title: Solving CASMI 2013 with MetFrag, MetFusion and MOLGEN-MS/MS.
abstract: The second Critical Assessment of Small Molecule Identification (CASMI) contest took place in 2013. A joint team from the Swiss Federal Institute of Aquatic Science and Technology (Eawag) and Leibniz Institute of Plant Biochemistry (IPB) participated in CASMI 2013 with an automatic workflow-style entry. MOLGEN-MS/MS was used for Category 1, molecular formula calculation, restricted by the information given for each challenge. MetFrag and MetFusion were used for Category 2, structure identification, retrieving candidates from the compound databases KEGG, PubChem and ChemSpider and joining these lists pre-submission. The results from Category 1 were used to guide whether formula or exact mass searches were performed for Category 2. The Category 2 results were impressive considering the database size and automated regime used, although these could not compete with the manual approach of the contest winner. The Category 1 results were affected by large m/z and ppm values in the challenge data, where strategies beyond pure enumeration from other participants were more successful. However, the combination used for the CASMI 2013 entries was extremely useful for developing decision-making criteria for automatic, high throughput general unknown (non-target) identification and for future contests.
authors.affiliation: Eawag: Swiss Federal Institute of Aquatic Science and Technology.
authors.forename: Emma L
authors.initials: EL
authors.lastname: Schymanski
authors.affiliation: Leibniz Institute of Plant Biochemistry, Department of Stress and Developmental Biology.
authors.forename: Michael
authors.initials: M
authors.lastname: Gerlich
authors.affiliation: Leibniz Institute of Plant Biochemistry, Department of Stress and Developmental Biology.
authors.forename: Christoph
authors.initials: C
authors.lastname: Ruttkies
authors.affiliation: Leibniz Institute of Plant Biochemistry, Department of Stress and Developmental Biology.
authors.forename: Steffen
authors.initials: S
authors.lastname: Neumann
keywords: chemical clustering; computational mass spectrometry; maximum common substructure; small molecule identification
references.citation: Curr Pharm Des. 2006;12(17):2111-20
references.pmid: 16796559
references.citation: Anal Bioanal Chem. 2010 Jun;397(3):943-51
references.pmid: 20232059
references.citation: BMC Bioinformatics. 2010 Mar 22;11:148
references.pmid: 20307295
references.citation: J Mass Spectrom. 2010 Jul;45(7):703-14
references.pmid: 20623627
references.citation: J Cheminform. 2011 May 16;3:18
references.pmid: 21575202
references.citation: J Cheminform. 2011 Oct 07;3:33
references.pmid: 21982300
references.citation: J Am Soc Mass Spectrom. 2012 Jan;23(1):179-85
references.pmid: 22069037
references.citation: PLoS One. 2011;6(12):e28966
references.pmid: 22194963
references.citation: J Chem Inf Model. 2013 Mar 25;53(3):601-12
references.pmid: 23330685
references.citation: J Mass Spectrom. 2013 Mar;48(3):291-8
references.pmid: 23494783
references.citation: Nucleic Acids Res. 2014 Jan;42(Database issue):D199-205
references.pmid: 24214961
references.citation: Metabolites. 2013 May 21;3(2):397-411
references.pmid: 24957998
references.citation: Metabolites. 2013 May 24;3(2):412-39
references.pmid: 24957999
references.citation: Metabolites. 2013 May 28;3(2):440-62
references.pmid: 24958000
references.citation: Metabolites. 2013 Jun 13;3(2):506-16
references.pmid: 24958003
references.citation: Metabolites. 2013 Aug 05;3(3):623-36
references.pmid: 24958142
references.citation: Mass Spectrom (Tokyo). 2014;3(Spec Iss 2):S0039
references.pmid: 26819882