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

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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-017-0219-x) contains supplementary material, which is available to authorized users.

Comparative Evaluation of Data Dependent and Data Independent Acquisition Workflows Implemented on an Orbitrap Fusion for Untargeted Metabolomics

“…Thus, despite fluctuations in the relative intensity of some fragment ions can be observed, a DP score > ~500 seems sufficient to retain high confidence in metabolite identification ( Figure 2). Our results are in good agreement with those of Blazenovic et al who found that a dot product score threshold of 400 gave the best results on a training dataset of more than 300 MS/MS spectra, within the frame of the Critical Assessment of Small Molecule Identification (CASMI) contest [34]. Each 10-fold dilution of test mix concentration (from 100 to 10 and then 1 ng/mL) resulted as expected in a 15-20% drop of the MS/MS triggering Table S2).…”

Annotation: A Computational Solution for Streamlining Metabolomics Analysis

“…Defined fragmentation rules are used in proteomics which allows accurate in-silico MS/MS predictions, but due to the high chemical diversity of metabolites, existing rules to model CID behavior are not sufficiently accurate [71]. In-silico MS/MS data in metabolomics are usually generated from heuristic approaches that predict fragmentation routes by indirectly estimating bond dissociation energies.…”

MESSAR: Automated recommendation of metabolite substructures from tandem mass spectra

“…compounds that have not been structurally described yet and are therefore not present in any molecular database. As a result typically only a fraction of compounds can be identified correctly [13].…”