Wang Hao, Fan Bingbing, Liu Mingxuan, Shu Qiong, Huang Yidi, Sun Qinglu, Wang Hailong
Department of Rheumatology and Immunology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Dongcheng District, Beijing, China.
Department of Rheumatology and Immunology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Haidian District, Beijing, China.
Medicine (Baltimore). 2025 Sep 12;104(37):e44266. doi: 10.1097/MD.0000000000044266.
Given the increasing incidence and disability rate of rheumatoid arthritis (RA) year by year, RA has become a common cause of disability. Danggui Niantong Decoction (DGNTD) has been shown to have therapeutic effects on RA. However, to date, its bioactive components and potential targets remain unclear. To systematically explore the potential mechanisms of DGNTD in the treatment of RA, we utilized a combination of network pharmacology, Mendelian randomization, molecular docking, and molecular dynamics simulation. We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database to identify DGNTD's active ingredients and potential targets, and GeneCards to screen RA-related targets. Common targets were identified via Venn analysis. We built a protein-protein interaction network and a drug-ingredient-target map with Cytoscape. Based on shared targets, we conducted gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses to reveal key pathways. To validate results, we used R for Mendelian randomization to assess core targets' correlation with RA. We used Autodock for molecular docking and GROMACS for dynamics simulations to verify complex stability. DGNTD contains 316 active ingredients and 276 potential targets. Through protein-protein interaction network analysis and drug-ingredient-target network screening, we identified 215 active ingredients and 200 common targets, with quercetin and naringenin as core active ingredients. The core targets included RAC-alpha serine/threonine-protein kinase, cellular tumor antigen p53, signal transducer and activator of transcription 3, mitogen-activated protein kinase 1, mitogen-activated protein kinase 3, and Myc proto-oncogene protein. The Kyoto encyclopedia of genes and genomes and gene ontology enrichment analyses revealed 186 signaling pathways, with core targets mainly involving the PI3K/AKT pathway, lipid metabolism, and atherosclerosis-related biological processes. After validation through Mendelian randomization, RAC-alpha serine/threonine-protein kinase and mitogen-activated protein kinase 3 may be key targets for the treatment of RA by DGNTD. The molecular docking and dynamics simulations showed that the complexes formed by the core active ingredients and key targets exhibited strong stability. DGNTD exerts its therapeutic effects on RA through the synergistic action of multiple components, targets, and pathways, with its anti-inflammatory effects and potential molecular mechanisms being particularly noteworthy and warranting further investigation.
鉴于类风湿关节炎（RA）的发病率和致残率逐年上升，RA已成为导致残疾的常见原因。当归拈痛汤（DGNTD）已被证明对RA具有治疗作用。然而，迄今为止，其生物活性成分和潜在靶点仍不清楚。为了系统地探索DGNTD治疗RA的潜在机制，我们结合了网络药理学、孟德尔随机化、分子对接和分子动力学模拟。我们使用中药系统药理学数据库和分析平台数据库来识别DGNTD的活性成分和潜在靶点，并使用GeneCards筛选RA相关靶点。通过韦恩分析确定共同靶点。我们用Cytoscape构建了蛋白质-蛋白质相互作用网络和药物-成分-靶点图。基于共享靶点，我们进行了基因本体论和京都基因与基因组百科全书富集分析，以揭示关键途径。为了验证结果，我们使用R进行孟德尔随机化，以评估核心靶点与RA的相关性。我们使用Autodock进行分子对接，使用GROMACS进行动力学模拟，以验证复合物的稳定性。DGNTD包含316种活性成分和276个潜在靶点。通过蛋白质-蛋白质相互作用网络分析和药物-成分-靶点网络筛选，我们确定了215种活性成分和200个共同靶点，其中槲皮素和柚皮素为核心活性成分。核心靶点包括RAC-α丝氨酸/苏氨酸蛋白激酶、细胞肿瘤抗原p53、信号转导和转录激活因子3、丝裂原活化蛋白激酶1、丝裂原活化蛋白激酶3和Myc原癌基因蛋白。京都基因与基因组百科全书和基因本体论富集分析揭示了186条信号通路，核心靶点主要涉及PI3K/AKT通路、脂质代谢和动脉粥样硬化相关的生物学过程。通过孟德尔随机化验证后，RAC-α丝氨酸/苏氨酸蛋白激酶和丝裂原活化蛋白激酶3可能是DGNTD治疗RA的关键靶点。分子对接和动力学模拟表明，核心活性成分与关键靶点形成的复合物具有很强稳定性。DGNTD通过多种成分、靶点和途径的协同作用对RA发挥治疗作用，其抗炎作用和潜在分子机制尤其值得关注，有待进一步研究。
