基于网络药理学的茵陈五苓散治疗非酒精性脂肪肝病的机制分析＊

目的 运用网络药理学,对茵陈五苓散（YCWLD）治疗非酒精性脂肪肝病(NAFLD)的机制进行系统预测及分析。方法 通过TCMSP、Batman-tcm数据库筛选出YCWLD中具有成药可能性较大以及口服吸收较佳的候选活性成分。从TCMSP和Swiss Target Prediction数据库中收集和预测候选化合物的作用靶点。利用Genecards、TTD、CooLGeN三个数据库获取NAFLD的疾病靶点,并与潜在活性成分的作用靶点进行交集分析,获得YCWLD治疗NAFLD的靶点。检索DisGenet数据库分析治疗靶点的类型。通过cytoscape 3.7.1软件构建草药-候选化合物-治疗靶点网络以及利用Uniprot、String数据库构建蛋白互作网络(PPI),阐述各分子之间的关系及关键功能分子。采用DAVID数据库对治疗靶点进行基因本体（gene ontology,GO）富集分析以及基因组百科全书（Kyoto Encyclopedia of Genes and Genomes,KEGG）通路分析,进而达到系统探讨YCWLD治疗NAFLD相关机制的目的。结果 本研究通过草药-候选化合物-治疗靶点网络分析发现,YCWLD中包含的24个候选成分可作用于NAFLD的34个靶点,候选成分中quercetin、beta-sitosterol、sitosterol可能是YCWLD发挥抗NAFLD作用的关键成分,而靶点中DPP4、NR1H3、NR1H2、SREBF1、SREBF2作用较为重要。PPI网络显示免疫及炎症相关靶点起枢纽作用。通过GO富集分析显示作用靶点涉及157个条目,KEGG分析发现NAFLD、Cytokine-cytokine receptor interaction、Insulin resistance等17条潜在信号通路可能是YCWLD预防及治疗NAFLD的主要通路。结论 本研究系统预测了YCWLD抗NAFLD的作用机制,并为下一步实验验证关键化合物、靶点及通路提供了方向。

Mechanism of Yinchenwuling Decotion against Non-alcoholic Fatty Liver Disease Dased on Network Pharmacology

Objective The mechanism of YCWLD in the treatment of nonalcoholic fatty liver disease (NAFLD) was systematically predicted and analyzed by network pharmacology.Methods The candidate active ingredient of YCWLD with high drug potential and better oral absorption were screened by TCMSP and Batman-tcm database. The target of candidate ingredient was collected and predicted from the TCMSP and Swiss Target Prediction databases. The disease target of NAFLD was obtained by using Genecards, TTD and CooLGenN databases. The intersection analysis between disease target and ingredients target was employed to obtain the therapeutic target of YCWLD against the NAFLD. The DisGenet database was searched to analyze the type of therapeutic target. The cytoscape 3.7.1 software was used to construct a herbs-candidate compound-therapeutic target network and a protein interaction network (PPI) was constructed using Uniprot and String databases to illustrate the relationship among molecules and find out the key functional molecules.Results Herbs-candidate compound-therapeutic target network analysis found that the 24 candidate components contained in YCWLD can act on 34 targets of NAFLD. Among the candidate components, quercetin, beta-sitosterol, and sitosterol may be the key ingredients of YCWLD in the treatment of NAFLD. As far as the target is concerned, DPP4, NR1H3, NR1H2, SREBF1, and SREBF2 are more prominent. The PPI network shows that immune and inflammation-related targets play a pivotal role in network. GO enrichment analysis found Therapeutic target involved 157 items. KEGG analysis found that 17 potential signaling pathways such as NAFLD, Cytokine-cytokine receptor interaction and Insulin resistance may be the main pathways for YCWLD to prevent and treat NAFLD.Conclusion This study systematically predicted the mechanism of YCWLD against NAFLD and provided direction for the next step to verify key compounds, targets and pathways.