目的 通過網(wǎng)絡(luò)藥理學(xué)及分子對接技術(shù)，篩選環(huán)丙沙星調(diào)控主動脈夾層發(fā)生發(fā)展的關(guān)鍵靶點(diǎn)基因，并通過動物及細(xì)胞實(shí)驗進(jìn)一步探究其潛在致病機(jī)制。方法 通過TargetPrediction、PharmMapper、GeneCards、CTD數(shù)據(jù)庫分別篩選環(huán)丙沙星及主動脈夾層的相關(guān)靶點(diǎn)，二者取交集后得到環(huán)丙沙星調(diào)控主動脈夾層的潛在靶點(diǎn)；使用基因與蛋白質(zhì)相互作用檢索數(shù)據(jù)庫（STRING）構(gòu)建蛋白質(zhì)相互作用（PPI）網(wǎng)絡(luò)分析潛在靶點(diǎn)間的關(guān)聯(lián)。通過對潛在靶點(diǎn)進(jìn)行京都基因與基因組百科全書（KEGG）通路富集分析和基因本體（GO）功能富集分析，構(gòu)建“藥物-靶點(diǎn)-通路-疾病”網(wǎng)絡(luò)。利用Cytoscape軟件及蛋白質(zhì)復(fù)合物聚類算法（MCODE）等插件進(jìn)一步篩選出關(guān)鍵靶點(diǎn)，通過AutoDock vina和PyMol軟件把環(huán)丙沙星化學(xué)結(jié)構(gòu)與篩選出的關(guān)鍵靶點(diǎn)進(jìn)行分子對接及可視化呈現(xiàn)。最后結(jié)合動物模型構(gòu)建、蘇木精-伊紅（HE）染色法、細(xì)胞增殖和毒性檢測實(shí)驗、體內(nèi)外實(shí)時熒光定量反應(yīng)（RT-qPCR）實(shí)驗及蛋白質(zhì)免疫印跡（Western blotting），檢測小鼠主動脈組織及人主動脈平滑肌細(xì)胞（HASMCs）關(guān)鍵靶點(diǎn)基因表達(dá)。結(jié)果 本研究篩選出515個環(huán)丙沙星相關(guān)靶點(diǎn)，9 004個主動脈夾層相關(guān)靶點(diǎn)，并得到412個環(huán)丙沙星介導(dǎo)主動脈夾層的潛在靶點(diǎn)。KEGG通路富集分析結(jié)果顯示，主要富集于血脂與動脈粥樣硬化、白細(xì)胞介素（IL）-17信號通路、腫瘤壞死因子（TNF）信號通路等。GO功能富集分析結(jié)果顯示，細(xì)胞定位（CC）主要富集于膜筏、膜微區(qū)等；分子功能（MF）主要富集于受體結(jié)合、異生物跨膜轉(zhuǎn)運(yùn)蛋白活性等；生物學(xué)過程（BP）主要富集于對脂多糖的反應(yīng)、對細(xì)菌來源分子的反應(yīng)等。STRING及Cytoscape分析構(gòu)建PPI網(wǎng)絡(luò)圖及關(guān)鍵子模塊，獲得了15個關(guān)鍵靶點(diǎn)，分別為B淋巴細(xì)胞瘤-2（Bcl-2）、轉(zhuǎn)錄因子AP-1（JUN）、CD44、胱天蛋白酶3（CASP3）、Toll樣受體4（TLR4）、γ干擾素（IFNG）、腫瘤蛋白P53（TP53）、蛋白激酶B1（Akt1）、白蛋白（ALB）、基質(zhì)金屬蛋白酶9（MMP9）、白細(xì)胞介素（IL）-6、IL-10、IL-1β、甘油醛-3-磷酸脫氫酶（GAPDH）、腫瘤壞死因子（TNF）。分子對接結(jié)果顯示，環(huán)丙沙星與MMP9、ALB、GAPDH、Akt1、TP53、CASP3、IL-1β的對接模式較好。體內(nèi)實(shí)驗表明，相較于模型組，模型＋環(huán)丙沙星組在成膜率和死亡率上均增加，管壁彈性結(jié)構(gòu)破壞也更加嚴(yán)重；促凋亡基因及促炎基因的mRNA表達(dá)水平及蛋白表達(dá)水平均增加。體外實(shí)驗發(fā)現(xiàn)，相較于對照組，不同濃度環(huán)丙沙星刺激HASMCs細(xì)胞后，MMP9、IL-6、CASP3、JUN、IL-1β、TP53和TLR4表達(dá)水平明顯上調(diào)，Akt1表達(dá)水平明顯下調(diào)。結(jié)論 環(huán)丙沙星是介導(dǎo)主動脈夾層發(fā)生發(fā)展的重要因素之一，可能通過刺激炎癥因子表達(dá)及VASMCs凋亡發(fā)揮調(diào)控作用。

