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Exploring the mechanism of Xiaopi Hewei capsule in treating functional dyspepsia based on network pharmacology

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摘要 Objective:Functional dyspepsia(FD)is a widely prevalent gastrointestinal disorder throughout the world,whereas the efficacy of current treatment in the Western countries is limited.The traditional Chinese herbal formula Xiaopi Hewei capsule(XHC)is a clinically validated remedy in treating FD,but there is no literature expounds the underlying therapeutic mechanism of XHC so far.Methods:In the present study,the network pharmacology technology was used to explore the therapeutic mechanism of XHC in treating FD.We obtained relative compounds of XHC,potential targets of these compounds and FD-related targets by retrieving particular websites.Based on the matching results between XHC potential targets and disease targets,Protein-Protein Interaction(PPI)network was constructed to screen the hub targets by topology.Furthermore,DAVID bioinformatics resources were utilized for the enrichment analysis on GO and KEGG.Results:A total of 62 active compounds and 547 putative identified targets were screened from XHC,of which 241 overlapped with the targets of FD and were considered potential therapeutic targets.14 hub genes were recognized as potential targets of treatments.Moreover,the results of DAVID enrichment analysis indicated that XHC participated in the complex treating effects associated with anti-depression,inflammatory reaction and eradicating Helicobacter Pylori(HP).Molecular docking stimulation results showed that most bioactive compounds of XHC had a strong binding efficiency with hub genes.Conclusions:This study demonstrated that XHC has the characteristics of multi-compounds,multi-targets and multi-pathways in treating FD,which provides the theoretical basis for further research of XHC.
出处 《TMR Modern Herbal Medicine》 2020年第4期209-223,共15页 TMR现代中药
基金 This work was financial supported by the Major science and technology projects in Tibet region(Grant No:XZ201801-GA-16) School-enterprise cooperation project(Grant No:2019110031001686).
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