Background: Rheum palmatum L. (RpL) is a traditional Chinese medicine commonly used clinically. However, there was no systematic research to elucidate the mechanisms of RpL acting on COPD.

Objective: To explore the potential mechanisms against COPD based on network pharmacology. Methods: The active compounds of RpL were retrieved from TCMSP database, and their corresponding targets were obtained through TCMSP and STITCH databases. COPD-related targets were identified from the TTD, GeneCards and MalaCards database. Drug-disease genes were obtained through intersection analysis, and the correlation between these genes and COPD was analyzed. After that, a protein-protein interaction network was constructed and enrichment analysis was performed. Then, key targets were obtained according to the network topology attributes analysis. Finally, the Auto dock vina 1.1.2 was used for molecular docking to verify the binding ability between the active compounds and key targets.

Results: There were 8 active compounds and 90 corresponding targets were identified in RpL. A total of 4502 COPD-related targets were obtained from databases. After cross-analysis, 81 drug-disease targets were obtained. Drug-disease targets mainly regulated apoptosis and inflammatory responses and participated in related signal pathways. Besides, 28 key genes were obtained from the network topology analysis. TP53, TNF, NFKB1, VEGFA, MMP9, and MMP1 were selected to dock with the compounds. The results of molecular docking showed that the above targets have different affinities with the 8 active compounds of RpL.

中文翻译：

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掌上大黄中化合物抗慢性阻塞性肺疾病的潜在机制探索：网络药理学研究

背景：掌上大黄（RpL）是一种临床常用的中药。然而，没有系统的研究来阐明 RpL 对 COPD 的作用机制。

目的：基于网络药理学探讨抗COPD的潜在机制。方法：从TCMSP数据库中检索RpL的活性化合物，通过TCMSP和STITCH数据库获取其对应的靶标。COPD 相关目标是从 TTD、GeneCards 和 MalaCards 数据库中确定的。通过交叉分析获得药物-疾病基因，并分析这些基因与COPD的相关性。之后，构建蛋白质-蛋白质相互作用网络并进行富集分析。然后根据网络拓扑属性分析得到关键目标。最后，使用Auto dock vina 1.1.2进行分子对接，验证活性化合物与关键靶点的结合能力。

结果：在RpL中鉴定出8个活性化合物和90个相应的靶点。从数据库中总共获得了 4502 个 COPD 相关目标。经过交叉分析，获得了81个药物-疾病靶点。药物-疾病靶点主要调节细胞凋亡和炎症反应，并参与相关信号通路。此外，从网络拓扑分析中获得了28个关键基因。选择 TP53、TNF、NFKB1、VEGFA、MMP9 和 MMP1 与化合物对接。分子对接结果表明，上述靶点与RpL的8种活性化合物具有不同的亲和力。