【摘要】 目的:使用网络药理学方法研究当归中具有抗神经退行性疾病的活性成分,阐释其作用机制。方法:在TCMSP数据库检索中药当归的已知化学成分,以类药五原则为标准进行筛选,待选成分上传至BAR-MAN数据库进行成分-靶点关系分析,以P<0.05作为显著功能与通路的临界值。应用String10.0构建蛋白靶点互作网络,经MCODE分析获得5个基因簇,用DAMD 6.8进行GO、KEGG富集分析,网络关系图用cytoscape3.6.0构建。结果:TCMSP数据库中当归已知成分为125个,筛选后得到7个待选成分。对应的预测靶点303个,MCODE分析后得到5个Clust er,富集分析后得到5个GO结果和优选的10条KEGG信号通路。结论:通过网络药理学方法虚拟筛选到4个活性成分包括(-)樟脑酸、阿魏酸(反式)、3-亚丁基-7-羟基苯酞和川芎内酯D,其作用机制可能为影响线粒体氧化磷酸化和细胞能量代谢。更多还原

【Abstract】 Objective: To study the active ingredients fighting neurodegenerative diseases of Danggui(Angelica sinensis) using network pharmacology, and explore its underlying mechanism. Methods: The known chemical ingredients of Danggui were searched in TCMSP database, screened in light of lipinski′ s rule of five,component target relationship was analyzed after the ingredients to be selected were uploaded to BAT-MAN database, after taking P<0.05 as critical value of significant function and pathway. String 10.0 was used to construct protein target interaction network, five gene clusters were obtained after MCODE analysis, GO and KEGG enrichments were analyzed using DAVID6.8, network diagram was constructed usign cytoscape 3.6.0. Results:There were 125 known ingredients of Danggui in TCMSP database, seven ingredients to be selected were obtained after screening. A total of 303 corresponding prediction targets and five clusters were obtained after MCODE analysis, after enrichment analysis, five results of GO and ten optimized KEGG signaling pathways were received.Conclusion: After virtual screening with network pharmacology, four active ingredients were identified:(-) camphoric acid, ferulic acid(trans), 3-butyryl-7-hydroxyphthalide and ligusticide D, and its mechanism might be to affect mitochondrial oxidative phosphorylation and cellular energy metabolism.更多还原