A Two-Stage Fragment-Connection Framework for Infrared-Spectrum-Driven Molecular Structure Elucidation

A Two-Stage Fragment-Connection Framework for Infrared-Spectrum-Driven Molecular Structure Elucidation | 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 A Two-Stage Fragment-Connection Framework for Infrared-Spectrum-Driven Molecular Structure Elucidation Limin Yu, Qingyu Zhou, Zhenghui Pan, Jing Wang, Yanqi Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9357067/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 4 You are reading this latest preprint version Abstract Structure elucidation of molecules from infrared spectra is difficult because the number of possible solutions is very large, direct end-to-end generation is hard to learn, and training is often unstable. In this work, we present a two-stage approach that encodes molecules as Breaking of Retrosynthetically Interesting Chemical Substructures (BRICS) fragments, learns fragment representations from infrared spectra, and then frames the structure elucidation task as a spectrum-based fragment-connection prediction problem between fragment pairs. A complexity-controlled evaluation protocol is proposed to minimize distortion caused by simple molecules with small numbers of fragment nodes. Oracle-fragment and strict-vocabulary analyses further separate fragment-coverage errors from connection errors. The proposed approach successfully produces valid structures and competitive hit rates. Results under the strict-vocabulary protocol show that fragment coverage remains a significant bottleneck, while results in the oracle-fragment setting show improved hit rates but not reduced reconstruction errors, confirming the existence of a dual bottleneck. Finally, the plateau observed between the 5.8k and 63.0k datasets suggests that the primary source of error shifts from fragment coverage and local prediction to higher-order discrimination and ranking for molecular connection generation as data size and molecular complexity increase. In summary, improving structure elucidation guided by infrared spectra requires not only state-of-the-art neural models but also suitable structural abstractions, controlled decoding, and evaluation measures that better reveal reconstruction bottlenecks. Infrared spectra Fragment-based molecular representation Pairwise connection prediction Constrained fragment assembly Structure elucidation Full Text Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 12 May, 2026 Editor assigned by journal 19 Apr, 2026 Submission checks completed at journal 13 Apr, 2026 First submitted to journal 08 Apr, 2026 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-9357067","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619655100,"identity":"5891285c-9176-4cc9-be2b-2dacd42f3dfc","order_by":0,"name":"Limin Yu","email":"","orcid":"","institution":"Tianjin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Limin","middleName":"","lastName":"Yu","suffix":""},{"id":619655101,"identity":"28b47756-f94f-43fa-9453-4fe452cb6762","order_by":1,"name":"Qingyu Zhou","email":"","orcid":"","institution":"Tianjin Medical 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In this work, we present a two-stage approach that encodes molecules as Breaking of Retrosynthetically Interesting Chemical Substructures (BRICS) fragments, learns fragment representations from infrared spectra, and then frames the structure elucidation task as a spectrum-based fragment-connection prediction problem between fragment pairs. A complexity-controlled evaluation protocol is proposed to minimize distortion caused by simple molecules with small numbers of fragment nodes. Oracle-fragment and strict-vocabulary analyses further separate fragment-coverage errors from connection errors.\u003c/p\u003e \u003cp\u003eThe proposed approach successfully produces valid structures and competitive hit rates. Results under the strict-vocabulary protocol show that fragment coverage remains a significant bottleneck, while results in the oracle-fragment setting show improved hit rates but not reduced reconstruction errors, confirming the existence of a dual bottleneck. Finally, the plateau observed between the 5.8k and 63.0k datasets suggests that the primary source of error shifts from fragment coverage and local prediction to higher-order discrimination and ranking for molecular connection generation as data size and molecular complexity increase. 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