Systematic identification of suspected anthelmintic benzimidazole metabolites using LC–MS/MS

• Published in: Journal of pharmaceutical and biomedical analysis Vol. 151; pp. 151 - 158
• Main Authors: Majewsky, Marius, Castel, David, Le Dret, Ludivine, Johann, Pascal, Jones, David T., Pfister, Stefan M., Haefeli, Walter E., Burhenne, Jürgen
• Format: Journal Article
• Language: English
• Published: England Elsevier B.V 20-03-2018; Elsevier
• Subjects: Animals; Anthelmintics - analysis; Anthelmintics - metabolism; Benzimidazoles; Benzimidazoles - analysis; Benzimidazoles - metabolism; Chromatography, Liquid - methods; LC–MS/MS; Life Sciences; Mass shift; Metabolites; Mice; Mice, Nude; Structure elucidation; Tandem Mass Spectrometry - methods; Benzimidazoles; Metabolites; LC–MS/MS; Structure elucidation; Mass shift
• ISSN: 0731-7085; 1873-264X
• DOI: 10.1016/j.jpba.2017.12.056

•MS/MS spectra of benzimidazoles were structurally elucidated.•Characteristic product ions were predicted for unknown metabolites.•Predicted product ions were verified with measured spectra.•A workflow is described to rapidly identify known and unknown metabolites.
Metabolite reference standards are often not available, which results in a lack of MS/MS spectra for library matching. Consequently, the identification of suspected metabolites proves to be challenging. The present study aims at structurally elucidating the MS/MS fragmentation behavior of selected benzimidazole anthelmintics to theoretically predict characteristic product ions for rapid and systematic tentative metabolite identification.
A set of common characteristic product ions was identified from accurate mass MS/MS experiments for five parent compounds. It was hypothesized that the mass shift of any metabolic transformation at the parent molecule also is observable in the mass spectrum of the corresponding metabolite. This was tested and verified with six metabolite reference standards and subsequently, formulated as a general prediction scheme. The approach was integrated into a rapid MSe QTOF workflow and tested in mouse plasma for mebendazole and its metabolites. The presented scheme allows the prediction of characteristic product ions for suspected unknown metabolites. These can be matched with measured product ions of suspected metabolites for tentative identification. The theoretically predicted spectra can contribute to the tentative identification of unknown compounds in non-target and suspect screening approaches.