All-at-once RNA folding with 3D motif prediction framed by evolutionary information

All-at-once RNA folding with 3D motif prediction framed by evolutionary information | 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 All-at-once RNA folding with 3D motif prediction framed by evolutionary information Elena Rivas, Aayush Karan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5664139/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Oct, 2025 Read the published version in Nature Methods → Version 1 posted You are reading this latest preprint version Abstract Structural RNAs exhibit a vast array of recurrent short 3D elements involving non-Watson-Crick interactions that help arrange canonical double helices into tertiary structures. We present CaCoFold-R3D, a probabilistic grammar that predicts these RNA 3D motifs (also termed modules) jointly with RNA secondary structure over a sequence or alignment. CaCoFold-R3D uses evolutionary information present in an RNA alignment to reliably identify canonical helices (including pseudoknots) by covariation. We further introduce the R3D grammars, which also exploit helix covariation that constrains the positioning of the mostly non-covarying RNA 3D motifs. Our method runs predictions over an almost-exhaustive list of over fifty known RNA motifs (everything). Motifs can appear in any non-helical loop region (including 3-way, 4-way and higher junctions) (everywhere). All structural motifs as well as the canonical helices are arranged into one single structure predicted by one single joint probabilistic grammar (all-at-once). Our results demonstrate that CaCoFold-R3D is a valid alternative for predicting the all-residue interactions present in a RNA 3D structure. Furthermore, CaCoFold-R3D is fast and easily customizable for novel motif discovery. Biological sciences/Computational biology and bioinformatics/Computational models Biological sciences/Molecular biology/Non-coding RNAs Biological sciences/Molecular biology/Riboswitches Biological sciences/Computational biology and bioinformatics/Machine learning Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Published Journal Publication published 03 Oct, 2025 Read the published version in Nature Methods → 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-5664139","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":400114050,"identity":"5043d54e-3091-46cc-a1bb-1857aed8b8a0","order_by":0,"name":"Elena Rivas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIiWNgGAWjYDACdjApAcTMBz4AyQSIMBsQH8ChhRmuhS1xBilaQIDHkDgt/MzMxx783GOR2N9/5mPDjz8Mefyzzxh+rihjkOO7kYBVi2QzW7phzzOJxBk3cjc29rYxFEucyzGWPHOOwVgShxaDwzxmEjwHJIwZbvBuf8DbwJDYcIYtQbKxjSFxAw4t9of5v0n+AWqRP3/mYeOfPwyJ88+wJf8EaqnHpcWAmYdNGmiLnMGBHMZmHjag4WeYj4FsSTDAoUXiMJuZtAxQi+GNNMNm2TaJxI1ALZYN5yQMZ555gD3E2pufSb45UMcjd/7ww8Y3f2wS551hbL7ZUGYjz3ccuy0YtmIwRsEoGAWjYBSQAQC9VmFBctHw5gAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-2084-269X","institution":"Harvard University","correspondingAuthor":true,"prefix":"","firstName":"Elena","middleName":"","lastName":"Rivas","suffix":""},{"id":400114051,"identity":"a09b9737-a8b7-49c0-bead-64d2d02145da","order_by":1,"name":"Aayush Karan","email":"","orcid":"","institution":"Harvard University","correspondingAuthor":false,"prefix":"","firstName":"Aayush","middleName":"","lastName":"Karan","suffix":""}],"badges":[],"createdAt":"2024-12-17 18:36:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5664139/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5664139/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41592-025-02833-w","type":"published","date":"2025-10-03T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":92761464,"identity":"04b7664d-3351-4050-bf5f-9546ac61bc68","added_by":"auto","created_at":"2025-10-04 07:05:35","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1770337,"visible":true,"origin":"","legend":"Article File","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5664139/v1_covered_11b0660a-819a-4e7d-8102-74d28bf681e8.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"All-at-once RNA folding with 3D motif prediction framed by evolutionary information","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5664139/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5664139/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Structural RNAs exhibit a vast array of recurrent short 3D elements involving non-Watson-Crick interactions that help arrange canonical double helices into tertiary structures. 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