Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics

Ivana Blaženović, Tobias Kind, Jian Ji, Oliver Fiehn
<span title="2018-05-10">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ie7tehbfsfhs5pdyyt2rrdmnpm" style="color: black;">Metabolites</a> </i> &nbsp;
The annotation of small molecules remains a major challenge in untargeted mass spectrometry-based metabolomics. We here critically discuss structured elucidation approaches and software that are designed to help during the annotation of unknown compounds. Only by elucidating unknown metabolites first is it possible to biologically interpret complex systems, to map compounds to pathways and to create reliable predictive metabolic models for translational and clinical research. These strategies
more &raquo; ... clude the construction and quality of tandem mass spectral databases such as the coalition of MassBank repositories and investigations of MS/MS matching confidence. We present in silico fragmentation tools such as MS-FINDER, CFM-ID, MetFrag, ChemDistiller and CSI:FingerID that can annotate compounds from existing structure databases and that have been used in the CASMI (critical assessment of small molecule identification) contests. Furthermore, the use of retention time models from liquid chromatography and the utility of collision cross-section modelling from ion mobility experiments are covered. Workflows and published examples of successfully annotated unknown compounds are included. Classical structure elucidation using NMR commonly elucidates the full structure using de-novo approaches [10] . The natural product [11], environmental [12] and mass spectrometry community [13] usually have different definitions for compound identification. In metabolomics, five different levels exist (see Table 1 ) including the new 'Level 0' that requires the full 3D structure and stereochemistry information. More common are 'Level 1' annotations that are confirmed by two orthogonal parameters, such as retention time and MS/MS spectrum. These levels were initially forged by the Metabolomics Standards Initiative (MSI) of the Metabolomics Society [14, 15] and were later refined by the compound identification workgroup of the society. It is recommended to integrate the level of annotation for each compound into metabolomic profiling reports.
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