A feasible strategy based on isotopic fine structures to enhance the reliability of metabolite identification by Fourier transform ion cyclotron resonance mass spectrometry. (29th December 2019)

• Record Type: Journal Article
• Authors: Xu, Lu; Li, Xintong; Wang, Xue; Song, Aihua; Han, Fei
• Is Part Of: Rapid communications in mass spectrometry. Volume 34:Number 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-12-29
• Subjects: Mass spectrometry -- Periodicals; 543.65
• DOI: 10.1002/rcm.8560
• Languages: English
• ISSNs: 0951-4198

Abstract

Abstract : Rationale: In the process of the identification of unknown metabolites, the most important thing is to determine their real chemical formulae according to the accurate masses which are determined by high‐resolution mass spectrometry. However, high mass accuracy alone is not enough to exclude false candidates. Use of isotopic fine structures (IFSs) derived from Fourier transform ion cyclotron resonance mass spectrometry (FT‐ICR MS) as a single further constraint could decisively determine the molecular formulae for unknown metabolites. Methods: Gastrodin, an active constituent from Gastrodia elata Bl., which can penetrate through the blood–brain barrier and rapidly decompose to p ‐hydroxybenzyl alcohol in the brain, was selected as a model drug. The accurate masses, possible chemical formulae and IFSs of its metabolites in rat plasma were acquired using FT‐ICR MS. Results: Besides gastrodin, a total of eight metabolites including two phase I and six phase II metabolites were detected. Their chemical formulae were decisively determined by IFSs. Furthermore, their chemical structures were identified by comparing their fragment ions with those of gastrodin. Results indicated the metabolic pathways of gastrodin in rats including deglycosylation, oxidation, glucuronidation, sulfate conjugation and glycine conjugation. Conclusions: It is demonstrated that IFSs are effective in unambiguous determination of chemical formulae of metabolites. It could be used as a feasible strategy to enhance the reliability of metabolite identification in drug metabolism studies.