目的 采用网络药理学与分子对接技术探讨新疆阿魏Ferula sinkiangensisk抗癌的作用机制。方法 通过SymMap和SwissTargetPrediction 数据库筛选新疆阿魏的成分和靶点信息。利用 Genecards 数据库输入“cancer”关键词检索疾病的靶点；利用韦恩图获取药物-疾病的交集靶点，并借助STRING平台获取蛋白质-蛋白质相互作用（PPI）网络；利用DAVID数据库对药物-疾病的交集靶点进行基因本体（GO）富集分析和京都基因与基因组百科全书（KEGG）通路富集分析；利用Cytoscape 3.9.0软件绘制“活性成分-靶点-通路”网络图。利用 AutoDock软件对筛选出的主要活性成分及关键靶点进行分子对接实验，验证其结合活性。结果 获取新疆阿魏化学成分34个，对应靶点537个，通过筛选获得癌症靶点1 155个，药物-疾病的交集靶点134个。GO功能富集分析共获取331条条目（P＜0.05），其中生物过程（BP）249条，细胞组成（CC）31条，分子功能（MF）51条。KEGG通路 133条，并建立活性成分-靶点-通路网络，分子对接实验表明活性物质阿魏酸、法尼斯淝醇 A、法尼斯淝醇 C、柠檬烯和 β -蒎烯与关键靶点 CCND1、JUN、CXCL8、PIK3CA 均具有较好的结合能 力 。 结论 新疆阿魏中阿魏酸、法尼斯淝醇 A、法尼斯淝醇 C、柠檬烯和 β-蒎烯等化学物质，通过 CCND1、JUN、CXCL8和PIK3CA等靶点，调节PDL-1表达和PD-1免疫检查点通路、IL-17信号通路、雌激素信号通路和PI3K-Akt信号通路等发挥抗癌作用。

Objective To study the anticancer mechanism of Ferula sinkiangensisk based on network pharmacology and molecular docking. Methods The chemical substances, target information and component-target correspondence network of F. sinkiangensisk were screened through the SymMap and SwissTargetPrediction database. Genecards database to enter the "cancer" keyword was used to search for disease targets and further screened. Venn diagrams was used to obtain drug-disease intersection targets, and the STRING platform was use to obtain protein-protein interaction (PPI) networks. Gene ontology (GO) enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) enrichment pathway analysis were performed on drug-disease intersection targets using DAVID database. Cytoscape 3.9.0 software was used to draw the "active ingredient-target-pathway" network map. Finally, AutoDock software was used to carry out molecular docking experiments on the selected key targets to verify the binding activity. Results 34 chemical constituents and 537 corresponding targets were obtained from F. sinkiangensisk, 1 155 cancer targets and 134 drug-disease intersection targets were screened. GO functional enrichment analysis obtained a total of 331 items (P＜0.05) , including 249 biological processes (BP), 31 cellular components (CC) and 51 molecular functions (MF), and 133 KEGG pathways were obtained. The active ingredient-target-pathway network was established. Molecular docking experiments showed that the active substances ferulic acid, farnesfeinol A, farnesfeinol C, limonene and β-pinene had sound binding ability with key targets CCND1, JUN, CXCL8 and PIK3CA. Conclusion Ferulic acid, farnesiferol A, farnesiferol C, limonene, beta-pinene and other chemicals in F. sinkiangensisk, through targets such as CCND1, JUN, CXCL8 and PIK3CA, regulate the expression of PDL-1 and PD-1 immune checkpoint pathway, IL-17 signal pathway, estrogen signal pathway and PI3K-Akt signal pathway to play an anticancer role.

R285.5

湖南省科技创新计划资助项目（2022RC1228）；湖南省教育厅资助科研项目（19A353）