Xu Ding-Qiao, Huang Lu, Yue Shi-Jun, Chen Yan-Yan, Fu Rui-Jia, Tang Yu-Ping
Key Laboratory of Shaanxi Administration of Traditional Chinese Medicine for TCM Compatibility, Shaanxi University of Chinese Medicine Xi'an 712046, China.
Zhongguo Zhong Yao Za Zhi. 2022 Apr;47(7):1776-1789. doi: 10.19540/j.cnki.cjcmm.20220117.201.
The potential quality markers(Q-markers) of Polygoni Perfoliati Herba were studied based on analytic hierarchy process(AHP)-entropy weight method(EWM), network pharmacology, and spectrum-effect relationship analysis. The AHP-EWM was used for quantitative identification of the Q-markers. To be specific, AHP was applied for the weight analysis of the validity, testability, and specificity of the first-level indexes, and EWM for the analysis of the second-level indexes supported by literature and experimental data. Based on literature and network pharmacology, the validity analysis was to study the component-target-disease-efficacy network, and select the components with the strongest correlation with the efficacy of clearing heat and removing toxin, diuresis and alleviating edema, and relieving cough. For the testability analysis, the high performance liquid chromatography(HPLC) and literature research were used to determine the 10 components in Polygoni Perfoliati Herba, and the fingerprints of Polygoni Perfoliati Herba were established at the same time. The specificity analysis was based on the statistics of the number of plants in which the components existed. Thereby, the 11 compounds: quercetin, oleanolic acid, ellagic acid, gallic acid, kaempferol, rutin, esculetin, quercetin-3-O-glucuronide, ursolic acid, protocatechuic acid, and ferulic acid, were identified as potential Q-markers. The 11 compounds were identified to have high anti-inflammatory activity, indicating that the 11 Q-markers may be the functional material basis. The result in this study is expected to serve as a reference for the quality control of Polygoni Perfoliati Herba.
基于层次分析法（AHP）-熵权法（EWM）、网络药理学和谱效关系分析，对蓼大青叶的潜在质量标志物（Q-标志物）进行了研究。采用AHP-EWM对Q-标志物进行定量识别。具体而言，运用AHP对一级指标的有效性、可测性和特异性进行权重分析，运用EWM对文献和实验数据支持的二级指标进行分析。基于文献和网络药理学，有效性分析是研究成分-靶点-疾病-药效网络，选择与清热解毒、利尿消肿、止咳药效相关性最强的成分。对于可测性分析，采用高效液相色谱法（HPLC）和文献研究确定蓼大青叶中的10种成分，同时建立蓼大青叶的指纹图谱。特异性分析基于成分存在的植物数量统计。由此，确定槲皮素、齐墩果酸、鞣花酸、没食子酸、山柰酚、芦丁、秦皮乙素、槲皮素-3-O-葡萄糖醛酸苷、熊果酸、原儿茶酸和阿魏酸这11种化合物为潜在的Q-标志物。经鉴定，这11种化合物具有较高的抗炎活性，表明这11种Q-标志物可能是其功能物质基础。本研究结果有望为蓼大青叶的质量控制提供参考。
