Learning interpretable structural similarity from tandem mass spectra for small molecule analog discovery
Piedrahita Giraldo, J. S.; Da Silva, K. M.; Zare Shahneh, M. R.; Wang, M.; Laukens, K.; De Vijlder, T.; Bittremieux, W.
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Analog discovery remains a central bottleneck in mass spectrometry-based untargeted metabolomics, as conventional spectral similarity scores poorly reflect molecular structure. We introduce SIMBA, a transformer-based model that infers two interpretable graph-based distances, maximum common edge subgraph and substructure edit distance, directly from tandem mass spectra. SIMBA consistently retrieves structurally closer analogs than existing methods, enabling structure-aware small molecule identification beyond exact spectral matching.
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