Objective To screen the key target genes of ciprofloxacin in regulation of the occurrence and development of aortic dissection through network pharmacology and molecular docking technology, and further explore its potential pathogenic mechanism through animal and cell experiments. Methods TO screen the related targets of ciprofloxacin and aortic dissection were from TargetPrediction, PharmMapper, GeneCards, and CTD databases respectively, and the potential targets of ciprofloxacin regulating aortic dissection were obtained after the intersection of the related targets. PPI network was constructed using the search tool for STRING database to analyze the association between potential targets. The potential targets were analyzed by KEGG pathway enrichment and GO function enrichment analysis, and the “drug-target-pathway-disease” network was constructed. Cytoscape software and MCODE and other plug-ins were used to further screen out the key targets. The chemical structure of ciprofloxacin and the key targets were docked and visualized by AutoDock vina and PyMol software. Combined with animal model construction, HE staining, cell proliferation, and toxicity detection experiments, RT-Qpcr experiments, and Western blotting were used to detect the key target gene expression in mouse aortic tissues and human aortic smooth muscle cells (HASMCs). Results In this study, 515 Ciprofloxacin-related targets, and 9 004 aortic dissection-related targets were screened, resulting in 412 potential ciprofloxacin-regulated aortic dissection targets. KEGG pathway enrichment analysis showed that they were mainly enriched in lipid and atherosclerosis, IL-17 signaling pathway, TNF signaling pathway, etc. GO functional enrichment analysis showed that CC was mainly enriched in membrane raft and membrane microdomain. MF was mainly enriched in cytokine receptor binding and xenobiotic transmembrane transporter activity. BP were mainly enriched in the response to lipopolysaccharide, the response to molecule bacterial origin, etc. STRING and Cytoscape analysis were used to construct the PPI network and key sub-modules, and 15 key targets were obtained. They were Bcl-2, JUN, CD44, CASP3, TLR4, IFNG, TP53, Akt1, ALB, MMP9, IL-6, IL10, IL-1B, GAPDH, and TNF. Molecular docking results showed that ciprofloxacin had a good docking mode with MMP9, ALB, GAPDH, Akt1, TP53, CASP3, and IL1β. In vivo experiments showed that compared with the model group, the model + ciprofloxacin model group had increased film formation rate and mortality rate, and more serious damage to the elastic structure of the vessel wall. The mRNA and protein expression levels of pro-apoptotic and pro-inflammatory genes were increased. In vitro experiments showed that compared with the control group, the expression levels of MMP9, IL-6, CASP3, JUN, IL-1β, TP53, and TLR4 were significantly up-regulated, and the expression level of Akt1 was significantly down-regulated in HASMCs cell stimulated with different concentrations of ciprofloxacin. Conclusion Ciprofloxacin is one of the important factors mediating the occurrence and development of aortic dissection, which may play a regulatory role by stimulating the expression of inflammatory factors and VASMCs cell apoptosis.

R965

國家自然科學(xué)基金資助項目（82360090）；新疆維吾爾自治區(qū)重點(diǎn)研發(fā)任務(wù)專項（2022B03022-3）