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      MetFrag relaunched: incorporating strategies beyond in silico fragmentation.

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          Abstract

          The in silico fragmenter MetFrag, launched in 2010, was one of the first approaches combining compound database searching and fragmentation prediction for small molecule identification from tandem mass spectrometry data. Since then many new approaches have evolved, as has MetFrag itself. This article details the latest developments to MetFrag and its use in small molecule identification since the original publication.

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          MassBank: a public repository for sharing mass spectral data for life sciences.

          Hisayuki Horai, Masanori Arita, Shigehiko Kanaya … (2010)
          MassBank is the first public repository of mass spectra of small chemical compounds for life sciences (<3000 Da). The database contains 605 electron-ionization mass spectrometry (EI-MS), 137 fast atom bombardment MS and 9276 electrospray ionization (ESI)-MS(n) data of 2337 authentic compounds of metabolites, 11 545 EI-MS and 834 other-MS data of 10,286 volatile natural and synthetic compounds, and 3045 ESI-MS(2) data of 679 synthetic drugs contributed by 16 research groups (January 2010). ESI-MS(2) data were analyzed under nonstandardized, independent experimental conditions. MassBank is a distributed database. Each research group provides data from its own MassBank data servers distributed on the Internet. MassBank users can access either all of the MassBank data or a subset of the data by specifying one or more experimental conditions. In a spectral search to retrieve mass spectra similar to a query mass spectrum, the similarity score is calculated by a weighted cosine correlation in which weighting exponents on peak intensity and the mass-to-charge ratio are optimized to the ESI-MS(2) data. MassBank also provides a merged spectrum for each compound prepared by merging the analyzed ESI-MS(2) data on an identical compound under different collision-induced dissociation conditions. Data merging has significantly improved the precision of the identification of a chemical compound by 21-23% at a similarity score of 0.6. Thus, MassBank is useful for the identification of chemical compounds and the publication of experimental data. 2010 John Wiley & Sons, Ltd.
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            The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo-and Bioinformatics

            Christoph Steinbeck, Yongquan Han, Stefan Kuhn … (2003)
            The Chemistry Development Kit (CDK) is a freely available open-source Java library for Structural Chemo-and Bioinformatics. Its architecture and capabilities as well as the development as an open-source project by a team of international collaborators from academic and industrial institutions is described. The CDK provides methods for many common tasks in molecular informatics, including 2D and 3D rendering of chemical structures, I/O routines, SMILES parsing and generation, ring searches, isomorphism checking, structure diagram generation, etc. Application scenarios as well as access information for interested users and potential contributors are given.
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              Searching molecular structure databases with tandem mass spectra using CSI:FingerID.

              Kai Dührkop, Huibin Shen, Marvin Meusel … (2015)
              Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin.
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                Author and article information

                Journal
                Journal ID (iso-abbrev): J Cheminform
                Title: Journal of cheminformatics
                Publisher: Springer Nature
                ISSN (Print): 1758-2946
                Publication date (Electronic): 2016
                Volume: 8
                Affiliations
                [1 ] Leibniz Institute of Plant Biochemistry, Department of Stress and Developmental Biology, Weinberg 3, 06120 Halle, Germany.
                [2 ] Eawag: Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland.
                [3 ] Leibniz Institute of Plant Biochemistry, Department of Stress and Developmental Biology, Weinberg 3, 06120 Halle, Germany ; R&D NMR Software, Bruker BioSpin GmbH, Silberstreifen, 76287 Rheinstetten, Germany.
                [4 ] Eawag: Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland ; Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, 8092 Zürich, Switzerland.
                Article
                Publisher Item ID: 115
                DOI: 10.1186/s13321-016-0115-9
                PMC ID: 4732001
                PubMed ID: 26834843
                SO-VID: ca9041f5-a8b5-46f4-bc14-f1a3d0568641
                History

                Keywords: Compound identification,High resolution mass spectrometry,In silico fragmentation,Metabolomics,Structure elucidation
                Data availability:
                Keywords: Compound identification, High resolution mass spectrometry, In silico fragmentation, Metabolomics, Structure elucidation

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