Assessment of pulmonary infectious disease treatment with Mongolian medicine formulae based on data mining, network pharmacology and molecular docking

被引:18
|
作者
Zhou, Baochang [1 ]
Qian, Zhanhong [1 ]
Li, Qinyu [2 ]
Gao, Yuan [3 ]
Li, Minhui [1 ,2 ,4 ,5 ]
机构
[1] Inner Mongolia Med Univ, Coll Tradit Chinese Med, Hohhot 010110, Peoples R China
[2] Baotou Med Coll, Dept Pharm, Baotou 014040, Peoples R China
[3] Inner Mongolia Med Univ, Inner Mongolia Autonomous Reg Hosp Tradit Chinese, Clin Coll Tradit Chinese Med, Hohhot 010020, Peoples R China
[4] Inner Mongolia Inst Tradit Chinese & Mongolian Med, Hohhot 010010, Peoples R China
[5] Baotou Med Coll, Inner Mongolia Key Lab Characterist Geoherbs Resou, Baotou 014040, Peoples R China
基金
中国国家自然科学基金;
关键词
data mining; Mongolian medicine; network pharmacology; pulmonary tuberculosis; viral pneumonia; PNEUMONIA;
D O I
10.1016/j.chmed.2022.07.001
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Objective: Pulmonary infectious diseases (PID) include viral pneumonia (VP) and pulmonary tuberculosis (PT). Mongolian medicine (MM) is an effective treatment option in China, however, the core group medicines (CGMs) in the treatment of PID and their underlying therapeutic mechanisms remain unclear. In this study, through the method of data mining, the CGMs of MM for the treatment of PID were exca-vated, and the possible mechanism of action of the CGMs in the treatment of PID was explored by using network pharmacology.Methods: First, 89 MM formulae for the treatment of pulmonary infectious diseases collected from Gan Lu Si Bu, Meng Yi Jin Kui, People's Republic of China Ministry of Health Drug Standards (Mongolian Medicine Volume), Standard of Mongolian Medicine Preparations in Inner Mongolia (2007 Edition), and Standard of Mongolian Medicine Preparations in Inner Mongolia (2014 Edition). The CGMs of MM for PID were exca-vated through association rule analysis and cluster analysis. Then, the active ingredients and potential targets of the CGMs were obtained from TCMSP, TCMIP, BATMAN-TCM databases. PID targets information was collected from OMIM, GeneCards, and DrugBank databases. The possible targets of CGMs treatment for PID were obtained by intersection. The PPI network was constructed through the STRING database, and the topology analysis of the network was performed. Through the enrichment analysis of the inter-section targets by R language, the main action pathways and related target proteins of CGMs in the treat-ment of PID were screened out. The results were verified by molecular docking.Results: A total of 89 formulae were included, involving 164 MM herbs. The efficacy of the drugs was mainly cough-suppressing and panting-calming herbs, and heat-clearing herbs. The nature and flavor were mainly bitter and cold. The CGMs of MM to treatment of PID was excavated as the classic famous formula Sanzi Decoction (Toosendan Fructus-Chebulae Fructus-Gardeniae Fructus). A total of 28 candidate components and 237 predicted targets of CGMs were collected, and 61 common targets with PID were obtained, including key compounds such as quercetin, kaempferol, b-sitosterol and stigmastero and key targets such as VEGFA, IL6, TP53, AKT1. KEGG enrichment analysis yielded AGE-RAGE signaling path-ways, IL-17 signaling pathways, and TNF signaling pathways. Molecular docking results showed that the key targets were well matched with the potential active ingredients of CGMs.Conclusion: This study found that MM commonly used cough-suppressing and panting-calming herbs in combination with heat-clearing herbs to treat PID, and the CGMs for the treatment of PID is "Toosendan Fructus-Chebulae Fructus-Gardeniae Fructus". CGMs mainly play a role in the treatment of PID by acting on VEGFA, IL6, TP53, AKT1 and other targets, regulating AGE-RAGE signaling pathways, IL-17 signaling path-ways, and TNF signaling pathways.(c) 2022 Tianjin Press of Chinese Herbal Medicines. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:432 / 448
页数:17
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