网络药理学预测地黄饮子调控小胶质细胞干预阿尔茨海默病的机制
周婷婷 , 白一涵 , 曲金竹 , 于淼
山西医科大学学报 ›› 2026, Vol. 57 ›› Issue (6) : 656 -664.
网络药理学预测地黄饮子调控小胶质细胞干预阿尔茨海默病的机制
Mechanisms of Dihuang Yinzi intervening Alzheimer′s disease via microglia predicted by network pharmacology
目的 基于网络药理与分子对接方法预测地黄饮子调控小胶质细胞(MG)干预阿尔茨海默病(AD)的作用机制。 方法运用中药系统药理学数据库与分析平台(TCMSP)、SwissTargetPrediction和GeneCards数据库获取地黄饮子、AD和MG相关靶点。利用Venny2.1.0在线平台获取MG和AD交集靶点。构建蛋白-蛋白相互作用(PPI)网络,筛选度值15作为重要成分。利用Cytoscape 3.10.0绘制“药物-活性成分-靶点”网络,筛选Degree200作为核心靶点。将地黄饮子与MG、AD交集靶点的相关数据导入DAVID完成GO功能注释和KEGG通路富集分析。运用AutoDock开展分子对接,利用PyMOL软件进行可视化分析。 结果 筛选得到地黄饮子活性成分69个,作用靶点484个。MG与AD交集靶点2 234个。并筛选找到丹酚酸B、五味子酯A、当归酰基戈米辛O、戈米辛R、枫马京等15个重要成分,AKT1、TP53、IL6、TREM2等10个核心靶点。GO分析显示,作用靶点主要涉及对β-淀粉样蛋白的反应、神经元胞体、MAP激酶等生物学过程及分子功能条目;KEGG分析显示,药物作用主要涉及脂质与动脉粥样硬化、神经退行性疾病、JAK-STAT等通路。分子对接显示,丹酚酸B与AKT1、五味子酯A与TREM2、当归酰基戈米辛O与TREM2、戈米辛R与TREM2、枫马京与TP53的结合能均-5 kCal/mol,氢键长度均3.5 nm,结合良好。 结论地黄饮子可能通过丹酚酸B、五味子酯A等成分靶向MG的AKT1和TREM2等关键靶点,调控炎症通路,影响MG的极化,干预AD进程。
Objective To predict the mechanism by which Dihuang Yinzi regulates microglia(MG) in the intervention of Alzheimer's disease(AD) based on network pharmacology and molecular docking methods. Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), SwissTargetPrediction, and GeneCards databases were utilized to identify targets associated with Dihuang Yinzi, AD, and MG. The Venny 2.1.0 online platform was used to identify the intersection targets between MG and AD. A protein-protein interaction(PPI) network was constructed, and components with a degree value greater than 15 were identified as important constituents. Cytoscape 3.10.0 was utilized to construct a "drug-active ingredient-target" network, and targets with a degree 200 were selected as core targets. The intersection target data of Dihuang Yinzi with MG and AD were imported into DAVID for Gene Ontology(GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. Molecular docking was conducted using AutoDock, and the results were visualized with PyMOL. Results A total of 69 active ingredients and 484 targets of Dihuang Yinzi were identified, along with 2 234 intersection targets between MG and AD. Fifteen important components were screened, such as salvianolic acid B, schisantherin A, angeloylgomisin O, gomisin R, and Marckine. Ten core targets were identified, such as AKT1, TP53, IL6, and TREM2. GO analysis revealed that the targets mainly enriched in the items in biological processes and molecular functional entries such as response to amyloid-beta, neuronal cell body, and MAP kinase. KEGG analysis indicated that the drug was mainly associated with pathways, such as lipids and atherosclerosis, neurodegenerative diseases, and JAK-STAT signaling. Molecular docking demonstrated that the binding energies of salvianolic acid B with AKT1, schisantherin A with TREM2, angeloylgomisin O with TREM2, gomisin R with TREM2, and Marckine with TP53 were all lower than -5 kCal/mol, with hydrogen bond distances all less than 3.5 nm, indicating favorable binding. Conclusion Dihuang Yinzi may intervene in the progression of AD by targeting key microglial targets(AKT1 and TREM2) in MG through active components(salvianolic acid B and schisantherin A), thereby regulating inflammatory pathways and influencing MG polarization.
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国家自然科学基金项目(81803984)
黑龙江省中医药科研项目(ZHY2023-042)
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