目的 分析鉴定黄芩-槐花药对的活性成分，探究活性成分治疗慢性肾脏病（chronic kidney disease，CKD）的潜在作用机制。方法 采用超高效液相色谱-质谱联用（UPLC-ESI-TOF/MS）技术，对黄芩-槐花有效成分进行分析，结合中药系统药理学数据库和分析平台查找黄芩-槐花中有效成分的作用靶点。分别在比较毒物基因组学数据库（comparative toxicogenomics database，CTD)、在线人类孟德尔遗传数据（online mendelian inheritance in man，OMIM）、GeneCards和DrugBank数据库中以“Chronic kidney disease，CKD”为关键词，查找疾病相关蛋白，用Venny图取交集筛选出二者共同作用靶点。利用Cytoscape 3.8.2软件构建“活性成分靶点-疾病”的调控网络，运用String数据库获取蛋白相互作用关系（Protein-protein interation，PPI），将疾病和有效成分的共同核心蛋白进行基因本体论（Gene ontology，GO）以及京都基因组百科全书（Kyoto encyclopedia of genes and genomes，KEGG）通路富集分析，并构建“核心靶点-通路”网络图。结果 黄芩-槐花药对共鉴别出29种有效活性成分，其中槲皮素、染料木素、汉黄芩素、山柰酚等17种关键活性成分的作用靶点与疾病相关蛋白取交集，共筛选出包括白介素-6（interleukin-6，IL-6）、细胞信号转导与转录激活因子3（signal transducer and activator of transcription 3，STAT3）、肿瘤坏死因子（tumor necrosis factor，TNF）、血管内皮生长因子（vascular endothelial growth factor-A，VEGFA）、趋化因子-8（chemokine factor-8，CXCL-8）等36个核心靶点。对关键作用靶点进行通路富集分析，黄芩-槐花药对中有效成分主要通过磷脂酰肌醇3-激酶（phosphatidylinositol 3-kinase，PI3K）-丝氨酸/苏氨酸蛋白激酶B（protein kinase，PKB，AKT）、Janus激酶（janus kinase，JAK）-信号传导和转录激活因子（signal transducer and activator of transcription，STAT）、白介素-17（interleukin-17，IL-17）、晚期糖基化终末化产物（advanced glycation end products，AGE）及晚期糖基化终末产物受体（receptor for dvanced glycation end products，RAGE）等信号通路对慢性肾脏病发挥治疗作用。结论 确定了黄芩-槐花药对中含有的29种有效成分，分析出黄酮类、类黄酮类、黄酮醇类以及皂苷类4类化合物中主要成分汉黄芩苷、槲皮素、山柰酚和槐花皂苷III的质谱裂解规律；探究黄芩-槐花药对在治疗CKD中的潜在机制，为后续临床应用提供科学的理论基础。

Objective To establish the identification and analysis method of effective ingredients of Scutellaria baicalensis- Sophora japonica (SB-SJ) drug pair, and explore the potential mechanism in the treatment of chronic kidney disease (CKD) by network pharmacology analysis. Methods Ultra Performance Liquid Chromatography Electrospray Ionization-ion Trap-time Of Flight mass spectrometry (UPLC-ESI-TOF/MS) was used to analyze the active components of SB-SJ drug pair. Seeking the action targets of SB-SJ drug pair via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platfom (TCMSP), and the disease-related proteins were found by using the key words "Chronic kidney disease" in Comparative Toxicogenomics Database (CTD), Online Mendelian Inheritance in Man (OMIM), GeneCards and DrugBank databases, respectively. In addition, the interaction between the targets of active components and disease was analyzed on Venny platform, and the same targets of two were then screened. The regulatory network of "active component-disease targets" was constructed by Cytoscape 3.8.2 software. Moreover, the PPI was obtained by String software. The function and pathway enrichment analysis of core proteins were used GO and KEGG, and the "core target-pathway" network was further constructed. Results A total of 29 kinds of effect components were identified, including one chalcone, three flavonoids, eleven flavonoids, two saporins (pentacyclic titerpenes), seven dihydrofavonoids, one dihy doflavonol, one isoflavone and three flavonols. Among them, there were 17 active ingredients related to CKD, such as quercetin, genistein, wogonin and kaempferol, which were intersected with disease targets, and 36 core targets containing IL-6, STAT3, TNF, VEGFA and CXCL-8 were screened. According to the pathway enrichment analysis of the key targets, the active components of SB-SJ drug pair have the therapeutic effect on CKD mainly through PI3K-AKT, JAK-STAI, IL-17, AGE-RAGE and other signal pathways. Conclusion In this study, 29 active components in SB-SJ drug pair were determined, and the mass spectrometric cleavage rules of wogonoside, quercetin, kaempferol and kaikasaponin III were analyzed. Based on network pharmacology, the mechanism of SB-SJ drug pair in the treatment of CKD was explored, which provides a scientific basis for future clinical application.

广东省自然科学基金项目(2019A1515011124);广东省自然科学基金项目(2021A1515011674)