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运用网络药理学与分子对接技术阐明解毒清肝方治疗非小细胞肺癌的分子生物学机制

Integrating network pharmacology with molecular docking for elucidation of molecular biological mechanisms of Jiedu Qingjin formula for non-small cell lung cancer.

作者信息

Xu Bowen, Dan Wenchao, Wu Jingyuan, Wang Xinmiao, Qin Xiaoyan, Han Yingying, Song Xiaotong, Zhang Xiaoxiao, Li Jie

机构信息

Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.

Beijing University of Chinese Medicine, Beijing, China.

出版信息

J Biomol Struct Dyn. 2024;42(21):11322-11341. doi: 10.1080/07391102.2023.2262587. Epub 2023 Sep 28.

Abstract

Traditional Chinese medicine is an important part of complementary alternative medicine. Jiedu Qingjin formula (JDQJF) is an effective national invention patent for the treatment of non-small cell lung cancer (NSCLC). We investigated the molecular biological mechanisms based on network pharmacology, molecular docking, and molecular dynamics simulations. Compounds of JDQJF were screened through the TCMSP, ETCM, and literature. Targets were searched by DrugBank and predicted by SwissTargetPrediction. GEO database was applied for screening differentially expressed genes between cancerous tissues and healthy tissues of NSCLC. Subsequently, the protein-protein interaction between JDQJF and NSCLC were obtained by Cytoscape. Visual analyses were carried out to extract candidate genes, then subjected to Metascape for enrichment analyses. Finally, molecular docking was performed by AutoDock, and the best complexes were subjected to molecular dynamics simulation and binding energy calculations by MMPBSA. A total of 273 compounds, 390 targets, 3146 GO terms, and 174 KEGG pathways were obtained. Five potential compounds (quercetin, adenosine, apigenin, heptadecanoic acid, and luteolin) were notably modulated by key targets and . Enrichment results included cell cycle process, growth transduction factor, immune response-activating transduction, and involved PI3K/AKT, MAPK, NF-κB and VEGF pathway. -quercetin showed the highest binding affinity (-9.1 kcal/mol), revealed stable interactions during the simulation, and the highest estimated relative binding energy of the -Heptadecanoic was -184.277 kcal/mol. This study suggested that EMT-related, inflammation-related, immune-related, and angiogenesis-related pathways may be associated with JDQJF, and involved in the advancement of NSCLC, which points out the research direction for subsequent utility mechanism validation.Communicated by Ramaswamy H. Sarma.

摘要

传统医学是补充替代医学的重要组成部分。解毒清肝方(JDQJF)是一种治疗非小细胞肺癌(NSCLC)的有效国家发明专利。我们基于网络药理学、分子对接和分子动力学模拟研究了其分子生物学机制。通过 TCMSP、ETCM 和文献筛选 JDQJF 的化合物。通过 DrugBank 搜索靶点,并通过 SwissTargetPrediction 预测。通过 GEO 数据库筛选 NSCLC 癌组织与正常组织之间的差异表达基因。随后,通过 Cytoscape 获得 JDQJF 与 NSCLC 的蛋白质-蛋白质相互作用。通过可视化分析提取候选基因,然后将其导入 Metascape 进行富集分析。最后,通过 AutoDock 进行分子对接,并通过 MMPBSA 计算最佳复合物的结合能。共获得 273 种化合物、390 个靶点、3146 个 GO 术语和 174 个 KEGG 通路。五个潜在化合物(槲皮素、腺嘌呤、芹菜素、十七烷酸和木樨草素)被关键靶点和显著调节。富集结果包括细胞周期过程、生长转导因子、免疫反应激活转导,涉及 PI3K/AKT、MAPK、NF-κB 和 VEGF 通路。-槲皮素表现出最高的结合亲和力(-9.1 kcal/mol),在模拟过程中表现出稳定的相互作用,而 -十七烷酸的最高估计相对结合能为-184.277 kcal/mol。本研究表明 EMT 相关、炎症相关、免疫相关和血管生成相关通路可能与 JDQJF 相关,并参与 NSCLC 的进展,为后续的应用机制验证指出了研究方向。

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