Mechanism of Wumei Pill in the Treatment of Non-Erosive reflux disease from the Perspective of Network Pharmacology and Molecular docking

Objective:Based on network pharmacology and molecular docking to explore the mechanism of Wumei Pill in the treatment of non-erosive reflux disease(NERD).Method:We collected the active ingredients and targets of Wumei Pill by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),and collected NERD related targets through Genecards,PharmGKB,Drugbank,DisGeNET,OMIM,CTD and TTD databases.Intersection targets of Wumei Pill targets and NERD related targets were the potential targets of Wumei Pill in the treatment of NERD.We imported the intersection targets into the STRING database to obtain the PPI network,and obtained the hub targets.The network diagram of"Drugs-Potential active ingredients-Potential targets"was constructed by Cytoscape 3.7.2 software.We used R software to perform Gene Ontology function enrichment analysis(GO)and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis(KEGG)on hub targets,and then performed molecular docking verification.Results:There were 129 active ingredients and 213 drug targets of Wumei Pill of which 114 were the intersection targets.1587 GO enrichment items were identified(P<0.05),including 1,491 biological processes,11 cell components,and 85 molecular functions.143 KEGG pathways(P<0.05),mainly related to Kaposi sarcoma-associated herpesvirus infection,IL-17 signaling pathway,the TNF signaling pathway,MAPK signaling pathway.Results of molecular docking showed that the potential active ingredients in Wumei Pill had relatively stable binding activity to the key targets.Conclusion:Wumei pill for the treatment of non-erosive reflux disease are main active ingredients quercetin,kaempferol,beta sitosterol,Isocorypalmine,Stigmasterol,rutaecarpine,etc,the main targets is JUN,TP53,AKT1,may inhibit excessive inflammation,antioxidant therapy effect into full play.This provided a certain theoretical basis for clinical application.

Mining Functional Gene Modules Linked with Rheumatoid Arthritis Using a SNP-SNP Network

The identification of functional gene modules that are derived from integration of information from different types of networks is a powerful strategy for interpreting the etiology of complex diseases such as rheumatoid arthritis （RA）. Genetic variants are known to increase the risk of developing RA. Here, a novel method, the construction of a genetic network, was used to mine functional gene modules linked with RA. A polymorphism interaction analy- sis （PIA） algorithm was used to obtain cooperating single nucleotide polymorphisms （SNPs） that contribute to RA disease. The acquired SNP pairs were used to construct a SNP-SNP network. Sub-networks defined by hub SNPs were then extracted and turned into gene modules by mapping SNPs to genes using dbSNP database. We per- formed Gene Ontology （GO） analysis on each gene module, and some GO terms enriched in the gene modules can be used to investigate clustered gene function for better understanding RA pathogenesis. This method was applied to the Genetic Analysis Workshop 15 （GAW 15） RA dataset. The results show that genes involved in func- tional gene modules, such as CD160 （rs744877） and RUNX1 （rs2051179）, are especially relevant to RA, which is supported by previous reports. Furthermore, the 43 SNPs involved in the identified gene modules were found to be the best classifiers when used as variables for sample classification.