基于专利数据挖掘与网络药理学探讨大血藤抗高脂血症的作用机制

[目的] 采用数据挖掘和网络药理学初步探讨大血藤治疗高脂血症的可能作用机制。[方法] 借助 PubMed 和CNKI 检索“大血藤化学成分”或“红藤成分”进行资料收集和化合物筛选，用 Origin Pro 2021 软件对涉及中药的功效类别等进行频数分析，用 SPSS Modeler 18.0 软件进行关联规则分析和聚类分析。利用 Swiss ADME 平台来预测候选化合物的吸收度和类药性的相关参数。采用 Swiss Target Prediction 平台来收集预测到的所有靶点， 以“hyperlipidemia”“dyslipidemia”等为关键词检索 Genegards、Drug Bank Database 等数据库中高脂血症的潜在靶点，通过 Uniprot 数据库去重和校正靶点名称，取活性成分和高脂血症靶点交集，进而运用 Cytoscape 3.8.0 软件来进行网络可视化并筛选核心靶点基因。通过 DAVID 6.8 数据库进行基因本体（GO）功能富集分析和京都基因和基因组百科全书（KEGG）通路富集分析，预测交集靶点作用机制，并绘制气泡图等进行可视化。[结果] 通过数据挖掘对大血藤的用药配伍规律进行分析，结果显示性味以温性、寒性和苦味、辛味为主，归经方面以肝、脾为主，配伍以当归、甘草、红花等关联密切，研究结果与中药治疗高脂血症用药规律一致。中药-化合物-靶点网络包含了 43 个活性成分和相应靶点 133 个，关键靶点涉及类视黄酸受体 α（RXRA）、信号转导及转录激活蛋白 3（STAT3）、90 kDa 热休克蛋白 αA1（HSP90AA1）、蛋白激酶Bα（AKT1）、磷酸肌醇 3-激酶调节亚基 1（PIK3R1）、雌激素受体 1（ESR1）、过氧化物酶体增殖物激活受体（PPAR）A、核受体亚家族 3C 组成员 1（NR3C1）等。GO 功能富集分析得到条目 437 个（P＜0.01），KEGG 通路富集分析筛选得到57 条信号通路（P＜0.05）。[结论] 大血藤可以通过多个活性成分干预血脂异常中的多个靶点、多个环节，从多维、系统的层面参与调控血脂代谢和高脂血症的发生发展过程，为大血藤的进一步开发利用提供理论基础。

Mechanism of sargentodoxa cuneate in treatment of hyperlipidemia based on patent data mining and network pharmacology

[Objective] To explore the possible mechanism of Sargentodoxa cuneata in the treatment of hyperlipidemia by data mining and network pharmacology. [Methods] PubMed and CNKI were used to search for “chemical constituents of Sargentodoxa cuneata” or “components of Sargentodoxa cuneata” for data collection and compound screening. Origin Pro 2021 software was used to analyze the frequency of efficacy categories involving traditional Chinese medicine. SPSS Modeler 18.0 software was used for association rule analysis and cluster analysis. The Swiss ADME platform was used to predict the absorption and drug-like properties of candidate compounds. Swiss Target Prediction platform was used to collect all the predicted targets. The potential targets of hyperlipidemia in Genegards，Drug Bank Database and other databases were searched with “hyperlipidemia” and “hyperlipidemia” as keywords. The target names were removed and corrected by Uniprot database，and the intersection of active components and hyperlipidemia targets was taken. Cytoscape 3.8.0 software was used to visualize the network and screen the core target genes. GO function enrichment analysis and KEGG pathway enrichment analysis were performed through the DAVID 6.8 database to predict the mechanism of action of the intersection targets，and the mapping was visualized. [Results] Through data mining，the law of drug compatibility of sargentodoxa cuneata was analyzed. The results showed that the nature and flavor were mainly warm，cold，bitter and pungent，and the meridian was mainly liver and spleen. The compatibility was closely related to angelica，licorice and safflower. The results are consistent with the medication rule of traditional Chinese medicine in the treatment of hyperlipidemia. Traditional Chinese medicine-compound-target network contained 43 active components and 133 corresponding targets. The key targets involved RXRA，STAT3，HSP90AA1，AKT1，PIK3R1，ESR1，PPARA， NR3C1，etc. GO functional enrichment analysis obtained 437 items （P＜0.01），and KEGG pathway enrichment analysis screened 57 signal pathways （P＜0.05）. [Conclusion] Sargentodoxa cuneata can interfere with multiple targets and links in dyslipidemia through multiple active components，and participate in the regulation of lipid metabolism and the occurrence and development of hyperlipidemia from a multidimensional and systematic level. This study can provide a theoretical basis for the further development and utilization of sargentodoxa cuneata.