title: Automatic Compound Annotation from Mass Spectrometry Data Using MAGMa.
abstract: The MAGMa software for automatic annotation of mass spectrometry based fragmentation data was applied to 16 MS/MS datasets of the CASMI 2013 contest. Eight solutions were submitted in category 1 (molecular formula assignments) and twelve in category 2 (molecular structure assignment). The MS/MS peaks of each challenge were matched with in silico generated substructures of candidate molecules from PubChem, resulting in penalty scores that were used for candidate ranking. In 6 of the 12 submitted solutions in category 2, the correct chemical structure obtained the best score, whereas 3 molecules were ranked outside the top 5. All top ranked molecular formulas submitted in category 1 were correct. In addition, we present MAGMa results generated retrospectively for the remaining challenges. Successful application of the MAGMa algorithm required inclusion of the relevant candidate molecules, application of the appropriate mass tolerance and a sufficient degree of in silico fragmentation of the candidate molecules. Furthermore, the effect of the exhaustiveness of the candidate lists and limitations of substructure based scoring are discussed.
authors.affiliation: Laboratory of Biochemistry, Wageningen University; Netherlands eScience Center.
authors.forename: Lars
authors.initials: L
authors.lastname: Ridder
authors.affiliation: Glasgow Polyomics, Garscube Estate, University of Glasgow.
authors.forename: Justin J J
authors.initials: JJ
authors.lastname: van der Hooft
authors.affiliation: Netherlands eScience Center.
authors.forename: Stefan
authors.initials: S
authors.lastname: Verhoeven
keywords: MS/MS fragmentation; mass spectrometry; metabolomics; small molecule identification; substructures
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