Arabian Journal of Chemistry (Jan 2024)

Quality markers screening of traditional Chinese medicine prescriptions based on the multi-factor analysis strategy: Jin-Zhen oral liquid as a case

  • Ling-xian Liu,
  • Hai-bo Li,
  • Jia-ying Zhang,
  • Dan-feng Shi,
  • Zhen-zhong Wang,
  • Xin-sheng Yao,
  • Wei Xiao,
  • Yang Yu

Journal volume & issue
Vol. 17, no. 1
p. 105433

Abstract

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Background: Jin-Zhen oral liquid (JZOL), a well-known traditional Chinese medicine prescription (TCMp), has extensively been used to treat acute bronchitis in children more than four hundred years in China. However, the current quality control standard of JZOL is inadequate, posing challenges for its internationalization. Purpose: In this study, a Q-marker screening strategy based on multi-factor analysis was proposed to comprehensively evaluate anti-inflammatory Q-markers of Jin-Zhen oral liquid (JZOL). Methods: Firstly, the chemical profile and the pharmacokinetics properties of multiple components in JZOL were characterized by UPLC-Q/TOF-MS and UPLC-QqQ-MS. By integrating the measurable and absorbed components, twenty-two components with structures accurately defined, were selected as candidate Q-markers of JZOL. Following that, a network connecting 22 components and targets closely associated with bronchitis was established. Afterwards, a multi-factor analysis mode was developed to balance the components’ multiple characteristics, and screen out the anti-inflammatory Q-markers in JZOL. Finally, the anti-inflammatory activity evaluation was conducted by LPS-induced RAW 264.7 macrophages to prove the representativeness of anti-inflammatory Q-markers in JZOL. Results: As a result, a total of 92 components were characterized in JZOL and the pharmacokinetics properties of 11 bioactive components in vivo were further characterized. Then, an overlapping of 46 targets involved in the interactions of selected 22 candidate Q-markers and the regulation of bronchitis inflammation were collected. Subsequently, a multi-factor analysis was developed on 22 candidate anti-inflammatory Q-markers covering five factors, with the statistic KMO values of 0.645, and the P values of Bartlett's Test equal to 0.000. A total of seven ingredients (aloeemodin-8-O-β-d-glucopyranoside, baicalin, chrysin-7-O-β-d-glucuronide, oroxylin A 7-O-β-d-glucuronide, wogonoside, chrysophanol-8-O-β-d-glucopyranoside, and skullcapflavone II) were selected as Q-markers of JZOL, and the inhibitory effects of these candidate Q-markers on the secretion of inflammatory cytokes (NO, IL-6, IL-1β, and PGE2) in lipopolysaccharide (LPS)-stimulated RAW264.7 cells were evaluated and confirmed. Conclusion: This study not only offers a fresh approach to uncovering Q-markers in the quality control research of TCMps but also identifies the suitable anti-inflammatory Q-markers for JZOL for the first time, with the potential to serve as a reference for existing quality control standards of JZOL.

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