2024 Editor invited by journal 20 Oct, 2024 Submission checks completed at journal 18 Oct, 2024 First submitted to journal 03 Oct, 2024 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. 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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-5197791","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":385540072,"identity":"6ad6a24a-e069-40de-9ac7-9b7daced6dd9","order_by":0,"name":"Denis POMPON","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIie3QPQuCQBzH8V8EtljziT28hYsDKfDFnIsuRU3hKATXErX6PnoDgeTkCwhsiaBZaHFwqNBo6bKx4b7LHX/4cA+ASvWP7culr70GnWpQS1hJOFBZVkuc4GfSSZeH3dw/eRtzdc4aue2I1pplGehMRoxT7KZhcp2KbsIIuOsIPbGMEHQcSAg9Tqy0LaKpIBOYBY+cx8Zq6iio7JQX8TTiXXKUhN0K0FrCNcItUhFq4gup3hINn/cZwXWZ0OOFsaZy8vixOJ370WAQepcjbLu3bS13We7LCQjQ/HRhKZASlUqlUr27A4uOVG7nwZZXAAAAAElFTkSuQmCC","orcid":"","institution":"Université de Toulouse, CNRS, INRAE, INSA","correspondingAuthor":true,"prefix":"","firstName":"Denis","middleName":"","lastName":"POMPON","suffix":""},{"id":385540073,"identity":"821ffedd-4c6c-43d8-86fc-fb89f0f58acd","order_by":1,"name":"Luis F. 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