Wu Yeke, Li Jiawei, Liu Min, Gao Ranran, Xie Yunfei, Li Huijing, Li Li
Department of Stomatology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, China.
School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, China.
Naunyn Schmiedebergs Arch Pharmacol. 2025 Mar 31. doi: 10.1007/s00210-025-03942-1.
Periodontitis (PD) is a complex oral inflammatory disease with diverse pathogenic factors, demanding effective multi-target therapeutic approaches. Traditional Chinese Medicine (TCM) formulations, like the Kouqiangjie Formula (KQJF), hold potential as alternative therapies due to their multiple pharmacological effects. This study comprehensively investigated the key active ingredients and molecular targets of KQJF in treating PD through a combination of network pharmacology, machine learning, Mendelian randomization (MR), and experimental validation. The active components and targets of KQJF were identified via the TCMSP and HERB databases, while PD-related genes were sourced from GeneCards, CTD, and DisGeNET. Gene expression data from GEO datasets enabled differential expression analysis. Machine learning models, including Random Forest (RF) and Support Vector Machine (SVM), were employed to evaluate the diagnostic potential of gene sets. Molecular docking was utilized to assess the interactions between active ingredients and targets, and MR analysis was conducted to explore the causal relationships with PD. Experimental validation was carried out using a rat model. The results indicated that KQJF consists of 193 active compounds that target 561 proteins, with a significant overlap of 272 targets related to PD. Key compounds such as luteolin, linolenic acid, and naringenin were identified. The SVM model demonstrated excellent predictive performance, with an AUC of 0.954. MR analysis revealed a significant causal effect of the CASP3 gene on the risk of PD (OR = 1.595, p = 0.015). Experimental findings showed that these compounds could reduce the expression of CASP3 and improve the integrity of periodontal tissues. In conclusion, luteolin, linolenic acid, and naringenin are the core compounds in KQJF, and CASP3 is an important target. This study emphasizes the great potential of KQJF for PD treatment and provides a solid data base for the development of new therapeutic strategies.
牙周炎（PD）是一种具有多种致病因素的复杂口腔炎症性疾病，需要有效的多靶点治疗方法。中药配方，如口腔洁方剂（KQJF），由于其多种药理作用，具有作为替代疗法的潜力。本研究通过网络药理学、机器学习、孟德尔随机化（MR）和实验验证相结合的方法，全面研究了KQJF治疗PD的关键活性成分和分子靶点。通过TCMSP和HERB数据库鉴定了KQJF的活性成分和靶点，而与PD相关的基因则来自GeneCards、CTD和DisGeNET。来自GEO数据集的基因表达数据用于差异表达分析。采用包括随机森林（RF）和支持向量机（SVM）在内的机器学习模型来评估基因集的诊断潜力。利用分子对接评估活性成分与靶点之间的相互作用，并进行MR分析以探索与PD的因果关系。使用大鼠模型进行实验验证。结果表明，KQJF由193种活性化合物组成，靶向561种蛋白质，其中有272个靶点与PD显著重叠。鉴定出了木犀草素、亚麻酸和柚皮苷等关键化合物。SVM模型表现出优异的预测性能，AUC为0.954。MR分析显示，CASP3基因对PD风险有显著的因果效应（OR = 1.595，p = 0.015）。实验结果表明，这些化合物可以降低CASP3的表达并改善牙周组织的完整性。总之，木犀草素、亚麻酸和柚皮苷是KQJF中的核心化合物，CASP3是一个重要靶点。本研究强调了KQJF治疗PD的巨大潜力，并为开发新的治疗策略提供了坚实的数据库。
