biostudies-literatureWang FNational Institute of Environmental Health SciencesNatural Sciences and Engineering Research Council of CanadaEesti TeadusagentuurCanadian Institute for Advanced ResearchAlberta Machine Intelligence InstituteNIEHS NIH HHSCanada Foundation for InnovationGenome British ColumbiaGenome CanadaCanadian Institutes of Health ResearchCIHR11692-11700https://www.ebi.ac.uk/biostudies/studies/S-EPMC9064193biostudies-literatureUnknown93(34)In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries, we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for compAnalytical chemistryCFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound Identification.PMC9064193U2C ES030170U2CES030170264PROPUTJD903284MBOWishart DSWang FTian SArndt DLiigand JGreiner RfalseCFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound Identification.In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries, we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for comp2021-01-01T00:00:00Z2021 Aug2025-04-04T09:40:34.994Z2025-04-04T09:40:34.994ZS-EPMC90641933440325610.1021/acs.analchem.1c01465