MS<sup>n</sup>Lib: efficient generation of open multi-stage fragmentation mass spectral libraries.

Brungs, Corinna; Schmid, Robin; Heuckeroth, Steffen; Mazumdar, Aninda; Drexler, Matúš; Šácha, Pavel; Dorrestein, Pieter C; Petras, Daniel et al. · Nat Methods · 2025

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Abstract

Untargeted high-resolution mass spectrometry is a key tool in clinical metabolomics, natural product discovery and exposomics, with compound identification remaining the major bottleneck. Currently, the standard workflow applies spectral library matching against tandem mass spectrometry (MS<sup>2</sup>) fragmentation data. Multi-stage fragmentation (MS<sup>n</sup>) yields more profound insights into substructures, enabling validation of fragmentation pathways; however, the community lacks open MS<sup>n</sup> reference data of diverse natural products and other chemicals. Here we describe MS<sup>n</sup>Lib, a machine learning-ready open resource of >2 million spectra in MS<sup>n</sup> trees of 30,008 unique small molecules, built with a high-throughput data acquisition and processing pipeline in the open-source software mzmine.

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