基于网络药理学与分子对接探讨紫草素治疗乙型病毒性肝炎的作用机制*

目的: 通过网络药理学方法系统化探究紫草素治疗乙型病毒性肝炎的功效网络,并用分子对接技术进行验证。方法: 利用中药系统药理学数据库与分析平台(TCMSP)和药物靶标分析网站(Pharm Mapper)获取紫草素的有效化合物及作用靶点,利用在线人类孟德尔遗传数据库(OMIM)、人类基因数据库(GeneCards)、基因疾病关联数据库(DisGeNET)、毒性与基因比较数据库(CTD)获取乙型病毒性肝炎的疾病靶点,经靶点映射获取紫草素与乙肝的共同作用靶点,通过STRING数据库获取靶点之间的关系信息,应用Cytoscape 3.8.2做可视化处理,并通过R语言进行基因本体论(GO)分析和京都基因与基因组百科全书(KEGG)通路富集分析。运用AutoDockTools完成分子对接。结果: 共获得AKT丝氨酸/苏氨酸激酶 1 (AKT1)、血清白蛋白(ALB)以及非受体酪氨酸激酶(原癌基因SRC),丝裂原活化蛋白激酶1 (MAPK1)、表皮生长因子受体(EGFR)等63个作用靶点,经GO富集分析得到1 779个生物学过程、41个细胞组分、108个分子功能,经KEGG富集分析得到79条相关通路,其中主要与PI3K/Akt通路密切相关。分子对接显示靶蛋白与主要化学成分结合能较强,结合力好。结论: 紫草素以多靶点、多通路的特点实现抗乙肝的作用,为后期实验验证提供依据。

Mechanism of shikonin in the treatment of viral hepatitis B based on network pharmacology and molecular docking

Objective: To systematically explore the efficacy network of shikonin in the treatment of viral hepatitis B by network pharmacology method, and to verify it by molecular docking technology. Methods: The effective compounds and targets of shikonin were obtained by traditional Chinese medicine system pharmacology database and analysis platform (TCMSP) and drug target analysis website (PharmMapper). The disease targets of hepatitis B were obtained by online human Mendelian genetic database (OMIM), human gene database (GeneCards), gene disease association database (DisGeNET) and toxicity and gene comparison database (CTD). The common targets of shikonin and hepatitis B were obtained by target mapping. The relationship information between targets was obtained by STRING database. Cytoscape 3.8.2 was used for visualization, and gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out by R language. And, AutoDockTools was used to complete molecular docking. Results: A total of 63 targets including AKT serine/threonine kinase 1 (AKT1), serum albumin (ALB), non-receptor tyrosine kinase (SRC), mitogen-activated protein kinase 1 (MAPK1) and epidermal growth factor receptor (EGFR) were obtained. 1779 biological processes, 41 cell components and 108 molecular functions were obtained by GO enrichment analysis. 79 related pathways were obtained by KEGG enrichment analysis, which were mainly closely related to PI3K/Akt pathway. Molecular docking showed that the target protein had strong binding energy and good binding ability with the main chemical components. Conclusion: The anti-HBV effect of shikonin is achieved by multi-target and multi-pathway, which provides a basis for later experimental verification.