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Archive > Volume 13 Issue 1 > 2021,13(1). DOI:10.1016/j.chmed.2020.06.002 Prev Next

Quality Analysis of TCM

An integrated strategy toward comprehensive characterization and quantification of multiple components from herbal medicine: An application study in Gelsemium elegans

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    摘要:


    Abstract:
    Objective: To develop a powerful integrated strategy based on liquid chromatography coupled with mass spectrometry (LC-MS) systems for the comprehensive characterization and quantification of multiple components of herbal medicines. Methods: Firstly, different mobile phase additives, analysis time, and MS acquisition modes were orthogonally tested with liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) in order to detect as many components of Gelsemium elegans as possible with high peak intensity. Secondly, several data mining strategies, including database searching, diagnostic ion filtering and neutral loss filtering, were utilized to perform chemical profiling. Subsequently, this study focused on the quantification and validation of the performance of a liquid chromatography-triple mass spectrometry (LC-QqQ/MS) assay based on derivative multiple reaction monitoring (DeMRM). Results: A total of 147 components from G. elegans were characterized, among them 116 nontarget components were reported for the first time. A sensitive and reproducible LC-QqQ/MS method was successfully developed and validated for the simultaneous relative quantification of 41 components of G. elegans. This LC-QqQ/MS method was then applied to compare the contents of components in the roots, stems and leaves. Conclusion: The present integrated strategy would significantly contribute to chemical studies on herbal medicine, and its utility could be extended to other research fields, such as metabolomics, quality control, and pharmacokinetics.

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    Project Supported:
    This work was supported by National Key R&D Program of Intergovernmental Key Projects (Grant No: 2018YFE0101700) and National Natural Science Foundation of China (Grant No. 31972737).

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