Cycle-MS: A Closed-Loop End-to-End Framework for Mass Spectrometry Structure Elucidation
Mass spectrometry (MS) is indispensable for molecular analysis; however, elucidating complex molecular structures from spectra remains a major challenge. Here, we present Cycle-MS, an end-to-end framework that unifies inverse spectrum-to-molecule prediction with forward spectrum reconstruction, with cycle-consistency losses refining latent representations. Cycle-MS demonstrates enhanced accuracy in predicting atomic compositions, molecular formulas, scaffolds, and functional groups, offering robust recovery of molecular scale and key chemical features. Interpretability analysis shows that Cycle-MS prioritizes structurally diagnostic fragments over nonspecific abundant peaks, ensuring chemical plausibility and structural reliability. Together, these advances establish Cycle-MS as a robust, accurate, and interpretable framework that offers a path toward fully automated, high-precision MS-based structure elucidation.
Authors
- Jinglong Lin
- Hui Li (ORCID: https://orcid.org/0000-0001-9198-3951)
- Fanyang Mo
- Zhiyuan Yan
- Chengchun Liu
- Li Yuan
Institutions
- Peking University (CN)
- Peking University Shenzhen Hospital (CN)
- Preferred Networks (Japan) (JP)
Publication Details
- Journal
- Journal of Chemical Information and Modeling
- Published
- 2026-02-25
- DOI
- https://doi.org/10.1021/acs.jcim.5c02981
- Primary Topic
- Mass Spectrometry Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00