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Study on pharmacodynamic mechanism of compound Shuanghuanglian in prevention and treatment of pneumonia based on network pharmacology and association analysis
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作者 Xiao-Lin Zhang Cao Di +4 位作者 Long Zhang Chao-Chao Hua De-Hui Ma Hui-Hui Liu Ming-Jun Liu 《Medical Data Mining》 2021年第3期37-46,共10页
Background:Platform for prediction and analysis of Chinese medicine against coronavirus disease 2019(TCMAntiCOVID-19 V1.0)was used to explore the active ingredients,key targets and mechanisms of the compound coronavir... Background:Platform for prediction and analysis of Chinese medicine against coronavirus disease 2019(TCMAntiCOVID-19 V1.0)was used to explore the active ingredients,key targets and mechanisms of the compound coronavirus disease 2019(COVID-19),It will provide a reference for the clinical application of this prescription as a broad-spectrum agent in the prevention and treatment of pneumonia.It will also win valuable time for finding symptomatic Chinese medicine prescriptions and vaccine research and development.Methods:Set Banxia Tianma Baizhu decoction as the negative control.Qingfei Paidu decoction as the positive control,and use TCMAntiCOVID-19 V1.0 platform to predict the potential efficacy of compound Shuanghuanglian.We used the quantitative evaluation algorithm of multi-target drugs for the network disturbance of disease,by comparing the changes of network topological characteristics before and after drug intervention,and using the disturbance rate to evaluate the drug’s dryness for disease prediction.Using batman-TCM,the credibility card value of the target sets 20,then the target of traditional Chinese medicine composition is predicted,the heterogeneous network of traditional Chinese medicine composition-drug target-disease target is established.The interaction of related network is realized by JavaScript Visualization is realized,and cycloscape is edited.The average connectivity,the average shortest path length,the centrality of connectivity and the centrality of network compactness are calculated by using R’s iGraph package,and nulldistribution is used as the overall distribution to correct the disturbance rate of drugs to the real network,so as to evaluate the stability of network topology and explore its mechanism.Results:The key targets of COVID-19 were Aif1,Ccl2,Cdc20,Cxcl13,Fcer1g,Ido1,Ifng,Il10,Il1rnIl6,Ncf4,Ptger4,Spi1,Tnf,Xcl1;after the intervention,the average connectivity,the average shortest path length,the network connectivity centrality and the network tightness centrality were(2.31e+1),(2.41e+0),(6.21e−1),(1.68e−2)respectively;the total scores of network stability evaluation of drug intervention diseases were 18.29,12.59 and 19.10 respectively.Conclusion:Compound Shuanghuanglian can effectively break the stability of the disease network of COVID-19,and the overall effect of prevention and treatment of COVID-19 is close to that of the positive control Qingfei Paidu decoction,which is significantly better than that of the negative control Banxia Tianma Baizhu decoction.That is because compound Shuanghuanglian mainly acts on Aif1,Ccl2,Cdc20,Cxcl13,Fcer1g and other key targets.Compound Shuanghuanglian plays important role of inhibiting the inflammatory response of patients with COVID-19 and alleviating lung injury,so as to achieve the purpose of treating COVID-19.At the same time,in the initial stage of COVID-19 and other sudden infectious pneumoniausing compound Shuanghuanglian can win valuable time before finding symptomatic Chinese medicine prescription and vaccine research. 展开更多
关键词 Compound Shuanghuanglian Coronavirus disease 2019 TCMAntiCOVID-19 Network pharmacology pharmacodynamic mechanism
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