Biomedicine Key Laboratory of Shaanxi Province, College of Life Sciences, Northwest University, Xi'an, 710069, China.
Physical and Chemical Laboratory, Shaanxi Provincial Center for Disease Control and Prevention, Xi'an, 710054, China.
Mol Divers. 2023 Feb;27(1):81-102. doi: 10.1007/s11030-022-10415-7. Epub 2022 Mar 8.
Xuanbai Chengqi Decoction (XBCQD), a classic traditional Chinese medicine, has been widely used to treat COVID-19 in China with remarkable curative effect. However, the chemical composition and potential therapeutic mechanism is still unknown. Here, we used multiple open-source databases and literature mining to select compounds and potential targets for XBCQD. The COVID-19 related targets were collected from GeneCards and NCBI gene databases. After identifying putative targets of XBCQD for the treatment of COVID-19, PPI network was constructed by STRING database. The hub targets were extracted by Cytoscape 3.7.2 and MCODE analysis was carried out to extract modules in the PPI network. R 3.6.3 was used for GO enrichment and KEGG pathway analysis. The effective compounds were obtained via network pharmacology and bioinformatics analysis. Drug-likeness analysis and ADMET assessments were performed to select core compounds. Moreover, interactions between core compounds and hub targets were investigated through molecular docking, molecular dynamic (MD) simulations and MM-PBSA calculations. As a result, we collected 638 targets from 61 compounds of XBCQD and 845 COVID-19 related targets, of which 79 were putative targets. Based on the bioinformatics analysis, 10 core compounds and 34 hub targets of XBCQD for the treatment of COVID-19 were successfully screened. The enrichment analysis of GO and KEGG indicated that XBCQD mainly exerted therapeutic effects on COVID-19 by regulating signal pathways related to viral infection and inflammatory response. Meanwhile, the results of molecular docking showed that there was a stable binding between the core compounds and hub targets. Moreover, MD simulations and MM-PBSA analyses revealed that these compounds exhibited stable conformations and interacted well with hub targets during the simulations. In conclusion, our research comprehensively explained the multi-component, multi-target, and multi-pathway intervention mechanism of XBCQD in the treatment of COVID-19, which provided evidence and new insights for further research.
宣白承气汤(XBCQD)是一种经典的中药方剂,在中国被广泛用于治疗 COVID-19,疗效显著。然而,其化学成分和潜在的治疗机制尚不清楚。在这里,我们使用多个开源数据库和文献挖掘技术,筛选 XBCQD 的化合物和潜在靶点。COVID-19 相关靶点从 GeneCards 和 NCBI 基因数据库中收集。确定 XBCQD 治疗 COVID-19 的潜在靶点后,通过 STRING 数据库构建 PPI 网络。使用 Cytoscape 3.7.2 提取枢纽靶点,并进行 MCODE 分析以提取 PPI 网络中的模块。使用 R 3.6.3 进行 GO 富集和 KEGG 通路分析。通过网络药理学和生物信息学分析获得有效化合物。对有效化合物进行药物相似性分析和 ADMET 评估,以筛选核心化合物。此外,通过分子对接、分子动力学(MD)模拟和 MM-PBSA 计算研究核心化合物与枢纽靶点之间的相互作用。结果,我们从 XBCQD 的 61 种化合物中收集了 638 个靶点和 845 个 COVID-19 相关靶点,其中 79 个是潜在靶点。基于生物信息学分析,成功筛选出 XBCQD 治疗 COVID-19 的 10 种核心化合物和 34 个枢纽靶点。GO 和 KEGG 的富集分析表明,XBCQD 主要通过调节与病毒感染和炎症反应相关的信号通路发挥治疗 COVID-19 的作用。同时,分子对接结果表明,核心化合物与枢纽靶点之间存在稳定的结合。此外,MD 模拟和 MM-PBSA 分析表明,这些化合物在模拟过程中表现出稳定的构象,并与枢纽靶点相互作用良好。总之,本研究全面解释了 XBCQD 治疗 COVID-19 的多成分、多靶点、多途径干预机制,为进一步研究提供了证据和新的思路。