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引用本文:杨亦柳,于倩,肖凤琴,刘晖,李佳,严铭铭,李光哲.基于网络药理学和化学计量学方法预测桔梗的质量标志物[J].中国现代应用药学,2023,40(13):1785-1794.
YANG Yiliu,YU Qian,XIAO Fengqin,LIU Hui,LI Jia,YAN Mingming,LI Guangzhe.Prediction of Platycodonis Radix Quality Marker Based on Network Pharmacology and Chemometrics Methods[J].Chin J Mod Appl Pharm(中国现代应用药学),2023,40(13):1785-1794.
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基于网络药理学和化学计量学方法预测桔梗的质量标志物
杨亦柳1, 于倩1, 肖凤琴1, 刘晖1, 李佳1, 严铭铭1,2, 李光哲1
1.长春中医药大学, 长春 130117;2.吉林省中药保健食品科技创新中心, 长春 130117
摘要:
目的 基于中药质量标志物(quality marker,Q-marker)理论的有效性和可测性对桔梗饮片Q-marker进行初步预测分析。方法 建立20批桔梗样品的指纹图谱,进行相似度评价,同时通过网络药理学构建"成分‒靶点‒通路"网络图,预测桔梗药材的潜在活性成分。运用主成分分析法、正交偏最小二乘判别分析等数理分析方法筛选差异性成分,并对候选成分进行含量测定。结果 建立的指纹图谱有19个共有峰,指认了8个共有成分作为候选活性成分,进行网络药理学分析。网络药理学筛选出6个联接度较高的化合物,基于Q-marker溯源及传递性、特有性、有效性、可测性等方面综合考虑,初步预测了木犀草素、紫丁香苷、绿原酸、桔梗皂苷D、桔梗皂苷D3和桔梗皂苷E作为桔梗潜在Q-marker。结论 桔梗Q-marker预测分析为桔梗药材质量的全面控制提供参考,同时也为桔梗药效关联物质基础及作用机制的研究和探索奠定基础。
关键词:  桔梗  网络药理学  指纹图谱  含量测定  质量标志物
DOI:10.13748/j.cnki.issn1007-7693.20222301
分类号:R285.5
基金项目:吉林省科技发展计划项目(20210401096YY);长春市重点研发计划项目(21ZGY15)
Prediction of Platycodonis Radix Quality Marker Based on Network Pharmacology and Chemometrics Methods
YANG Yiliu1, YU Qian1, XIAO Fengqin1, LIU Hui1, LI Jia1, YAN Mingming1,2, LI Guangzhe1
1.Changchun University of Chinese Medicine, Changchun 130117, China;2.Jilin Provincial Science & Technology Innovation Center of Health Food of Chinese Medicine, Changchun 130117, China
Abstract:
OBJECTIVE To preliminary predict and analyze the quality marker(Q-markers)of Platycodonis Radix decoction based on the validity and measurability of traditional Chinese medicine Q-marker. METHODS The fingerprints of 20 batches of Platycodonis Radix samples were established, and the similarity was evaluated. At the same time, a "component-target-pathway" network diagram was constructed through network pharmacology to predict the potential active components of Platycodonis Radix. Mathematical analysis methods such as principal component analysis and orthogonal partial least-squares discrimination analysis were used to screen differential components; the content of candidate components were determined. RESULTS There were 19 common peaks in the established fingerprint, and 8 common components were identified as candidate active components for network pharmacology analysis. Network pharmacology indicated that 6 compounds were screened out with a high degree of connectivity. Based on the comprehensive consideration of Q-marker principle:traceability and transmissibility, specificity, efficacy, and measurability, luteolin, syringin, chlorogen acid, platycoside D, platycoside D3 and platycoside E were preliminarily predicted as potential Q-markers of platycodon. CONCLUSION The prediction analysis of Platycodonis Radix Q-marker provides a reference for the comprehensive control of the quality of Platycodonis Radix medicinal materials, and also lays a foundation for the research and exploration of the substance basis and mechanism of action of Platycodonis Radix.
Key words:  Platycodonis Radix  network pharmacology  fingerprint  content determination  quality markers
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