Network pharmacology-based prediction of active ingredient and Mechanisms of Astragalus membranaceus and Panax notoginseng coupled-herbs against Diabetic neuropathic pain

药物数据库 三七 小桶 系统药理学 计算生物学 药理学 传统医学 基因 化学 生物 医学 基因表达 生物化学 基因本体论 替代医学 药品 病理
作者
Ruili Li,Wei Zhang,Minna Yao,Jingwen Wang
出处
期刊:Letters in Drug Design & Discovery [Bentham Science]
卷期号:20 (11): 1830-1845
标识
DOI:10.2174/1570180819666220602142704
摘要

Background: Diabetic neuropathic pain seriously affects the quality of a patient’s life. To predict molecular mechanism based on network pharmacology and verify the interaction between the active ingredient of Astragalus membranaceus and Panax notoginseng coupled-herbs (AP) and target genes related to Diabetic neuropathic pain (DNP) molecular docking assay was performed. AP and their target genes related to DNP were analyzed based on network pharmacology followed by experimental validation. Methods: TCMSP, PubMed and CNKI websites were used to acquire active components in AP. OMIM, DrugBank database and DisGeNET database were used to collect and analyze target genes related to DNP. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) analysis were conducted in the DAVID database. The protein-protein interaction (PPI) network model was constructed by introducing the selected components-disease common target into the string database. Auto- Dock Vina 1.1.2 was used to dock receptor proteins with small ligand molecules. VonFrey’s statement was used to detect mechanical allodynia of DNP rats. Potential targets were detected by Western blot assay. Results: We decided that 22 and 9 chemical compositions possessed the fair ability of absorption, distribution, metabolism and excretion in Astragalus membranaceus and Panax notoginseng, respectively. These active compositions act on 70 target genes related to DNP. The core gene in the protein-protein interaction network are CAT, ESR1, HMOX1, IL1β, IL6, NFE2L2, NOS2, PPARG, PTGS2 and TNF, etc. Furthermore, GO, and KEGG pathway enrichment analyses indicated that DNP related target genes regulated by AP exist in multiple signaling pathways, including insulin resistance, PI3K-Akt signaling, HIF-1 signaling pathway, Fluid shear stress and atherosclerosis, and AGE-RAGE signaling pathway etc. AP inhibited mechanical hyperalgesia and reduced SERPINE1, FN1, IL1β, and IL6 expression of diabetic neuropathic rats in a dose-dependent manner. Conclusion: We first confirm that AP possess an anti-DNP effect through multiple signaling pathways based on network pharmacology. These results provide a theoretical basis for us to further research on the molecular mechanism of AP in the treatment of DNP.

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