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.
Lin et al. (Wed,) studied this question.