目的 基于数据挖掘与网络药理学方法，系统分析中药复方治疗感染性肺炎的药效物质及作用机制。方法 通过中医传承辅助系统（V3.0）对中华中医药学会遴选出的45首中药方剂进行频次、关联规则分析。利用中药系统药理学数据库与分析平台（TCMSP）结合现代生物学手段，通过对炎症水平的抑制作用以及对细胞骨架损伤修复作用的评价，筛选出活性成分，整合Genecards等数据库获取共有靶点，构建蛋白质-蛋白质相互作用（PPI）网络并进行基因本体（GO）分析和京都基因和基因组百科全书（KEGG）通路富集分析。最后经由分子对接验证。结果 筛选出甘草、半夏、桔梗等16味中药为复方治疗感染性肺炎的核心药物，明确木犀草素、绿原酸和甘草次酸3个关键药效物质，并确定35个治疗感染性肺炎的核心靶点。分子对接结果提示核心成分与核心靶点结合稳定。结论 木犀草素、绿原酸和甘草次酸可通过Ras蛋白（Ras）磷脂酰肌醇3激酶（PI3K-Akt）、血管内皮生长因子（VEGF）信号通路调节肺部炎症、改善气道功能，起到治疗感染性肺炎的作用。

Objective To systematically investigate the pharmacodynamic substances and mechanisms of traditional Chinese medicine (TCM) in treating infectious pneumonia through data mining and network pharmacology approaches. Methods Forty-five formulas from the China Association of Chinese Medicine were analyzed using the TCM Inheritance Support System (V3.0) for frequency statistics and association rule mining. Active components were screened via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) combined with modern biological evaluations, including anti-inflammatory activity assessment and cytoskeletal damage repair efficacy. Shared targets were identified by integrating Genecards and other databases, followed by protein-protein interaction (PPI) network construction, Gene Ontology (GO) functional annotation, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was performed for validation. Results Sixteen core herbs (e.g., Glycyrrhizae Radix et Rhizoma, Pinelliae Rhizoma, and Platycodonis Radix) and three key pharmacodynamic compounds (luteolin, chlorogenic acid, and glycyrrhetinic acid) were identified. Thirty-five core therapeutic targets for infectious pneumonia were determined, with molecular docking confirming stable binding affinities between core compounds and targets. Conclusion Luteolin, chlorogenic acid, and glycyrrhetinic acid exert therapeutic effects on infectious pneumonia by modulating pulmonary inflammation and improving airway function through the Ras, PI3K-Akt, and VEGF signaling pathways.

R974

国家自然科学基金青年项目（82404968）；天津市教委科研计划项目（2021KJ129）