目的 通過關聯(lián)分析總結《中國藥典》中治療流感的中藥復方中核心藥物，并結合網(wǎng)絡藥理學與分子對接技術探索核心藥物的潛在作用機制。方法 從《中國藥典》2020年版中收集治療流感的中藥復方，并采用Excel 2021建立流感方藥數(shù)據(jù)庫，通過R studio軟件進行藥物分類、性味歸經、使用頻次、關聯(lián)分析、聚類分析和相關性分析探索用藥規(guī)律，獲得核心藥物。通過中藥系統(tǒng)藥理學數(shù)據(jù)庫與分析平臺（TCMSP）、GeneCard、OMIM和Drugbank等數(shù)據(jù)庫，篩選核心藥物活性成分及其靶點和流感疾病靶點，并對獲得的交集靶點進行基因本體（GO）和京都基因與基因組百科全書（KEGG）分析。利用Cytoscape軟件構建中藥、活性成分和靶點的網(wǎng)絡關系及蛋白質-蛋白質相互作用（PPI）網(wǎng)絡。最后，基于Vina軟件進行分子對接分析。結果 共納入中藥復方59首，涵蓋中藥201種，以頻次≥8次的中藥為高頻中藥，共19種，依次為甘草、桔梗、黃芩、連翹等；高頻藥物以補虛藥、化痰止咳平喘藥、清熱藥、解表藥為主，藥味以辛、苦、甘為主，歸經以肺經、脾經居多。通過關聯(lián)規(guī)則分析發(fā)現(xiàn)“桔梗-甘草”“陳皮-茯苓-紫蘇葉”“陳皮-茯苓-半夏”等配伍最常見；相關性分析顯示“紫蘇葉-陳皮”“白芷-防風”“茯苓-半夏”等強相關潛在藥對；聚類分析獲得5個藥物組方；復雜網(wǎng)絡分析顯示桔梗、紫蘇葉、甘草、金銀花等在治療流感的復方中位于核心地位。綜合頻次、聚類、關聯(lián)規(guī)則及復雜網(wǎng)絡分析結果，發(fā)現(xiàn)桔梗、紫蘇葉、甘草、金銀花、連翹、麻黃、苦杏仁、陳皮、半夏、茯苓為治療流感的核心中藥。通過網(wǎng)絡藥理學分析，進一步確定核心中藥的主要活性成分，包括槲皮素、山柰酚、木犀草素等，核心靶點則為TP53、TNF、JUN、IL6等，主要涉及白細胞介素-17（IL-17）、腫瘤壞死因子（TNF）信號通路等發(fā)揮治療作用。此外，關鍵活性成分與核心靶點之間能夠穩(wěn)定結合。結論 治療流感的核心中藥，可能通過槲皮素、山柰酚、木犀草素等活性成分，作用于TP53、TNF等靶點，參與IL-17、TNF等通路發(fā)揮治療作用。

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

上海中醫(yī)內科臨床重點實驗室項目（20DZ2272200）；上海市市級科技重大專項“重大突發(fā)傳染病防控關鍵核心技術研究”（ZXS004R4-2）；上海市自然科學基金項目（22ZR1460100）；張煒寶山區(qū)名中醫(yī)傳承工作室（BSMZYGZS-2024-01）