目的 整合数据挖掘、生物信息学、网络药理学和分子动力学方法，探究慢性阻塞性肺疾病急性加重（acute exacerbation of chronic obstructive pulmonary disease，AECOPD）不同基础证的用药规律及分子调控机制。方法 检索并收集含证型信息的中药复方治疗AECOPD临床研究文献，提取证型、方名、组成、剂量等信息。基于RStudio平台，联合统计描述、Apriori算法和Phi相关系数分析，确定高频基础证与核心中药。利用ccTCM数据库收集中药成分及靶点，通过SwissADME进行类药性评估，SwissTargetPredict进行靶点预测。同时，从GEO、Genecards、NCBI-gene、Disgenet数据库获取AECOPD疾病靶点，将中药靶点与疾病靶点取交集，筛选出潜在作用靶点，借助Metascape平台进行基因本体论和通路富集分析。基于STRING构建蛋白互作网络，Cytoscape 3.9.1软件筛选关键作用靶点，分子对接和分子动力学模拟进行验证。结果 纳入1 306篇文献，涉及136个证型、577种方剂和286味中药。拆解得到AECOPD的基础证31个，其中高频基础证为痰热证、痰湿证和血瘀证。痰热证的核心中药为黄芩、桑白皮、浙贝母、瓜蒌和苦杏仁，映射到潜在作用靶点159个，功能富集于细胞运动调控和炎症信号转导相关条目，细胞组分定位在内吞囊泡和受体复合物，肿瘤坏死因子-α（tumor necrosis factor-α，TNF-α）、信号转导和转录激活因子3（signal transducer and activator of transcription 3，STAT3）和白细胞介素6（interleukin 6，IL6）为关键作用靶点，分别与汉黄芩苷、黄芩苷和绿原酸结合最好，其中TNF-α与汉黄芩苷的预测分值最高。痰湿证的核心中药为半夏、陈皮、茯苓、紫苏子、莱菔子和白芥子，映射到潜在作用靶点170个，功能富集于细胞运动调控和代谢应激反应相关条目，细胞组分定位在细胞-基质黏附结构，表皮生长因子受体（epidermal growth factor receptor，EGFR）、TNF-α、STAT3、IL6和蛋白激酶B1（protein kinase B1，AKT1）为关键作用靶点，分别与木犀草苷、咖啡酸、芹菜素、茯苓新酸A和16α-羟基松苓新酸结合最好，其中EGFR与木犀草苷的预测分值最高。血瘀证的核心中药为川芎、丹参和桃仁，映射到潜在作用靶点120个，功能富集于血管生成、缺氧应答和细胞凋亡相关条目，细胞组分定位在细胞-基质黏附结构，基质金属蛋白酶-9（matrix metalloproteinase-9，MMP-9）、B淋巴细胞瘤-2（B-cell lymphoma-2，BCL2）、白细胞介素-1β（interleukin-1β，IL1B）、Toll样受体4（Toll-like receptor 4，TLR4）、TNF-α、STAT3和AKT1为关键作用靶点，分别与丹酚酸B、二氢丹参酮I、迷迭香酸、阿魏酸、咖啡酸、4-萜品醇和洋川芎内酯A结合最好，其中MMP-9与丹酚酸B的预测分值最高。经分子动力学模拟验证，汉黄芩苷-TNF-α、木犀草苷-EGFR和丹酚酸B-MMP-9具有良好的稳定性。结论 从分子层面诠释了“同病异治”的科学内涵，痰热、痰湿和血瘀是AECOPD发病过程中的重要病机，不同基础证核心中药的调控机制差异显著，汉黄芩苷-TNF-α、木犀草苷-EGFR和丹酚酸B-MMP-9是AECOPD研究中值得关注的机制组合。

Objective To integrate data mining, bioinformatics, network pharmacology, and molecular dynamics approaches to explore the medication patterns and molecular regulatory mechanisms underlying different basic syndromes in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods Clinical research literatures on traditional Chinese medicine (TCM) compound prescriptions for treating AECOPD with syndrome type information were retrieved and collected. Information including syndrome types, prescription names, compositions, and dosages was extracted. Based on the RStudio platform, statistical description, Apriori algorithm, and Phi correlation coefficient analysis were combined to identify high-frequency basic syndromes and core TCM herbs. The ccTCM database was used to collect TCM components and their targets, with SwissADME for drug-likeness evaluation and SwissTargetPrediction for target prediction. Meanwhile, AECOPD-related disease targets were obtained from GEO, GeneCards, NCBI-Gene, and DisGeNET databases. The intersection of TCM-derived targets and disease targets was used to screen potential therapeutic targets, followed by Gene Ontology and pathway enrichment analysis via the Metascape platform. A protein-protein interaction (PPI) network was constructed based on STRING, and key therapeutic targets were screened using Cytoscape 3.9.1. Molecular docking and molecular dynamics simulation were performed for validation. Results A total of 1 306 articles were included, involving 136 syndrome types, 577 prescriptions, and 286 TCM herbs. Thirty-one basic syndromes of AECOPD were identified, with the