目的 通过生物信息学和分子动力学模拟探讨连花清瘟方的体内成分治疗流行性感冒的关键靶点和作用机制。方法 查阅文献筛选连花清瘟方体内暴露量较大的成分，并结合TCMSP数据库获取连花清瘟方潜在的活性成分，通过SwissTargetPrediction和Super-PRED数据库收集相关靶点。通过GEO、GeneCards、Drugbank数据库收集流行性感冒的作用靶点，进一步获得连花清瘟治疗流感的潜在靶标，构建“成分–疾病–靶点”网络。使用STRING数据库对潜在靶标进行蛋白互作分析，利用DAVID数据库进行基因本体（GO）功能富集和基因百科全书（KEGG）通路富集。最后采用Autodock软件进行分子对接验证，采用GROMACS v2020.6软件对分子对接复合物进行分子动力学模拟。结果 共筛选出连花清瘟方活性成分25个和520个相关靶点，收集到与流感相关的作用靶点3 255个，取交集后得到连花清瘟治疗流感的潜在作用靶点244个，其中类固醇受体辅激活因子（SRC）、信号转导和转录激活因子3（STAT3）、磷酸肌醇-3-激酶调节亚基1（PIK3R1）、表皮生长因子受体（EGFR）等为关键靶标，主要涉及Th17细胞分化、T细胞受体信号通路、PI3K/蛋白激酶B（Akt）信号通路、肿瘤坏死因子（TNF）信号通路等炎症信号通路。分子对接结果显示SRC为最关键的作用靶标，与各活性成分的结合能力最强。分子动力学模拟结果显示绿原酸–SRC复合物结合稳定。结论 连花清瘟方可能通过绿原酸、大黄酸、苦杏仁苷、连翘酯苷A等活性成分调控SRC、STAT3等靶点发挥治疗流行性感冒的作用，与介导Th17细胞分化、T细胞受体信号通路等炎症信号通路有关，为临床应用与研究提供理论基础。

Objective To explore the key targets and mechanism of Lianhua Qingwen formula absorbed components in treatment of influenza by bioinformatics analysis and molecular dynamics simulation. Methods The literature was reviewed to search the components with high exposure of Lianhua Qingwen formula in vivo as potential active ingredients of Lianhua Qingwen formula combined with the TCMSP database, and relevant targets were collected through SwissTargetPrediction and Super-PRED database. The targets of influenza were collected from GEO, GeneCards, and Drugbank databases, further the potential targets of Lianhua Qingwen formula in treatment of influenza were obtained. A network of “ingredient-disease-target” was constructed. Protein-protein interactions were analyzed for potential targets using the STRING database. GO functional enrichment and KEGG pathway enrichment were performed using the DAVID database. Autodock software was used for molecular docking validation and GROMACS v2020.6 software was used for molecular dynamics simulation of molecular docking complexes. Results A total of 25 active ingredients of Lianhua Qingwen formula and 520 related targets were screened, and 3 255 targets related to influenza were collected. A total of 244 potential targets of Lianhua Qingwen formula in treatment of influenza were obtained after taking the intersection, among which SRC, STAT3, PIK3R1, PIK3CA, and EGFR were the key targets. The above targets are mainly related to the differentiation of Th17 cells, the T-cell receptor signaling pathway, PI3K/Akt signaling pathway, TNF signaling pathway and other inflammatory signaling pathways. The molecular docking results showed that SRC was the most critical target, which had the strongest binding ability with each active ingredient, and the molecular dynamics simulation results showed that the SRC-chlorogenic acid complex was stable in binding. Conclusion Lianhua Qingwen formula may exert effects on influenza through the modulation of SRC, STAT3 and other targets by active ingredients such as chlorogenic acid, rhein, amygdalin, and forsythoside A. It is associated with inflammatory signaling pathways such as Th17 cell differentiation and T cell receptor signaling pathways. This study provides a theoretical basis for the follow-up research.

R286.4

佛山市卫生健康局医学科研课题（20240050）；佛山市“十四五”医学重点专科项目（FS2D145035）；佛山市工程技术研究中心项目