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An overview of tools, software, and methods for natural product fragment and mass spectral analysis

  • Aurélien F. A. Moumbock EMAIL logo , Fidele Ntie-Kang EMAIL logo , Sergi H. Akone , Jianyu Li , Mingjie Gao , Kiran K. Telukunta and Stefan Günther
Published/Copyright: June 28, 2019
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Abstract

One major challenge in natural product (NP) discovery is the determination of the chemical structure of unknown metabolites using automated software tools from either GC–mass spectrometry (MS) or liquid chromatography–MS/MS data only. This chapter reviews the existing spectral libraries and predictive computational tools used in MS-based untargeted metabolomics, which is currently a hot topic in NP structure elucidation. We begin by focusing on spectral databases and the general workflow of MS annotation. We then describe software and tools used in MS, particularly those used to predict fragmentation patterns, mass spectral classifiers, and tools for fragmentation trees analysis. We then round up the chapter by looking at more advanced approaches implemented in tools for competitive fragmentation modeling and quantum chemical approaches.

Acknowledgements

AFAM was supported by a doctoral research grant from the German Academic Exchange Service (DAAD). FNK acknowledges a return fellowship and an equipment subsidy from the Alexander von Humboldt Foundation, Germany. Financial support for this work is acknowledged from a ChemJets fellowship from the Ministry of Education, Youth and Sports of the Czech Republic awarded to FNK. JL was supported by the German National Research Foundation [DFG, Research Training Group 1976] and by the Baden-Württemberg Foundation [BWST_WSF-043].

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Published Online: 2019-06-28

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