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. 2017 May 25;9(1):32.
doi: 10.1186/s13321-017-0219-x.

Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy

Ivana Blaženović  1   2   3 , Tobias Kind  3 , Hrvoje Torbašinović  4 , Slobodan Obrenović  4 , Sajjan S Mehta  3 , Hiroshi Tsugawa  5 , Tobias Wermuth  3 , Nicolas Schauer  2 , Martina Jahn  1 , Rebekka Biedendieck  1 , Dieter Jahn  1 , Oliver Fiehn  6   7
Affiliations

Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy

Ivana Blaženović et al. J Cheminform. .

Abstract

In mass spectrometry-based untargeted metabolomics, rarely more than 30% of the compounds are identified. Without the true identity of these molecules it is impossible to draw conclusions about the biological mechanisms, pathway relationships and provenance of compounds. The only way at present to address this discrepancy is to use in silico fragmentation software to identify unknown compounds by comparing and ranking theoretical MS/MS fragmentations from target structures to experimental tandem mass spectra (MS/MS). We compared the performance of four publicly available in silico fragmentation algorithms (MetFragCL, CFM-ID, MAGMa+ and MS-FINDER) that participated in the 2016 CASMI challenge. We found that optimizing the use of metadata, weighting factors and the manner of combining different tools eventually defined the ultimate outcomes of each method. We comprehensively analysed how outcomes of different tools could be combined and reached a final success rate of 93% for the training data, and 87% for the challenge data, using a combination of MAGMa+, CFM-ID and compound importance information along with MS/MS matching. Matching MS/MS spectra against the MS/MS libraries without using any in silico tool yielded 60% correct hits, showing that the use of in silico methods is still important.

Keywords: Compound identification; In silico fragmentation; MS/MS; Mass spectrometry; Metabolomics; Structure elucidation.

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Figures

Fig. 1
Fig. 1
Structure elucidation workflow of small molecules. a In silico fragmentation can be used to identify and rank unknown MS/MS spectra by matching theoretical fragments to experimental MS/MS spectra. b The voting/consensus combines the output of multiple in silico fragmentation tools, uses compound and MS/MS databases lookups to further boost compound ranks
Fig. 2
Fig. 2
Principal component analysis of the molecular descriptor space from the training and validation sets. Individual outliers show compounds only found in a specific data set. Overlapping dots show very similar compounds
Fig. 3
Fig. 3
Comparison of the accuracy of compound annotations obtained by in silico fragmentation tools alone and in combination with metadata for both CASMI data sets
See this image and copyright information in PMC

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