[关键词]
[摘要]
目的 基于网络药理学、分子对接与体外实验探讨紫苏抗肺腺癌的作用机制。方法 通过中药系统药理学数据库与分析平台收集紫苏的活性成分及其相应靶点,利用OMIM和GeneCards数据库预测肺腺癌相关靶点,使用Venny 2.1.0工具获得紫苏与肺腺癌的交集靶点。利用Cytoscape 3.9.0软件构建药物–靶点–疾病网络并筛选核心活性成分,利用STRING工具与Cytoscape软件构建交集靶点的蛋白质–蛋白质相互作用(PPI)网络并筛选核心靶点,通过Metascape工具完成交集靶点的基因本体(GO)及京都基因与基因组百科全书(KEGG)富集分析,利用AutoDockTools 1.5.7软件完成活性成分与核心靶点的分子对接。使用活性成分β-谷甾醇与阳性对照药物顺铂处理人非小细胞肺癌A549细胞,并通过细胞计数试剂盒-8(CCK-8)检测细胞活力并计算药物半数抑制浓度(IC50),通过流式细胞术检测细胞凋亡,通过Western blotting检测信号通路相关蛋白的表达水平。结果 从紫苏中筛选出14个活性成分,并获得48个紫苏药物靶点和肺腺癌的交集靶点;明确了木犀草素、β-胡萝卜素和β-谷甾醇3种核心成分,以及肿瘤蛋白53(TP53)、表皮生长因子受体(EGFR)、白细胞介素-6(IL-6)、蛋白激酶B1(Akt1)与胱天蛋白酶-3(CASP3)5个核心靶点。富集分析发现,交集靶点富集于细胞对化学压力的反应等生物过程基因集、膜筏等细胞成分基因集、DNA结合转录因子结合等分子功能基因集以及磷脂酰肌醇3-激酶(PI3K)/Akt等信号通路。分子对接结果表明β-谷甾醇等成分与EGFR等核心靶点具有良好的结合能力。CCK-8检测结果发现β-谷甾醇对A549细胞活力具有抑制作用,且具有浓度相关性,其IC50值为42 μmol/L。流式细胞术结果表明,随着β-谷甾醇浓度的增加,A549细胞凋亡率增加(P<0.05)。Western blotting结果表明,84 μmol/L β-谷甾醇组的p-PI3K/PI3K、p-Akt/Akt及p-mTOR/mTOR均显著降低(P<0.05、0.01、0.001)。结论 β-谷甾醇等为紫苏的核心活性成分,可通过靶向EGFR、IL-6等关键靶点调控PI3K/Akt等信号通路发挥抗肺腺癌作用。
[Key word]
[Abstract]
Objective To explore the mechanism of Perilla frutescens against lung adenocarcinoma based on network pharmacology, molecular docking, and in vitro experiments. Methods The active components of P. frutescens and their corresponding targets were collected through the traditional Chinese medicine systems pharmacology database and analysis platform. Lung adenocarcinoma- related targets were predicted using the OMIM and GeneCards databases. The intersection targets of P. frutescens and lung adenocarcinoma were obtained using the Venny 2.1.0 tool. A drug-target-disease network was constructed using Cytoscape 3.9.0 software to screen the core active components. The protein-protein interaction (PPI) network of the intersection targets was constructed using the STRING tool and Cytoscape software to screen the core targets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses of the intersection targets were performed using the Metascape tool. Molecular docking between the active components and core targets was carried out using AutoDockTools 1.5.7 software. Human non-small cell lung cancer A549 cells were treated with the active component β-sitosterol and the positive control drug cisplatin. Cell viability was detected using the cell counting Kit-8 (CCK-8) assay, and the half-maximal inhibitory concentration (IC50) was calculated. Apoptosis was detected by flow cytometry. The expression levels of signaling pathway-related proteins were detected by Western blotting. Results Fourteen active components were screened from P. frutescens, and 48 intersecting targets between P. frutescens drug targets and lung adenocarcinoma were identified. Three core components (luteolin, β-carotene, and β-sitosterol) and five core targets tumor protein p53 (TP53), epidermal growth factor receptor (EGFR), interleukin-6 (IL-6), protein kinase B1 (Akt1), and Caspase-3 (CASP3) were determined. Enrichment analysis showed that the intersection targets were enriched in biological processes such as cellular response to chemical stress, cellular components such as membrane rafts, molecular functions such as DNA-binding transcription factor binding, and signaling pathways such as the phosphatidylinositol 3-kinase (PI3K)/Akt pathway. Molecular docking results indicated that β-sitosterol and other components had good binding affinity with core targets such as EGFR. The CCK-8 assay showed that β-sitosterol inhibited the viability of A549 cells in a concentration-dependent manner, with an IC50 value of 42 μmol/L. Flow cytometry results demonstrated that the apoptotic rate of A549 cells increased with increasing concentrations of β-sitosterol (P < 0.05). Western blotting results showed that the ratios of p-PI3K/PI3K, p-Akt/Akt, and p-mTOR/mTOR were significantly decreased in the 84 μmol/L β-sitosterol group (P < 0.05, 0.01, 0.001). Conclusion β-Sitosterol and other components are the core active components of P. frutescens, which exert anti-lung adenocarcinoma effects by regulating signaling pathways such as the PI3K/Akt pathway through targeting key targets including EGFR and IL-6.
[中图分类号]
R285;R286.4
[基金项目]
黑龙江省外国专家项目(G2024044)