基于网络药理学及分子对接探索六味地黄丸治疗糖尿病相关骨质疏松症的分子机制
Exploration of the Molecular Mechanism of Liuwei Dihuang in Treating Diabetes-Related Osteoporosis Based on Network Pharmacology and Molecular Docking

六味地黄丸作为临床常用的滋阴补肾经典复方，常被用于糖尿病相关骨质疏松症的治疗。本研究运用网络药理学及分子对接，对六味地黄丸治疗糖尿病相关骨质疏松症的作用机制展开系统阐释。具体方法是：首先从TCMSP数据库和文献中检索筛选六味地黄丸药物中包含的主要化合物，接着通过TCMSP和BATMAN-TCM获取化合物的作用靶点，同时在GeneCards中检索疾病相关靶点，然后取其交集靶点，用STRING构建蛋白互作(PPI)网络，再通过CytoNCA筛选核心节点，随后进行GO与KEGG富集分析，最后搭建“中药–化合物–靶点”以及“通路–靶点”网络，并用分子对接验证结果。研究共筛选出73个主要化合物、234个药物作用靶点以及1215个疾病相关靶点，经过取交集得到98个候选治疗靶点，基于PPI分析和网络拓扑筛选，确定了3个核心靶点，分别是JUN、MAPK1和AKT1，结合网络分析结果与富集分析，明确了4个核心化合物，即槲皮素、山奈酚、薯蓣皂苷元和β-谷甾醇。7组核心配体–受体对接实验都呈现出较强的亲和力，其中槲皮素与JUN的结合能最低，为？9.3 kcal/mol。结果显示，六味地黄丸可能通过槲皮素、山奈酚、薯蓣皂苷元和β-谷甾醇等活性成分，与JUN、AKT1、MAPK1等关键靶点相互作用，对AGE-RAGE、脂质–动脉粥样硬化、流体剪切力–动脉粥样硬化以及IL-17等信号通路进行调控，以此发挥治疗糖尿病相关骨质疏松症的多组分–多靶点–多通路协同作用。本研究为六味地黄丸治疗糖尿病相关骨质疏松症的后续实验以及临床应用提供了理论铺垫。
Liuwei Dihuang, a classical yin-nourishing and kidney-tonifying herbal formula commonly used in clinical practice, is frequently prescribed for diabetes-related osteoporosis. In this study, we systematically elucidated the mechanisms of action of Liuwei Dihuang in the treatment of diabetes mellitus-associated osteoporosis using network pharmacology and molecular docking. The specific methods were as follows: Firstly, we identified the principal compounds contained in Liuwei Dihuang from the TCMSP database and relevant literature, then retrieved their putative targets via TCMSP and BATMAN-TCM. Disease-related targets were obtained from GeneCards, and the overlap between drug and disease targets yielded candidate therapeutic targets. These candidates were used to construct a protein-protein interaction (PPI) network in STRING, and core nodes were selected by CytoNCA, followed by GO and KEGG enrichment analysis, and finally, we built “herb-compound-target” and “pathway-target” networks and validated our findings through molecular docking. In total, we identified 73 main compounds, 234 drug-related targets, and 1215 disease-related targets. Their intersection produced 98 candidate targets, from which PPI and network topology analysis pinpointed three core targets: JUN, MAPK1, and AKT1. Integrating network and enrichment results revealed four core compounds—quercetin, kaempferol, diosgenin, and β-sitosterol. Seven core ligand-receptor docking pairs all showed strong affinities, among which quercetin had the lowest binding energy to JUN, which was ？9.3 kcal/mol. The results suggest that