4.4 Article

Metabolite identification of triptolide by data-dependent accurate mass spectrometric analysis in combination with online hydrogen/deuterium exchange and multiple data-mining techniques

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RAPID COMMUNICATIONS IN MASS SPECTROMETRY
卷 25, 期 20, 页码 3167-3177

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WILEY-BLACKWELL
DOI: 10.1002/rcm.5211

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资金

  1. National Natural Science Foundation of China [30901829, 31071146]
  2. Shandong Natural Science Foundation of China [BS2009SW013]
  3. Southeast University [3231001201]

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Triptolide (TP), the primary active component of the herbal medicine Tripterygium wilfordii Hook F, has shown promising antileukemic and anti-inflammatory activity. The pharmacokinetic profile of TP indicates an extensive metabolic elimination in vivo; however, its metabolic data is rarely available partly because of the difficulty in identifying it due to the absence of appropriate ultraviolet chromophores in the structure and the presence of endogenous interferences in biological samples. In the present study, the biotransformation of TP was investigated by improved data-dependent accurate mass spectrometric analysis, using an LTQ/Orbitrap hybrid mass spectrometer in conjunction with the online hydrogen (H)/deuterium (D) exchange technique for rapid structural characterization. Accurate full-scan MS and MS/MS data were processed with multiple post-acquisition data-mining techniques, which were complementary and effective in detecting both common and uncommon metabolites from biological matrices. As a result, 38 phase I, 9 phase II and 8 N-acetylcysteine (NAC) metabolites of TP were found in rat urine. Accurate MS/MS data were used to support assignments of metabolite structures, and online H/D exchange experiments provided additional evidence for exchangeable hydrogen atoms in the structure. The results showed the main phase I metabolic pathways of TP are hydroxylation, hydrolysis and desaturation, and the resulting metabolites subsequently undergo phase II processes. The presence of NAC conjugates indicated the capability of TP to form reactive intermediate species. This study also demonstrated the effectiveness of LC/HR-MSn in combination with multiple post-acquisition data-mining methods and the online H/D exchange technique for the rapid identification of drug metabolites. Copyright (C) 2011 John Wiley & Sons, Ltd.

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