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基于数据挖掘的陈皮与木香药对高频应用芳香类中药治疗便秘的网络药理学研究

[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].

作者信息

Wang Liang-Feng, Zhang Xiao-Fei, Li Hui-Ting, Liu Xiao-Li, Ren Gui-Lin, Wang Yao, Cha Qing-Lin, Yang Ming, Wang Fang

机构信息

Key Laboratory of Modern Preparation of Traditional Chinese Medicine under Ministry of Education, Jiangxi University of Traditional Chinese Medicine Nanchang 330004, China.

Key Laboratory of Modern Preparation of Traditional Chinese Medicine under Ministry of Education, Jiangxi University of Traditional Chinese Medicine Nanchang 330004, China College of Pharmacy, Shaanxi University of Chinese Medicine Xianyang 712046, China.

出版信息

Zhongguo Zhong Yao Za Zhi. 2020 May;45(9):2103-2114. doi: 10.19540/j.cnki.cjcmm.20200221.304.

DOI:10.19540/j.cnki.cjcmm.20200221.304
PMID:32495559
Abstract

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 CYP19 A1, PPARA, PGR, ACHE, SLC6 A2 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, Ca~(2+) 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 CYP19 A1, PPARA, PGR, ACHE, SLC6 A2 and other targets, providing a new idea and method for the further study of aromatic traditional Chinese medicine in the treatment of constipation.

摘要

在本研究中,基于数据挖掘并通过网络药理学方法,我们分析了芳香类中药治疗便秘高频使用药对的作用机制。通过数据挖掘获取用于治疗便秘的芳香类中药,并以陈皮-木香药对作为研究对象。采用水蒸气蒸馏法提取陈皮和木香的挥发油,运用气相色谱-质谱联用仪(GC-MS)检测挥发油的化学成分。通过PubChem、TCMSP、STITCH和瑞士靶点预测数据库检索陈皮和木香挥发油的作用靶点。在OMIM、Genecards-Search Resuits和TTD数据库中预测并筛选便秘的相关靶点。将获取的靶点导入Cytoscape 3.7.1,利用R语言构建蛋白质-蛋白质相互作用(PPI)网络图并进行GO和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。使用Discovery Studio 2.5软件验证成分与靶点之间的分子对接。其中,治疗便秘最常用的芳香类中药药对为陈皮-木香。通过GC-MS共检测到33种化合物,预测陈皮和木香挥发油治疗便秘的共有180个共同作用靶点。关键靶点包括CYP19 A1、PPARA、PGR、ACHE、SLC6 A2等。GO富集分析表明,陈皮和木香挥发油的活性主要涉及循环系统、血液循环和类固醇激素结合等生物学过程。在KEGG富集通路中,神经活性配体-受体相互作用、内分泌抵抗、Ca²⁺信号通路和IL-17信号通路对便秘有显著影响。分子对接结果显示,与便秘治疗相关的靶点蛋白PGR与γ-亚麻酸、二氢-α-紫罗兰酮、α-桉叶醇、氧化石竹烯和β-紫罗兰酮具有良好的结合作用。结果表明,运用数据挖掘技术和网络药理学揭示了芳香类中药高频使用中陈皮和木香挥发油的活性成分可主要通过CYP19 A1、PPARA、PGR、ACHE、SLC6 A2等靶点治疗便秘,为芳香类中药治疗便秘的进一步研究提供了新思路和方法。

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