地黄治疗糖尿病肾病伴抑郁的网络药理学机制

Q3 Medicine Digital Chinese Medicine Pub Date : 2022-06-01 DOI:10.1016/j.dcmed.2022.06.007
Lei Xing , Chen Qingyao , Wang Xiaoping , Xu Jie , Gao Yazhen , Lin Qiaohong , Ye Zuwen , Zhang Jieyan , Si Qin , Wang Fang
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引用次数: 2

摘要

目的基于网络药理学,探讨地黄治疗糖尿病肾病(DN)合并抑郁的分子机制。方法通过中药综合药理学研究平台(TCMIP)、中药系统药理学数据库与分析平台(TCMSP)及相关文献对地黄进行成分鉴定。通过结合SwissTargetPrediction和PubChem数据库检测组件目标。从治疗靶点数据库(TTD)、DisGeNET和Ensembl数据库中收集疾病靶点,以“糖尿病肾病”和“抑郁症”为关键词。利用Venny 2.1.0软件绘制疾病组分靶点,获取潜在靶点。利用Search Tool for Retrieval of Interacting Genes/Proteins (STRING)数据库和Cytoscape 3.7.2构建蛋白-蛋白相互作用(PPI)网络。基于COXPRESdb 7.3收集关键靶点的共表达基因。利用R语言对潜在目标进行基因本体(GO)和京都基因与基因组百科全书(KEGG)富集分析。使用Discovery Studio 4.5对目标组件对接进行验证和评估。结果根据数据库和文献报道,地黄中含有65种有效成分,155个相关靶点治疗DN合并抑郁症。PPI筛选显示,关键靶点包括丝氨酸/苏氨酸蛋白激酶1 (AKT1)、信号传导与激活因子转录3 (STAT3)、白细胞介素6 (IL-6)、丝裂原活化蛋白激酶1 (MAPK1)、血管内皮生长因子A (VEGFA)等。氧化石墨烯富集分析主要涉及脂质代谢、蛋白质分泌调节、细胞稳态和磷脂酰肌醇3激酶活性等生物学过程。KEGG通路富集分析包括AGE-RAGE信号通路在糖尿病补体、胰岛素抵抗(IR)、神经营养因子信号通路、toll样受体信号通路、松弛素信号通路、表皮生长因子受体酪氨酸激酶抑制剂(EGFR-TKIs)等中的作用。分子对接表明,该靶点对水苏糖、甘露糖、毛蕊糖、黑糖等具有较高的亲和力。结论基于网络药理学,本研究初步预测地黄通过调节炎症、糖代谢、神经等作用治疗DN合并抑郁。
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Mechanisms of Dihuang (Rehmanniae Radix) in treating diabetic nephropathy complicated with depression based on network pharmacology

Objective

To predict the molecular mechanism of Dihuang (Rehmanniae Radix) in the treatment of diabetic nephropathy (DN) complicated with depression based on network pharmacology.

Methods

The components of Dihuang (Rehmanniae Radix) were identified from the Integrated Pharmacology-based Research Platform of Traditional Chinese Medicine (TCMIP), Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and relevant literature. The component targets were detected by combining the SwissTargetPrediction and PubChem databases. Disease targets were collected from the Therapeutic Target Database (TTD), DisGeNET, and Ensembl databases with “diabetic nephropathy” and “depression” as keywords. The disease-component targets were mapped using Venny 2.1.0 to obtain potential targets. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and Cytoscape 3.7.2. The co-expression genes of the key targets were collected based on the COXPRESdb 7.3. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed for potential targets using R language. Target-component docking was verified and evaluated using Discovery Studio 4.5.

Results

According to the databases and literature reports, Dihuang (Rehmanniae Radix) contained 65 active components, and had 155 related targets for the treatment of DN complicated with depression. PPI screening showed that the key targets included serine/threonine protein kinase 1 (AKT1), signal transducer and activator transcription 3 (STAT3), interleukin 6 (IL-6), mitogen-activated protein kinase 1 (MAPK1), and vascular endothelial growth factor A (VEGFA), etc. GO enrichment analysis mainly involved biological processes, such as lipid metabolism, protein secretion regulation, cell homeostasis, and phosphatidylinositol 3 kinase activity. KEGG pathway enrichment analysis included the role of the AGE-RAGE signaling pathway in diabetic complements, insulin resistance (IR), neurotrophin signal path, Toll-like receptor signaling pathway, relaxin signaling pathway, epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), etc. Molecular docking showed that the target had high affinity for stachyose, manninotriose, verbascose, nigerose, etc.

Conclusion

Based on network parmacology, this study preliminarily predict the effects of Dihuang (Rehmanniae Radix) in treating DN complicated with depression by regulating inflammation, glucose metabolism, nution nerve, etc.

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来源期刊
Digital Chinese Medicine
Digital Chinese Medicine Medicine-Complementary and Alternative Medicine
CiteScore
1.80
自引率
0.00%
发文量
126
审稿时长
63 days
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