METLIN 960 K represents the largest collection of experimentally acquired small-molecule MS/MS spectra currently available. We introduce a reengineered publicaly accessible METLIN platform integrating high-resolution tandem mass spectrometry (MS/MS) data for over 960,000 empirically validated molecular standards. This scale was enabled by a high-throughput experimental framework integrating acoustic droplet ejection with high-throughput LC-MS/MS acquisition, allowing systematic empirical generation of MS/MS spectra from authentic standards. In addition to scale, METLIN 960 K provides a uniquely standardized MS/MS data set, with spectra acquired under controlled and consistent conditions across ionization modes and collision energies, enabling reproducible spectral comparison and machine-learning applications. Each compound is characterized by MS/MS spectra acquired in both positive and negative ionization modes across four collision energies (0, 10, 20, and 40 eV), enabling comprehensive fragmentation coverage and improved structural annotation. Designed as a reference library for XCMS-METLIN and compatible with machine-learning workflows, METLIN 960 K supports high-fidelity spectral matching, neutral loss analysis, and filtering of misannotations, including annotation of in-source fragments and biologically synchronized ranking of candidate metabolites. The platform also provides empirically derived MRM transitions on all standards (via METLIN-MRM), supporting quantitative method development across a chemically diverse range of metabolites, natural products, lipids, peptides, pharmaceuticals, and toxicants. A redesigned interface enables efficient querying by exact mass, formula, or structure with direct access to curated spectra and metadata. Two additional resources enhance identification: (1) METLIN Core, a high-frequency-use subset for rapid searching, and (2) > 1.02 million additional structures without MS/MS data for hypothesis generation. Derived exclusively from authentic standards, METLIN 960 K (https://metlin.scripps.edu) provides the largest publicly available empirical MS/MS database, delivering high-confidence annotation for both untargeted and targeted mass spectrometry workflows.
Uritboonthai et al. (Tue,) studied this question.