Volume 11 Issue 3
Jun.  2021
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Chanjuan Yu, Fengyun Wang, Xinyue Liu, Jiayan Miao, Siqi Tang, Qin Jiang, Xudong Tang, Xiaoyan Gao. Corydalis Rhizoma as a model for herb-derived trace metabolites exploration: A cross-mapping strategy involving multiple doses and samples[J]. Journal of Pharmaceutical Analysis, 2021, 11(3): 308-319. doi: 10.1016/j.jpha.2020.03.006
Citation: Chanjuan Yu, Fengyun Wang, Xinyue Liu, Jiayan Miao, Siqi Tang, Qin Jiang, Xudong Tang, Xiaoyan Gao. Corydalis Rhizoma as a model for herb-derived trace metabolites exploration: A cross-mapping strategy involving multiple doses and samples[J]. Journal of Pharmaceutical Analysis, 2021, 11(3): 308-319. doi: 10.1016/j.jpha.2020.03.006

Corydalis Rhizoma as a model for herb-derived trace metabolites exploration: A cross-mapping strategy involving multiple doses and samples

doi: 10.1016/j.jpha.2020.03.006
  • Received Date: Oct. 30, 2019
  • Accepted Date: Mar. 05, 2020
  • Rev Recd Date: Mar. 04, 2020
  • Available Online: Jan. 24, 2022
  • Publish Date: Jun. 15, 2021
  • Deciphering the metabolites of multiple components in herbal medicine has far-reaching significance for revealing pharmacodynamic ingredients. However, most chemical components of herbal medicine are secondary metabolites with low content whose in vivo metabolites are close to trace amounts, making it difficult to achieve comprehensive detection and identification. In this paper, an efficient strategy was proposed: herb-derived metabolites were predicted according to the structural characteristics and metabolic reactions of chemical constituents in Corydalis Rhizoma and chemical structure screening tables for metabolites were conducted. The fragmentation patterns were summarized from representative standards combining with specific cleavage behaviors to deduce structures of metabolites. Ion abundance plays an important role in compound identification, and high ion abundance can improve identification accuracy. The types of metabolites in different biological samples were very similar, but their ion abundance might be different. Therefore, for trace metabolites in biological samples, we used the following two methods to process: metabolites of high dose herbal extract were analyzed to characterize those of clinical dose herbal extracts in the same biological samples; cross-mapping of different biological samples was applied to identify trace metabolites based on the fact that a metabolite has different ion abundance in different biological samples. Compared with not using this strategy, 44 more metabolites of clinical dose herbal extract were detected. This study improved the depth, breadth, and accuracy of current methods for herb-derived metabolites characterization.
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