【目的】 采用网络药理学与分子对接探讨加味小陷胸汤对 2 型糖尿病（T2DM）和阻塞性睡眠呼吸暂停（OSA）“异病同 治”的作用机制。【方法】 在中药系统药理学数据库与分析平台（TCMSP）检索及筛选加味小陷胸汤（黄连、半夏、瓜蒌、柴 胡、丹参、赤芍、黄芪）中7味中药的活性成分及相关靶点，利用Swiss Target Prediction对活性成分进行靶点预测，其后运用 UniProt数据库进行靶点基因标准化。利用DisGeNET、OMIM、Gene Cards等数据库获得T2DM和OSA的主要致病靶点，利用 韦恩图对疾病相关靶点与活性成分作用靶点取交集，获得加味小陷胸汤“异病同治”T2DM 和 OSA 的潜在作用靶点。借助 STRING数据库及Cytoscape 3.10.2软件分别构建潜在作用靶点的蛋白质-蛋白质相互作用（PPI）网络和“药物-成分-靶点”网 络，通过网络拓扑分析筛选出核心活性成分和核心靶点。通过Metascape数据库对潜在作用靶点进行基因本体论（GO）功能及 京都基因与基因组百科全书（KEGG）通路富集分析。利用 AutoDock 软件对筛选出的核心靶点与化合物进行分子对接验证。 【结果】 157个加味小陷胸汤活性成分可作用于1 043个蛋白靶点，与1 798个OSA疾病相关靶点和3 466个T2DM疾病相关靶 点比对后，得到253个潜在作用靶点。GO功能富集分析显示，潜在作用靶点核心化学成分主要参与了磷代谢的上调、细胞 迁移的调节、循环系统过程、激素水平的调节等生物过程。KEGG通路富集分析得到Rap1、AGE-RAGE、cAMP、阿尔茨海 默病等通路。PPI和“药物-成分-靶点”网络拓扑分析筛选出IL-6、TNF、Akt1、IL-1β、EGFR等39个核心靶点以及丹酚酸 B、丹参醛、黄芩苷、姜黄素等核心活性成分，分子对接显示上述成分受体与核心蛋白配体能稳定对接。【结论】 加味小陷胸 汤“异病同治”T2DM 和 OSA 的共性药效物质基础为丹酚酸 B、黄芩苷、姜黄素等，其共同作用机制可能与 IL-6、TNF、 Akt1等关键靶点，调控Rap1、AGE-RAGE、cAMP等信号通路相关。

Objective To explore the mechanism of Modified Xiaoxianxiong Decoction（MXD） in “treating different diseases with the same method” for type 2 diabetes mellitus（T2DM） and obstructive sleep apnea（OSA） using network pharmacology and molecular docking. Methods Active components and related targets of the seven herbs in MXD（composed of Coptidis Rhizoma，Pinelliae Rhizoma，Trichosanthis Fructus，Bupleuri Radix，Salviae Miltiorrhizae Radix et Rhizoma，Paeoniae Radix Rubra，Astragali Radix） were retrieved and screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform（TCMSP）. Swiss Target Prediction was used for target prediction of active components，followed by gene standardization using the UniProt database. Disease-related targets of T2DM and OSA were obtained from DisGeNET， OMIM， and GeneCards databases. A Venn diagram was used to identify overlapping targets between disease-related targets and active component-related targets，yielding potential therapeutic targets of MXD for both T2DM and OSA. The STRING database and Cytoscape 3.10.2 were employed to construct a protein-protein interaction（PPI） network and a “drugcomponent-target” network，respectively. Core active components and core targets were identified through network topology analysis. GO functional and KEGG pathway enrichment analyses were performed on potential targets using Metascape. Molecular docking validation was conducted using AutoDock to assess binding affinity between core targets and compounds. Results A total of 157 active components of MXD acted on 1 043 protein targets. After comparison with 1 798 OSA-related targets and 3 466 T2DM-related targets， 253 potential therapeutic targets were identified. GO enrichment analysis revealed that these targets were primarily involved in biological processes such as upregulation of phosphorus metabolism，regulation of cell migration，circulatory system processes，and hormone level regulation. KEGG pathway analysis identified key pathways including Rap1，AGE-RAGE，cAMP， and Alzheimer’s disease. PPI and “drug-component-target” network topology analysis screened 39 core targets （e.g.，IL-6，TNF，Akt1，IL-1β，EGFR） and core active components（e.g.，salvianolic acid B，tanshinone IIA， baicalin， curcumin）. Molecular docking confirmed stable binding between these components and their corresponding target proteins. Conclusion The common pharmacodynamic basis of MXD in “treating different diseases with the same method” for T2DM and OSA includes active components such as salvianolic acid B， baicalin， and curcumin. The shared mechanism may involve key targets（e. g.， IL-6， TNF， Akt1） and modulation of signaling pathways such as Rap1，AGE-RAGE，and cAMP.

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国家自然科学基金资助项目（编号：82374380）；深圳市“医疗卫生三名工程”项目资助（编号：SZZYSM202202010）；深圳市 福田区卫生健康系统科研项目（编号：FTWS2022036）；广东省基础与应用基础研究基金项目（编号：2023A1515220236）