high-frequency ones being phlegm-heat syndrome, phlegm-dampness syndrome, and blood stasis syndrome. For phlegm-heat syndrome: Core herbs were Huangqin (Scutellariae Radixs), Sangbaipi (Mori Cortex), Zhebeimu (Fritillariae Thunbergii Bulbus), Gualou (Trichosanthis Fructus), and Kuxingren (Armeniacae Semen Amarum), mapping to 159 potential therapeutic targets. Functional enrichment focused on cell motility regulation and inflammatory signal transduction, with cellular components localized in endocytic vesicles and receptor complexes. Tumor necrosis factor-α (TNF-α), signal transducer and activator of transcription 3 (STAT3), and interleukin 6 (IL6) were key therapeutic targets, optimally binding wogonoside, baicalin, and chlorogenic acid respectively, with TNF-α and wogonoside showing the highest binding score. For phlegm-dampness syndrome, core herbs were Banxia (Pinelliae Rhizoma), Chenpi (Citri Reticulatae Pericarpium), Fuling (Poria), Zisuzi (Perillae Fructus), Laifuzi (Raphani Semen), and Baijiezi (Sinapis Semen), mapping to 170 potential therapeutic targets. Functional enrichment centered on cell motility regulation and metabolic stress response, with cellular components localized in cell-matrix adhesion structures. Epidermal growth factor receptor (EGFR), TNF-α, STAT3, IL6, and protein kinase B1 (AKT1) were key therapeutic targets, optimally binding luteoloside, caffeic acid, apigenin, poricoic acid A, and 16α-hydroxytrametenolic acid respectively, with EGFR and luteoloside showing the highest binding score. For blood stasis syndrome, core herbs were Ligusticum chuanxiong Chuanxiong (Chuanxiong Rhizoma), Danshen (Salviae Miltiorrhizae Radix et Rhizoma), and Taoren (Persizae Semen), mapping to 120 potential therapeutic targets. Functional enrichment concentrated on angiogenesis, hypoxia response, and cell apoptosis, with cellular components localized in cell-matrix adhesion structures. Matrix metalloproteinase-9 (MMP-9), B-cell lymphoma-2 (BCL2), interleukin-1β (IL1B), Toll-like receptor 4 (TLR4), TNF-α, STAT3, and AKT1 were key therapeutic targets, optimally binding salvianolic acid B, dihydrotanshinone I, rosmarinic acid, ferulic acid, caffeic acid, 4-terpineol, and senkyunolide A respectively, with MMP-9 and salvianolic acid B showing the highest binding score. Molecular dynamics simulation verified that the wogonoside-TNF-α, luteoloside-EGFR, and salvianolic acid B-MMP-9 complexes demonstrated good stability. Conclusion This study elucidates the scientific connotation of “treating the same disease with different methods” at the molecular level. Phlegm-heat, phlegm-dampness, and blood stasis are important pathological mechanisms in the pathogenesis of AECOPD. The regulatory mechanisms of core TCM herbs for different basic syndromes exhibit significant differences. The combinations of wogonoside-TNF-α, luteoloside-EGFR, and salvianolic acid B-MMP-9 are noteworthy mechanistic pairs in AECOPD research.

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国家科技重大专项“四大慢病重大专项”（2023ZD0506700，2023ZD0506701）；国家科学技术部重点研发计划项目（2017YFC1700103）；国家自然科学基金面上项目（81973791）；河南省中医药科学研究专项课题（2024ZY1009）