基于逆向网络药理学和分子对接预测治疗骨衰老的中草药活性成分OA
Predicting Active Components of Chinese Herbal Medicines for Treating Bone Aging Based on Reverse Network Pharmacology and Molecular Docking
目的 应用逆向网络药理学和分子对接技术探寻治疗骨衰老的潜在中草药活性成分及其作用机制,并进行初步实验验证.方法 从GEO数据库获取转录组数据,用GEO2R分析差异基因得到骨衰老特征基因群,构建PPI网络识别关键靶点,进行GO和KEGG富集分析.通过Degree、MCC、Stress三种算法取交集获得疾病核心靶点,利用核心靶点逆向寻找具有治疗骨衰老潜力的中草药,并进行药物活性分析,将药物活性成分与疾病核心靶点进行分子对接,进一步筛选代表药物,构建衰老骨细胞模型和动物模型初步验证其疗效.细胞实验分为4 组:对照组(Control)、骨衰老组(D-Gal)、槲皮素+骨衰老组(Que+D-Gal)以及槲皮素组(Que),利用D-半乳糖(10 g/L)构建衰老骨细胞模型,槲皮素(10 μM)处理D-Gal诱导的衰老骨细胞,通过SA-β-Gal染色观察细胞衰老情况,免疫荧光和Western blot检测细胞内p53 的蛋白表达.将 24 只C57BL/6J小鼠随机分为 4 组,每组 6 只,组别与细胞分组相同,用D-半乳糖(500 mg/kg)颈背部皮下注射构建骨衰老小鼠模型,槲皮素(50 mg/kg)灌胃,通过股骨切片HE染色观察骨保护效果.结果 获得 669 个骨衰老特征基因,主要富集于PI3K-AKT、MAPK、破骨细胞分化、长寿调节等通路,核心靶点为TP53、HSPA4、ESR1、ERBB2、GSK3B、STAT1.逆向收集到能共同作用于骨衰老 6 个核心靶点的中草药为矮地茶、艾叶、干姜、黑豆、红花、火麻仁、土茯苓,主要活性成分为谷甾醇、豆甾醇、槲皮素、木犀草素等,将疾病 6 个核心靶点与药物活性成分进行分子对接,发现豆甾醇、槲皮素、木犀草素与 6 个核心靶点均为较强结合(结合能≤-7 kcal/mol),综合考虑结合能与口服利用度,将槲皮素(Quercetin)为本研究的代表药物.细胞实验SA-β-Gal染色发现,与D-Gal组比较,Que+D-Gal组衰老细胞阳性面积明显减少(P<0.01);免疫荧光和Western blot验证发现,与D-Gal组比较,Que+D-Gal组的p53 荧光信号强度明显降低(P<0.01),p53 蛋白表达显著降低(P<0.001).小鼠股骨HE染色发现,与D-Gal组比较,Que+D-Gal组骨小梁数量增加.结论 本研究通过逆向网络药理学从大数据库中筛选到矮地茶、艾叶等中药的活性成分,如豆甾醇、槲皮素、木犀草素等可能调控衰老关键靶点TP53,与骨代谢相关通路基因如ESR1、GSK3B等协同作用,从而发挥骨保护作用.实验初步验证发现预测的代表药物之一槲皮素确实能改善骨衰老,并下调衰老关键因子p53 的表达.
Objective To explore potential active components of Chinese herbal medicines(CHMs)for treating bone aging and their mechanisms of action using reverse network pharmacology and molecular docking techniques,with preliminary experimental validation.Methods Transcriptomic data were obtained from the GEO database.GEO2R was used to analyze differentially expressed genes,identifying a characteristic bone aging gene set.A Protein-Protein Interaction(PPI)network was constructed to identify key targets,followed by Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses.Core disease targets were identified by intersecting results from three algorithms(Degree,MCC,and Stress).These core targets were used to reversely identify CHMs with potential anti-bone aging effects,followed by drug activity analysis.Molecular docking was performed between active components and core disease targets to further screen representative compounds.Senescent bone cell models and animal models were established for preliminary efficacy verification.Cell experiments were divided into 4 groups:control group(Control),bone aging group(D-Gal),quercetin+bone aging group(Que+D-Gal),and quercetin group(Que).An aging bone cell model was constructed using D-galactose(10 g/L),and quercetin(10 µM)was used to treat D-Gal-induced senescent cells.Cellular senescence was observed by SA-β-Gal staining,and p53 protein expression was detected by immunofluorescence and Western blot.Twenty-four C57BL/6J mice were randomly divided into 4 groups(6 mice per group)with the same grouping as cells.A bone aging mouse model was established via subcutaneous injection of D-galactose(500 mg/kg)on the dorsal neck,and quercetin(50 mg/kg)was administered by gavage.HE staining of femoral sections was used to observe bone protective effects.Results A total of 669 characteristic bone aging genes were identified,primarily enriched in as PI3K-AKT,MAPK,osteoclast differentiation,and longevity regulation pathways.Core targets were TP53,HSPA4,ESR1,ERBB2,GSK3B,and STAT1.Reverse screening identified CHMs acting on all six core targets:Ardisia japonica,Artemisia argyi,Zingiber officinale,Glycine max,Carthamus tinctorius,Cannabis sativa,and Smilax glabra.The main active components included β-sitosterol,stigmasterol,quercetin,and luteolin.Molecular docking between the six core targets and the active components revealed that stigmasterol,quercetin,and luteolin exhibited strong binding(binding energy≤-7 kcal/mol)to all six core targets.Considering both binding energy and oral bioavailability,quercetin was selected as the representative drug for this study.SA-β-Gal staining showed that the positive area of senescent cells in the Que+D-Gal group was significantly reduced compared to the D-Gal group(P<0.01).Immunofluorescence and Western blot confirmed that that p53 fluorescence signal intensity(P<0.01)and p53 protein expression(P<0.001)were significantly decreased in the Que+D-Gal group compared to the D-Gal group.Conclusion Through reverse network pharmacology,this study screened active components from traditional Chinese herbs such as Ardisia japonica and Artemisia argyi from large databases.Components like stigmasterol,quercetin,and luteolin may regulate the key aging target TP53 and synergize with genes in bone metabolism-related pathways(e.g.,ESR1,GSK3B),thereby exerting bone protective effects.Preliminary experimental verification has found that one of the predicted representative drugs,quercetin,can indeed improve bone aging and downregulate the expression of the key aging factor p53.
郭灕茸;刘湘;李佳昊;张颖
昆明医科大学护理学院,云南 昆明 650500云南省第一人民医院骨科,云南 昆明 650032广西医科大学第一附属医院重症医学科,广西 南宁 530021昆明医科大学护理学院,云南 昆明 650500||楚雄医药高等专科学校基础医学院,云南 楚雄 675005
医药卫生
骨衰老骨质疏松网络药理学分子对接槲皮素
Bone agingOsteoporosisNetwork pharmacologyMolecular docking simulationQuercetin
《昆明医科大学学报》 2026 (2)
21-34,14
云南省科技厅-昆明医科大学应用基础研究联合专项基金(202501AY070001-037)楚雄医药高等专科学校校内科研基金(2024ZDZX01)昆明医科大学学位与研究生教育创新基金(2025S208)
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