CFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound Identification

作者：Fei Wang, Jaanus Liigand, Siyang Tian, David Arndt, Russell Greiner, David S. Wishart · 发表于：Analytical Chemistry · 年份：2021 · DOI：10.1021/acs.analchem.1c01465 · 被引用次数：417 · 研究领域：Metabolomics and Mass Spectrometry Studies、Advanced Chemical Sensor Technologies、Analytical Chemistry and Chromatography

mass-spectrum-to-compound identification. This work improves CFM-ID's ability to predict ESI-MS/MS spectra from compounds by (1) learning parameters from features based on the molecular topology, (2) adding a new approach to ring cleavage that models such cleavage as a sequence of simple chemical bond dissociations, and (3) expanding its hand-written rule-based predictor to cover more chemical classes, including acylcarnitines, acylcholines, flavonols, flavones, flavanones, and flavonoid glycosides. We demonstrate that this new version of CFM-ID (version 4.0) is significantly more accurate than previous CFM-ID versions in terms of both EI-MS/MS spectral prediction and compound identification. CFM-ID 4.0 is available at http://cfmid4.wishartlab.com/ as a web server and docker images can be downloaded at https://hub.docker.com/r/wishartlab/cfmid.