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网络药理学和分子对接揭示百合固金汤治疗非小细胞肺癌的作用机制。

The mechanism of Bai He Gu Jin Tang against non-small cell lung cancer revealed by network pharmacology and molecular docking.

机构信息

Department of Computer Science and Technology, School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.

Hangzhou Cancer Institute, Hangzhou Cancer Hospital, Hangzhou, China.

出版信息

Medicine (Baltimore). 2022 Dec 30;101(52):e32555. doi: 10.1097/MD.0000000000032555.

DOI:10.1097/MD.0000000000032555
PMID:36596057
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9803515/
Abstract

BACKGROUND

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related burden and deaths, thus effective treatment strategies with lower side effects for NSCLC are urgently needed. To systematically analyze the mechanism of Bai He Gu Jin Tang (BHGJT) against NSCLC by network pharmacology and molecular docking.

METHODS

The active compounds of BHGJT were obtained by searching the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine and Encyclopaedia of Traditional Chinese Medicine. Search tool for interactions of chemicals was used for acquiring the targets of BHGJT. The component-target network was mapped by Cytoscape. NSCLC-related genes were obtained by searching Genecards, DrugBank and Therapeutic Target Database. The protein-protein interaction network of intersection targets was established based on Search Tool for Recurring Instances of Neighboring Genes (STRING), and further, the therapeutic core targets were selected by topological parameters. The hub targets were transmitted to Database for Annotation, Visualization and Integrated Discovery for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Finally, AutoDock Vina and MglTools were employed for molecular docking validation.

RESULTS

Two hundred fifty-six compounds and 237 putative targets of BHGJT-related active compounds as well as 1721potential targets of NSCLC were retrieved. Network analysis showed that 8 active compounds of BHGJT including kaempferol, quercetin, luteolin, isorhamnetin, beta-sitosterol, stigmasterol, mairin and liquiritigenin as well as 15 hub targets such as AKR1B10 and AKR1C2 contribute to the treatment of BHGJT against NSCLC. GO functional enrichment analysis shows that BHGJT could regulate many biological processes, such as apoptotic process. Three modules of the endocrine related pathways including the inflammation, hypoxia related pathways as well as the other cancer related pathways based on Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis might explain the biological mechanisms of BHGJT in treating BHGJT. The results of molecular docking verified that AKR1B10 and AKR1C2 had the strongest binding activity with the 8 key compounds of NSCLC.

CONCLUSION

Our study reveals the mechanism of BHGJT in treating NSCLC involving multiple components, multiple targets and multiple pathways. The present study laid an initial foundation for the subsequent research and clinical application of BHGJT and its active compounds against NSCLC.

摘要

背景

非小细胞肺癌(NSCLC)是癌症相关负担和死亡的主要原因,因此迫切需要有效的治疗策略,且副作用较低。本研究旨在通过网络药理学和分子对接系统分析百合固金汤(BHGJT)治疗 NSCLC 的作用机制。

方法

通过中药分子机制生物信息学分析工具和《中药大辞典》搜索 BHGJT 的活性化合物。利用搜索化学物质相互作用工具获取 BHGJT 的靶点。通过 Cytoscape 映射成分-靶点网络。从 Genecards、DrugBank 和 Therapeutic Target Database 中获取 NSCLC 相关基因。基于 Search Tool for Recurring Instances of Neighboring Genes(STRING)建立交集靶点的蛋白质-蛋白质相互作用网络,进一步根据拓扑参数选择治疗核心靶点。将枢纽靶点传输到基因本体(GO)和京都基因与基因组百科全书(KEGG)分析数据库进行注释。最后,使用 AutoDock Vina 和 MglTools 进行分子对接验证。

结果

共检索到 BHGJT 相关活性化合物的 256 种化合物和 237 个潜在靶点,以及 NSCLC 的 1721 个潜在靶点。网络分析表明,BHGJT 的 8 种活性化合物(包括山奈酚、槲皮素、木樨草素、异鼠李素、β-谷甾醇、豆甾醇、马里因和甘草素)和 15 个枢纽靶点(如 AKR1B10 和 AKR1C2)可能有助于 BHGJT 治疗 NSCLC。GO 功能富集分析表明,BHGJT 可调节多种生物过程,如凋亡过程。KEGG 通路富集分析表明,有三个模块的内分泌相关通路(包括炎症、缺氧相关通路以及其他癌症相关通路)可能解释了 BHGJT 治疗 NSCLC 的生物学机制。分子对接结果验证了 AKR1B10 和 AKR1C2 与 NSCLC 的 8 种关键化合物具有最强的结合活性。

结论

本研究揭示了 BHGJT 治疗 NSCLC 的作用机制涉及多个成分、多个靶点和多个通路。本研究为 BHGJT 及其活性化合物治疗 NSCLC 的后续研究和临床应用奠定了初步基础。

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