基于数据挖掘的芳香类中药治疗便秘高频次使用药对“陈皮-木香”网络药理学研究

Network pharmacology research on high frequency use of Pericarpium Citri Reticulatae and Aucklandiae Radix herb pair in treatment of constipation with aromatic traditional Chinese medicine based on data mining

该研究基于数据挖掘,通过网络药理学方法,分析芳香类中药治疗便秘高频次使用药对作用机制;以数据挖掘获得芳香类中药治疗便秘高频次使用药对"陈皮-木香"为研究对象,采用水蒸气蒸馏法提取陈皮、木香中的挥发油,利用气相色谱-质谱联用仪(GC-MS)检测陈皮-木香挥发油的化学成分,经PubChem,TCMSP,STITCH,Swiss Target Prediction数据库检索陈皮-木香挥发油成分的靶点,在OMIM,Genecards-Search Resuits,TTD数据库中预测和筛选便秘的作用靶点。将得到的靶点导入Cytoscape 3.7.1构建核心靶点相互作用网络图,利用R语言进行GO功能、KEGG通路富集分析,根据KEGG富集结果构建"成分-靶点-通路"网络图。通过Discovery Studio 2.5软件对成分与靶点进行分子对接验证。其中芳香类中药治疗便秘使用频次最高的药对为陈皮-木香,通过GC-MS共检测出33种化合物,共预测出陈皮-木香药对挥发油治疗便秘的共同作用靶点180个,关键靶点涉及CYP19A1,PPARA,PGR,ACHE,SLC6A2等。GO富集分析显示陈皮-木香药对挥发油的活性主要涉及循环系统、血液循环、固醇类激素结合等生物学过程。KEGG富集通路中神经活性配体-受体相互作用、内分泌抵抗、Ca^(2+)信号通路、IL-17信号通路对便秘有显著作用,分子对接结果表明发挥治疗便秘的关键靶蛋白PGR与γ-亚麻酸(gamma-linolenic acid)、二氢-α-紫罗兰酮(dihydro-alpha-ionone)、α-桉叶醇(alpha-eudesmol)、氧化石竹烯(caryophyllene oxide)、β-紫罗兰酮(beta-ionone)结合较好。结果表明,利用数据挖掘技术及网络药理学揭示了芳香类中药高频次使用药对陈皮-木香挥发油的活性成分主要通过CYP19A1,PPARA,PGR,ACHE,SLC6A2等靶点来治疗便秘,为芳香类中药治疗便秘的深入研究提供了新的思路和方法。

Based on data mining and through the method of network pharmacology,we analyzed the mechanism of high-frequency use of herb pair in the treatment of constipation with aromatic traditional Chinese medicine in this study.Through data mining,aromatic traditional Chinese medicine was obtained for the treatment of constipation and Pericarpium Citri Reticulatae and Aucklandiae Radix herb pair was used as the research object.The volatile oil from Pericarpium Citri Reticulatae and Aucklandiae Radix was extracted by steam distillation,and the chemical compositions of the volatile oil were detected by gas chromatography-mass spectrometry(GC-MS).The targets of volatile oil from Pericarpium Citri Reticulatae and Aucklandiae Radix were searched by PubChem,TCMSP,STITCH and Swiss Target Prediction databases.The targets of constipation were predicted and screened in OMIM,Genecards-Search Resuits and TTD databases.The obtained targets were introduced into Cytoscape 3.7.1 to construct protein-protein interaction(PPI)network diagram for GO and KEGG pathway enrichment analysis by using R language.The network diagram of"component-target-pathway"was constructed according to the results of KEGG enrichment.Discovery Studio 2.5 software was used to verify the molecular docking between the components and the targets.Among them,the most frequently used pair of aromatic traditional Chinese medicine in the treatment of constipation was Pericarpium Citri Reticulatae and Aucklandiae Radix.A total of 33 compounds were detected by GC-MS,and a total of 180 common action targets of Pericarpium Citri Reticulatae and Aucklandiae Radix on volatile oil in the treatment of constipation were predicted.The key targets included CYP19A1,PPARA,PGR,ACHE,SLC6A2 and so on.GO enrichment analysis showed that the activities of Pericarpium Citri Reticulatae and Aucklandiae Radix on volatile oil were mainly involved in the biological processes such as circulatory system,blood circulation,and steroid hormone binding.In KEGG enrichment pathway,neuroactive ligand-receptor interaction,endocrine resistance,Ca2+signal pathway and IL-17 signaling pathway showed significant effect on constipation.The results of molecular docking showed that PGR,the target protein related to the treatment of constipation,had a good binding with gamma-linolenic acid,dihydro-alpha-ionone,alpha-eudesmol,caryophyllene oxide and beta-ionone.The results show that by using data mining technology and network pharmacology,it is revealed that the active components of Pericarpium Citri Reticulatae and Aucklandiae volatile oil in high frequency use of aromatic traditional Chinese medicine can be used totreat constipation mainly through CYP19A1,PPARA,PGR,ACHE,SLC6A2 and other targets,providing a new idea and method for the further study of aromatic traditional Chinese medicine in the treatment of constipation.