基于网络药理学的两面针干预炎症靶点预测及作用机制研究

Targets prediction and mechanism of Zanthoxylum nitidum in intervention of inflammation based on network pharmacology

目的构建两面针干预炎症的"活性成分-炎症靶点-抗炎通路"网络关系,预测其干预炎症的靶点及机制。方法通过国内外文献调研和中药系统药理学分析平台(TCMSP)数据库及Pharmmapper服务器,以口服利用度(OB)和类药性(DL)作为限定条件对两面针成分进行筛选并预测和收集相关靶点。利用OMIM等数据库筛选炎症相关的基因和蛋白靶点;STRING数据库构建炎症靶点之间的交互网络;蛋白互作(PPI)网络分析获得"活性成分-预测靶点-炎症靶点"网络文件,并将其导入Cytoscape 3.5.1软件构建"活性成分-炎症靶点"网络,从而获得与两面针抗炎直接相关的靶点;利用DAVID数据库对筛选后的靶点进行KEGG通路富集,使用Cytoscape 3.5.1的插件ClueGO对其涉及的靶点进行生物学功能分析,最终合并以上关系构建"活性成分-炎症靶点-抗炎通路"网络。结果经筛选和分析获得两面针活性成分23个,抗炎靶点9个,包括COX-2、i NOS、PPARG、COX1、MAPK-14、JUN等,两面针抗炎的可能通路包括TNF信号通路、TRLs信号通路。结论初步揭示了两面针的抗炎作用是通过多成分和多靶点的相互作用,调控多条通路共同干预实现的,但关键的靶标和具体的调控机制尚待进一步的实验研究加以探索及验证。

Objective To construct the 'active components-inflammatory target-anti-inflammatory pathway' network of Zanthoxylumnitidum intervened in inflammation, and predict the target of Z. nitidum intervened in inflammation and its anti-inflammatory mechanism. Methods Using domestic and foreign literatures, TCMSP database, Pharmmapper server, oral availability(OB), and pharmacodynamics(DL) as the limiting conditions, the components of Z. nitidum were screened and the relative targets were predicted and collected. OMIM database was used to screen inflammation-related genes and protein targets;The STRING database was used to construct the interactive network between inflammatory targets;The network file of 'active ingredient-predictive target-inflammatory target' was obtained by PPI analysis and imported into Cytoscape 3.5.1 software to construct the network of 'active ingredientinflammatory target', so as to obtain the targets directly related to the anti-inflammatory effects of Z. nitidum. DAVID database was used to enrich the KEGG pathway of the selected targets, and then ClueGO plug-in was used to analyze the biological function of the target involved. Finally, the 'active component-inflammatory target-anti-inflammatory pathway' network was constructed by combining the above relationships. Results Twenty-three active ingredients were screened, and nine core anti-inflammatory targets were identified as COX-2, iNOS, PPARG, COX1, MAPK-14, JUN, NR3 C1 and so on;The most critical pathways included TNF TRLs signaling pathways. Conclusion It is preliminarily revealed that the anti-inflammatory effect of Z. nitidum is achieved through the interaction of multiple components and multiple targets, regulating the joint intervention of multiple pathways. However, the key targets and specific regulatory mechanisms need to be explored and verified by further experimental studies.