Network pharmacology-based strategy for predicting therapy targets of Sanqi and Huangjing in diabetes mellitus

被引:4
作者
Cui, Xiao-Yan [1 ]
Wu, Xiao [2 ]
Lu, Dan [3 ]
Wang, Dan [4 ]
机构
[1] Hebei Inst Drug & Med Device Control, Shijiazhuang 050011, Hebei, Peoples R China
[2] HEs Univ, Dept Basic Med, Shenyang 110163, Liaoning, Peoples R China
[3] Shenyang Sport Univ, Coll Human Kinesiol, Shenyang 110102, Liaoning, Peoples R China
[4] Shenyang Sport Univ, Coll Human Kinesiol, 36 Jinqiansong East Rd Sujiatun Dist, Shenyang 110102, Liaoning, Peoples R China
关键词
Panax notoginseng (Sanqi in Chinese); Polygonati Rhizoma (Huangjing in Chinese); Diabetes mellitus; Active compounds; Network pharmacology; Hub genes; MESSENGER-RNA EXPRESSION; POLYGONATUM-KINGIANUM; OXIDATIVE STRESS; RHIZOMA; RISK; DYSFUNCTION; GLUCOSE; FAT;
D O I
10.12998/wjcc.v10.i20.6900
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
BACKGROUND A comprehensive literature search shows that Sanqi and Huangjing (SQHJ) can improve diabetes treatment in vivo and in vitro, respectively. However, the combined effects of SQHJ on diabetes mellitus (DM) are still unclear. AIM To explore the potential mechanism of Panax notoginseng (Sanqi in Chinese) and Polygonati Rhizoma (Huangjing in Chinese) for the treatment of DM using network pharmacology. METHODS The active components of SQHJ and targets were predicted and screened by network pharmacology through oral bioavailability and drug-likeness filtration using the Traditional Chinese Medicine Systems Pharmacology Analysis Platform database. The potential targets for the treatment of DM were identified according to the DisGeNET database. A comparative analysis was performed to investigate the overlapping genes between active component targets and DM treatment-related targets. We constructed networks of the active component-target and target pathways of SQHJ using Cytoscape software and then analyzed the gene functions. Using the STRING database to perform an interaction analysis among overlapping genes and a topological analysis, the interactions between potential targets were identified. Gene Ontology (GO) function analyses and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted in DAVID. RESULTS We screened 18 active components from 157 SQHJ components, 187 potential targets for active components and 115 overlapping genes for active components and DM. The network pharmacology analysis revealed that quercetin, beta-sitosterol, baicalein, etc. were the major active components. The mechanism underlying the SQHJ intervention effects in DM may involve nine core targets (TP53, AKT1, CASP3, TNF, interleukin-6, PTGS2, MMP9, JUN, and MAPK1). The screening and enrichment analysis revealed that the treatment of DM using SQHJ primarily involved 16 GO enriched terms and 13 related pathways. CONCLUSION SQHJ treatment for DM targets TP53, AKT1, CASP3, and TNF and participates in pathways in leishmaniasis and cancer.
引用
收藏
页码:6900 / 6914
页数:15
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