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Current status of retention time prediction in metabolite identification
Author(s) -
Witting Michael,
Böcker Sebastian
Publication year - 2020
Publication title -
journal of separation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.72
H-Index - 102
eISSN - 1615-9314
pISSN - 1615-9306
DOI - 10.1002/jssc.202000060
Subject(s) - metabolomics , identification (biology) , mass spectrometry , tandem mass spectrometry , retention time , metabolite , chemistry , chromatography , liquid chromatography–mass spectrometry , biology , biochemistry , botany
Abstract Metabolite identification is a crucial step in nontargeted metabolomics, but also represents one of its current bottlenecks. Accurate identifications are required for correct biological interpretation. To date, annotation and identification are usually based on the use of accurate mass search or tandem mass spectrometry analysis, but neglect orthogonal information such as retention times obtained by chromatographic separation. While several tools are available for the analysis and prediction of tandem mass spectrometry data, prediction of retention times for metabolite identification are not widespread. Here, we review the current state of retention time prediction in liquid chromatography–mass spectrometry‐based metabolomics, with a focus on publications published after 2010.