High‐throughput UPLC‐Q‐TOF‐MS/MS coupled with multivariable data processing approach for the rapid screening and characterization of chemical constituents and potential bioactive compounds from Danggui Shaoyao San

化学 化学成分 主成分分析 色谱法 三萜类 偏最小二乘回归 传统医学 立体化学 人工智能 机器学习 计算机科学 医学
作者
Na Li,Yongzhou Yu,Xiaoyan Cui,Qi Liu,Hui Xiong
出处
期刊:Biomedical Chromatography [Wiley]
卷期号:36 (9) 被引量:8
标识
DOI:10.1002/bmc.5420
摘要

Danggui Shaoyao San (DSS), a herbal formula, has been widely used for decades in China to treat senile dementia and dysmenorrhea. Here, an integrative high-throughput UPLC-Q-TOF-MS/MS method coupled with a multivariable data processing approach was established for rapidly screening and identifying chemical constituents and potential bioactive compounds from DSS. Through the comparison with mass fragment ions, relevant literature, and in-house reference material database coupled with MS cleavage mechanism, 150 chemical constituents, mainly including triterpenoids, flavonoids, phathalides, and organic acids, were tentatively characterized. Most of them were identified for the first time. Then, principal component analysis was used to evaluate the differences in chemical profiles between groups, whereas the variable importance of the projection (VIP) spectrum (VIP > 1) and the trend plot of orthogonal partial least squares discriminant analysis were applied to intuitively screen the candidate variables present only in the dosed group. Consequently, by comparison with all the characterized components in vitro, 23 potential bioactive compounds were successfully identified, comprising 5 triterpenoids, 4 phathalides, 4 flavonoids, 4 organic acids, 3 lactones, and 3 other compounds, which were present in various medicinal materials, reflecting a synergistic mechanism. This work developed a rapid, reliable, and robust approach for comprehensive characterization of the chemical components and potential bioactive compounds of DSS, providing solid data for further research on pharmacodynamic substances and pharmacological mechanisms of DSS.
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