目的 基于指纹图谱和网络药理学分析预测经典名方竹茹汤（Zhuru Decoction，ZRD）中葛根的质量标志物（Q-Marker）。方法 建立葛根药材和饮片的水煎液及竹茹汤的指纹图谱，利用中药色谱指纹图谱相似度评价系统软件（2012年版）进行分析；采用网络药理学筛选和分析竹茹汤中葛根相关成分的作用靶点和通路，构建成分-靶点-通路网络，预测竹茹汤中葛根发挥治疗胃热呕吐功效潜在的Q-Marker。结果 分别建立了15批葛根药材水煎液、葛根饮片水煎液和18批竹茹汤的指纹图谱，相似度均>0.95，并指认出6个共有成分，分别为4号峰3'-羟基葛根素、6号峰葛根素、7号峰3'-甲氧基葛根素、9号峰葛根芹菜糖苷、11号峰大豆苷、23号峰大豆苷元；从网络药理学数据库中筛选分析得到6个化合物的14个核心靶点，包括转录因子p65（transcription factor p65，RELA）、RAC-α丝氨酸/苏氨酸蛋白激酶（RAC-α serine/threonine-protein kinase，AKT1）、肿瘤坏死因子（tumor necrosis factor，TNF）、信号转导和转录激活因子1-α/β（signal transducer and activator of transcription 1-α/β，STAT1）、白细胞介素-6（interleukin-6，IL-6）、丝裂原活化蛋白激酶14（mitogen-activated protein kinase 14，MAPK14）、STAT3、转录因子AP-1（transcription factor AP-1，JUN）、细胞肿瘤抗原p53（cellular tumor antigen p53，TP53）等和20条关键通路，包括IL-6、TNF信号通路、NOD样受体（NOD-like receptor）信号通路、Toll样受体（Toll-like receptor）信号通路等构建成分-靶点-通路图；基于“Q-Marker五原则”分析预测大豆苷元、葛根素、大豆苷为竹茹汤中葛根潜在的Q-Marker。结论 通过指纹图谱和网络药理学分析预测竹茹汤中葛根的Q-Marker，为全面控制竹茹汤的质量提供依据，为进一步研究竹茹汤的作用机制提供参考，同时为经典名方中复方及单味药的Q-Marker的关联性研究提供示范。

Objective To analyze and predict the Q-Marker of Gegen (Puerariae Lobatae Radix, PLR) in Zhuru Decoction (竹茹汤, ZRD) based on fingerprint and network pharmacology. Methods The fingerprints of PLR decoction, PLR pieces decoction and ZRD were collected, and analyzed by using the similarity evaluation system software for chromatographic fingerprint of traditional Chinese medicine (2012 edition); The function target and pathway of related components of PLR were screened and analyzed, and the "component-target-pathway" network was constructed to predict the potential Q-marker of PLR in therapeutic effect of ZRD on vomiting caused by stomach heat. Results The fingerprint libraries of 15 batches of PLR decoction, 15 batches of PLR pieces decoction, and 18 batches of ZRD were established, with the similarity more than 0.95. Six common components of peaks 4, 6, 7, 9, 11, 23 were identified, respectively, named 3'-hydroxy puerarin, puerarin, 3'-methoxy puerarin, apioside, daidzin and daidzein. A total of 14 core target sites related to six components including transcription factor p65 (RELA), RAC-α serine/threonine-protein kinase (AKT1), tumor necrosis factor (TNF), signal transducer and activator of transcription 1-α/β (STAT1), interleukin-6 (IL-6), mitogen-activated protein kinase 14 (MAPK14), signal transducer and activator of transcription 3 (STAT3), transcription factor AP-1 (JUN), cellular tumor antigen p53 (TP53) and etc, and 20 key pathways including Interleukin-6, TNF signaling pathway, NOD-like receptor signaling pathway, Toll-like receptor signaling pathway and others of PLR were screened out from network pharmacology system in the component-target-pathway network. Based on the analysis and prediction guided by the "Five Principles" of Q-Marker, daidzein, puerarin, daidzin were identified as the potential Q-Marker in ZRD. Conclusion In this study, the Q-Markers of PLR in ZRD are analyzed by fingerprint and network pharmacology, which provides a basis for comprehensive quality control of ZRD, and offers a reference for further study on the mechanism of ZRD. Meanwhile, it also could serve as an example for the correlation study of Q-Marker of compound and single medicine in the classic prescription.

R283.6

国家重点研发计划项目（2018YFC1707000）；江苏省研究生科研与实践创新训练计划项目（KYCX21_1773）