MAGMa-Based Mass Spectrum Annotation in CASMI 2014

Background: Identification of detected compounds in untargeted LC/MS profiling is a common bottleneck in metabolomics. The CASMI contest challenges mass spectrometry experts and algorithm developers to evaluate how reliable their methods derive molecular formulae and structures from blinded mass spectral data. Objective: The application of the MAGMa software to solve the CASMI 2014 challenges is described. Methods: MAGMa was used to automatically retrieve candidate molecular structures from the HMDB and PubChem chemical databases, based on MS1 precursor m/z values, and to provide a score indicating how well they explain the accurate MS2 spectra. Results: For 40 out of 48 challenges, candidates with the correct molecular formula were ranked on top. For 22 out of 42 challenges the top-ranked candidate also represented the correct chemical structure and in 9 other cases the correct molecule was ranked in the top 10. Conclusion: Advantages and limitations of the approach and consequences with respect to retrieving and scoring of the correct candidates are discussed.