目的 采用網(wǎng)絡(luò)藥理學(xué)與分子對(duì)接技術(shù)探討新疆阿魏Ferula sinkiangensisk抗癌的作用機(jī)制。方法 通過(guò)SymMap和SwissTargetPrediction 數(shù)據(jù)庫(kù)篩選新疆阿魏的成分和靶點(diǎn)信息。利用 Genecards 數(shù)據(jù)庫(kù)輸入“cancer”關(guān)鍵詞檢索疾病的靶點(diǎn)；利用韋恩圖獲取藥物-疾病的交集靶點(diǎn)，并借助STRING平臺(tái)獲取蛋白質(zhì)-蛋白質(zhì)相互作用（PPI）網(wǎng)絡(luò)；利用DAVID數(shù)據(jù)庫(kù)對(duì)藥物-疾病的交集靶點(diǎn)進(jìn)行基因本體（GO）富集分析和京都基因與基因組百科全書(shū)（KEGG）通路富集分析；利用Cytoscape 3.9.0軟件繪制“活性成分-靶點(diǎn)-通路”網(wǎng)絡(luò)圖。利用 AutoDock軟件對(duì)篩選出的主要活性成分及關(guān)鍵靶點(diǎn)進(jìn)行分子對(duì)接實(shí)驗(yàn)，驗(yàn)證其結(jié)合活性。結(jié)果 獲取新疆阿魏化學(xué)成分34個(gè)，對(duì)應(yīng)靶點(diǎn)537個(gè)，通過(guò)篩選獲得癌癥靶點(diǎn)1 155個(gè)，藥物-疾病的交集靶點(diǎn)134個(gè)。GO功能富集分析共獲取331條條目（P＜0.05），其中生物過(guò)程（BP）249條，細(xì)胞組成（CC）31條，分子功能（MF）51條。KEGG通路 133條，并建立活性成分-靶點(diǎn)-通路網(wǎng)絡(luò)，分子對(duì)接實(shí)驗(yàn)表明活性物質(zhì)阿魏酸、法尼斯淝醇 A、法尼斯淝醇 C、檸檬烯和 β -蒎烯與關(guān)鍵靶點(diǎn) CCND1、JUN、CXCL8、PIK3CA 均具有較好的結(jié)合能 力 。 結(jié)論 新疆阿魏中阿魏酸、法尼斯淝醇 A、法尼斯淝醇 C、檸檬烯和 β-蒎烯等化學(xué)物質(zhì)，通過(guò) CCND1、JUN、CXCL8和PIK3CA等靶點(diǎn)，調(diào)節(jié)PDL-1表達(dá)和PD-1免疫檢查點(diǎn)通路、IL-17信號(hào)通路、雌激素信號(hào)通路和PI3K-Akt信號(hào)通路等發(fā)揮抗癌作用。

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

湖南省科技創(chuàng)新計(jì)劃資助項(xiàng)目（2022RC1228）；湖南省教育廳資助科研項(xiàng)目（19A353）