目的 整合數(shù)據(jù)挖掘、生物信息學、網(wǎng)絡藥理學和分子動力學方法，探究慢性阻塞性肺疾病急性加重（acute exacerbation of chronic obstructive pulmonary disease，AECOPD）不同基礎證的用藥規(guī)律及分子調控機制。方法 檢索并收集含證型信息的中藥復方治療AECOPD臨床研究文獻，提取證型、方名、組成、劑量等信息。基于RStudio平臺，聯(lián)合統(tǒng)計描述、Apriori算法和Phi相關系數(shù)分析，確定高頻基礎證與核心中藥。利用ccTCM數(shù)據(jù)庫收集中藥成分及靶點，通過SwissADME進行類藥性評估，SwissTargetPredict進行靶點預測。同時，從GEO、Genecards、NCBI-gene、Disgenet數(shù)據(jù)庫獲取AECOPD疾病靶點，將中藥靶點與疾病靶點取交集，篩選出潛在作用靶點，借助Metascape平臺進行基因本體論和通路富集分析?；赟TRING構建蛋白互作網(wǎng)絡，Cytoscape 3.9.1軟件篩選關鍵作用靶點，分子對接和分子動力學模擬進行驗證。結果 納入1 306篇文獻，涉及136個證型、577種方劑和286味中藥。拆解得到AECOPD的基礎證31個，其中高頻基礎證為痰熱證、痰濕證和血瘀證。痰熱證的核心中藥為黃芩、桑白皮、浙貝母、瓜蔞和苦杏仁，映射到潛在作用靶點159個，功能富集于細胞運動調控和炎癥信號轉導相關條目，細胞組分定位在內吞囊泡和受體復合物，腫瘤壞死因子-α（tumor necrosis factor-α，TNF-α）、信號轉導和轉錄激活因子3（signal transducer and activator of transcription 3，STAT3）和白細胞介素6（interleukin 6，IL6）為關鍵作用靶點，分別與漢黃芩苷、黃芩苷和綠原酸結合最好，其中TNF-α與漢黃芩苷的預測分值最高。痰濕證的核心中藥為半夏、陳皮、茯苓、紫蘇子、萊菔子和白芥子，映射到潛在作用靶點170個，功能富集于細胞運動調控和代謝應激反應相關條目，細胞組分定位在細胞-基質黏附結構，表皮生長因子受體（epidermal growth factor receptor，EGFR）、TNF-α、STAT3、IL6和蛋白激酶B1（protein kinase B1，AKT1）為關鍵作用靶點，分別與木犀草苷、咖啡酸、芹菜素、茯苓新酸A和16α-羥基松苓新酸結合最好，其中EGFR與木犀草苷的預測分值最高。血瘀證的核心中藥為川芎、丹參和桃仁，映射到潛在作用靶點120個，功能富集于血管生成、缺氧應答和細胞凋亡相關條目，細胞組分定位在細胞-基質黏附結構，基質金屬蛋白酶-9（matrix metalloproteinase-9，MMP-9）、B淋巴細胞瘤-2（B-cell lymphoma-2，BCL2）、白細胞介素-1β（interleukin-1β，IL1B）、Toll樣受體4（Toll-like receptor 4，TLR4）、TNF-α、STAT3和AKT1為關鍵作用靶點，分別與丹酚酸B、二氫丹參酮I、迷迭香酸、阿魏酸、咖啡酸、4-萜品醇和洋川芎內酯A結合最好，其中MMP-9與丹酚酸B的預測分值最高。經分子動力學模擬驗證，漢黃芩苷-TNF-α、木犀草苷-EGFR和丹酚酸B-MMP-9具有良好的穩(wěn)定性。結論 從分子層面詮釋了“同病異治”的科學內涵，痰熱、痰濕和血瘀是AECOPD發(fā)病過程中的重要病機，不同基礎證核心中藥的調控機制差異顯著，漢黃芩苷-TNF-α、木犀草苷-EGFR和丹酚酸B-MMP-9是AECOPD研究中值得關注的機制組合。

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.

R285

國家科技重大專項“四大慢病重大專項”（2023ZD0506700，2023ZD0506701）；國家科學技術部重點研發(fā)計劃項目（2017YFC1700103）；國家自然科學基金面上項目（81973791）；河南省中醫(yī)藥科學研究專項課題（2024ZY1009）