目的 通过关联分析总结《中国药典》中治疗流感的中药复方中核心药物，并结合网络药理学与分子对接技术探索核心药物的潜在作用机制。方法 从《中国药典》2020年版中收集治疗流感的中药复方，并采用Excel 2021建立流感方药数据库，通过R studio软件进行药物分类、性味归经、使用频次、关联分析、聚类分析和相关性分析探索用药规律，获得核心药物。通过中药系统药理学数据库与分析平台（TCMSP）、GeneCard、OMIM和Drugbank等数据库，筛选核心药物活性成分及其靶点和流感疾病靶点，并对获得的交集靶点进行基因本体（GO）和京都基因与基因组百科全书（KEGG）分析。利用Cytoscape软件构建中药、活性成分和靶点的网络关系及蛋白质-蛋白质相互作用（PPI）网络。最后，基于Vina软件进行分子对接分析。结果 共纳入中药复方59首，涵盖中药201种，以频次≥8次的中药为高频中药，共19种，依次为甘草、桔梗、黄芩、连翘等；高频药物以补虚药、化痰止咳平喘药、清热药、解表药为主，药味以辛、苦、甘为主，归经以肺经、脾经居多。通过关联规则分析发现“桔梗-甘草”“陈皮-茯苓-紫苏叶”“陈皮-茯苓-半夏”等配伍最常见；相关性分析显示“紫苏叶-陈皮”“白芷-防风”“茯苓-半夏”等强相关潜在药对；聚类分析获得5个药物组方；复杂网络分析显示桔梗、紫苏叶、甘草、金银花等在治疗流感的复方中位于核心地位。综合频次、聚类、关联规则及复杂网络分析结果，发现桔梗、紫苏叶、甘草、金银花、连翘、麻黄、苦杏仁、陈皮、半夏、茯苓为治疗流感的核心中药。通过网络药理学分析，进一步确定核心中药的主要活性成分，包括槲皮素、山柰酚、木犀草素等，核心靶点则为TP53、TNF、JUN、IL6等，主要涉及白细胞介素-17（IL-17）、肿瘤坏死因子（TNF）信号通路等发挥治疗作用。此外，关键活性成分与核心靶点之间能够稳定结合。结论 治疗流感的核心中药，可能通过槲皮素、山柰酚、木犀草素等活性成分，作用于TP53、TNF等靶点，参与IL-17、TNF等通路发挥治疗作用。

To summarize the core drugs for the treatment of influenza in the Chinese Pharmacopoeia through association analysis, and investigate their potential mechanisms of action using network pharmacology and molecular docking techniques. Traditional Chinese medicine compound prescriptions for treating influenza were collected from the 2020 edition of the “Chinese Pharmacopoeia”, and an influenza prescription database was established using Excel 2021. Drug classification, nature and taste, meridians, frequency of use, association analysis, cluster analysis and correlation analysis were performed through R studio software to explore the medication patterns and obtain core Chinese medicines. The key active ingredients and their corresponding targets were identified using databases like TCMSP, GeneCard, OMIM, and Drugbank. Once the intersection of these targets was found, they underwent GO functional analysis and KEGG pathway enrichment. Cytoscape software was employed to map out the interaction networks among traditional Chinese medicine, active ingredients, and targets, as well as the PPI network. Finally, molecular docking simulations were conducted with Vina software to explore the interactions between critical compounds and their main targets. A total of 59 compound prescriptions were included, covering 201 traditional Chinese medicines. The drugs with a frequency of more than seven times were high-frequency drugs, totaling 19 kinds, including Glycyrrhizae Radix et Rhizoma, Platycodonis Radix, Scutellaria Baicalensis, Forsythiae Fructus, etc. The frequently used drugs were primarily tonic agents, expectorants, cough and asthma relievers, heat-clearing medications, and antipyretics. The taste of the drugs was mainly pungent, bitter and sweet, and the meridians were mostly lung and spleen. The association rule analysis showed that “Platycodonis Radix-Glycyrrhizae Radix et Rhizoma”, “Citri Reticulatae Pericarpium-PoriaPerillae Folium”, “Citri Reticulatae Pericarpium-Poria-Pinelliae Rhizoma” were the most common compatibility; the correlation analysis showed that “Perillae Folium-Citri Reticulatae Pericarpium”, “Angelicae Dahuricae Radix-Saposhnikoviae Radix”, “PoriaPinelliae Rhizoma” and other strongly correlated potential drug pairs; Cluster analysis obtained five drug prescriptions; complex network analysis showed that Platycodonis Radix, Perillae Folium, Glycyrrhizae Radix et Rhizoma, Lonicerae Japonicae Flos, etc. were in the core position in the compound prescriptions for the treatment of influenza. Based on the findings from frequency analysis, clustering, association rule mining, and complex network analysis, it was found that Platycodonis Radix, Perillae Folium, Glycyrrhizae Radix et Rhizoma, Lonicerae Japonicae Flos, Forsythiae Fructus, Ephedrae Herba, Armeniacae Amarum Semen, Citri Reticulatae Pericarpium, Pinelliae Rhizoma, Poria are the core drugs for the treatment of influenza. Through network pharmacology analysis, the primary active compounds of the core drugs were identified, including quercetin, kaempferol, and luteolin. The key targets were TP53, TNF, JUN, and IL6, which are primarily involved in the IL-17 and TNF signaling pathways, contributing to their therapeutic effects. In addition, the key active ingredients can be stably combined with the core targets. The core Chinese medicine for the treatment of influenza may act on targets such as TP53 and TNF through active ingredients such as quercetin, kaempferol, and luteolin, and participate in pathways such as IL-17 and TNF to play a therapeutic role. This provides insights into the use of Chinese medicine for influenza prevention and treatment, offering a scientific foundation for further investigation into their mechanisms of action.

R285.5

上海中医内科临床重点实验室项目（20DZ2272200）；上海市市级科技重大专项“重大突发传染病防控关键核心技术研究”（ZXS004R4-2）；上海市自然科学基金项目（22ZR1460100）；张炜宝山区名中医传承工作室（BSMZYGZS-2024-01）