目的 基于网络药理学、分子动力学模拟以及体外实验验证的方法，探讨补骨脂二氢黄酮甲醚治疗肺炎潜在作用机制。方法 通过GeneCards、TTD、DisGeNET数据库筛选肺炎相关靶点，经UniProt数据库进行标准化处理，获取疾病相关靶点；利用CTD、PharmMapper、SwissTarget Prediction数据库预测补骨脂二氢黄酮甲醚的作用靶点；取疾病与药物靶点交集，获得潜在治疗靶点，并借助Cytoscape 3.7.1构建“疾病–靶点–药物”调控网络；通过STRING数据库构建蛋白质相互作用（PPI）网络，利用仙桃学术平台进行基因本体（GO）功能与京都基因与基因组百科全书（KEGG）通路富集分析；采用AutoDock Vina、PyMOL等软件完成分子对接，运用GROMACS进行分子动力学模拟以验证结合稳定性。以脂多糖（LPS）诱导的A549细胞建立肺炎模型，利用CCK-8检测补骨脂二氢黄酮甲醚对A549细胞增殖影响，划痕实验检测补骨脂二氢黄酮甲醚对A549细胞迁移影响，ELISA实验检测补骨脂二氢黄酮甲醚对A549细胞中炎症因子表达影响，qRT-PCR实验检测补骨脂二氢黄酮甲醚对A549细胞中核心靶点以及信号通路相关靶点mRNA的表达，Western blotting实验检测补骨脂二氢黄酮甲醚对A549细胞中关键信号通路蛋白表达影响。结果 共筛选出肺炎相关靶点2 538个，补骨脂二氢黄酮甲醚作用靶点369个，共同靶点106个。PPI网络分析提示肿瘤坏死因子（TNF）、白细胞介素（IL）-6、IL-1β、蛋白激酶B1（Akt1）、白蛋白（ALB）、B细胞淋巴瘤因子-2（Bcl-2）为核心靶点。富集分析表明其作用机制可能与磷脂酰肌醇-3-激酶/蛋白激酶B（PI3K/Akt）和叉头框蛋白O（FoxO）等信号通路密切相关。分子对接结果显示，补骨脂二氢黄酮甲醚与核心靶点结合能均低于−5.0 kcal/mol，分子动力学模拟显示补骨脂二氢黄酮甲醚–Akt1复合物达到平衡状态，表明补骨脂二氢黄酮甲醚与Akt1的结合稳定，进一步验证分子对接结果的可靠性。细胞实验表明，与模型组相比，补骨脂二氢黄酮甲醚25.0、50.0μmol/L组细胞存活率、细胞迁移率、TNF-α、IL-1β、IL-6、IFN-γ水平显著降低（P＜0.05、0.01、0.001）。与模型组比较，补骨脂二氢黄酮甲醚25.0、50.0 μmol/L组TNF、IL-6、IL-1β、PI3K mRNA及补骨脂二氢黄酮甲醚50.0 μmol/L组Akt1 mRNA相对表达量显著降低（P＜0.05、0.01、0.001），而补骨脂二氢黄酮甲醚50.0 μmol/L组ALB、Bcl-2 mRNA相对表达量显著升高（P＜0.01、0.001）。与模型组相比，补骨脂二氢黄酮甲醚25.0、50.0μmol/L组p-Akt/Akt及补骨脂二氢黄酮甲醚50.0 μmol/L组p-PI3K/PI3K明显降低（P＜0.05、0.01、0.001）。结论 通过网络药理学、分子动力学模拟以及体外实验探究发现补骨脂二氢黄酮甲醚可能通过多靶点和多通路发挥治疗肺炎的作用。

Objective To explore the potential mechanism of ‌bavachinin in treatment of pneumonia based on network pharmacology, molecular dynamics simulation, and in vitro experiments methods. Methods Pneumonia-related targets were screened through the GeneCards, TTD, and DisGeNET databases, and standardized using the UniProt database to obtain disease-related targets, the targets of action of ‌bavachinin were predicted using the CTD, PharmMapper, and SwissTarget Prediction databases. Intersection of disease and drug targets was taken to obtain potential therapeutic targets, and a “disease-target-drug” regulatory network was constructed using Cytoscape 3.7.1. PPI network was constructed through the STRING database, and GO and KEGG pathway enrichment analysis were performed using the Xiantao Academic Platform. Molecular docking was completed using AutoDock Vina and PyMOL, and molecular dynamics simulation was conducted using GROMACS to verify binding stability. A pneumonia model was established using lipopolysaccharide to induce A549 cells. The effect of ‌bavachinin on the proliferation of A549 cells was detected using CCK-8, the effect of ‌bavachinin on A549 cells migration detected by scratch assay, the impact of ‌bavachinin on the expression of inflammatory factors in A549 cells was measured by ELISA, and the mRNA expression of core targets and targets related to the signaling pathway, the effects of ‌bavachinin on the expression of key signaling pathway proteins in A549 cells detected by western blotting experiment. Results A total of 2 538 pneumonia-related targets were screened, 369 targets of action for ‌bavachinin, and 106 common targets. PPI network analysis suggests that TNF, IL-6, IL-1β, Akt1, ALB, and Bcl-2 were core targets. Enrichment analysis indicates that its mechanism of action may be closely related to signaling pathways such as PI3K/Akt and FoxO. Molecular docking results showed that the binding energy of ‌bavachinin to the core targets were lower than −5.0 kcal/mol. Molecular dynamics simulations indicated that the ‌bavachinin-Akt1 complex reached equilibrium, demonstrating the stable binding between the two molecules and further validating the reliability of the docking results. Cell experiments showed that compared with the model group, the cell survival rate, cell migration rate, levels of TNF-α, IL-1β, IL-6, and IFN-γ in the 25.0 and 50.0 μmol/L bavachinin groups were significantly lower (P < 0.05, 0.01, 0.001). Compared with the model group, the relative expression levels of TNF, IL-6, IL-1β, PI3K mRNA in the 25.0 and 50.0 μmol/L bavachinin groups, and Akt1 mRNA in the 50.0 μmol/L bavachinin group were significantly lower (P < 0.05, 0.01, 0.001), while the relative expression levels of ALB and Bcl-2 mRNA in the 50.0 μmol/L bavachinin group were significantly higher (P < 0.01, 0.001). Compared with the model group, the p-Akt/Akt and p-PI3K/PI3K in the 25.0 and 50.0 μmol/L bavachinin groups were significantly lower (P < 0.05, 0.01, 0.001). Conclusion Through network pharmacology, molecular dynamics simulation, and in vitro experiments, it was found that ‌bavachinin may exert therapeutic effects on pneumonia through multi-target and multi-pathway mechanisms.

R285;R286.4

国家自然科学基金资助项目(31701104); 成都医学院-新都区人民医院联合基金项目(2022LHXD-03)