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网络药理学和分子对接技术在探讨黄芪-全蝎治疗前列腺癌的潜在机制中的应用。

Application of network pharmacology and molecular docking to elucidate the potential mechanism of Astragalus-Scorpion against prostate cancer.

机构信息

Shenzhen Bao'an Traditional Chinese Medicine Hospital Group, Guangzhou University of Chinese Medicine, Shenzhen, China.

School of Graduate, Guangzhou University of Chinese Medicine, Guangzhou, China.

出版信息

Andrologia. 2021 Oct;53(9):e14165. doi: 10.1111/and.14165. Epub 2021 Jun 29.

DOI:10.1111/and.14165
PMID:34185887
Abstract

The present study aimed to investigate the molecular mechanism of the Astragalus-Scorpion drug pair in the treatment of prostate cancer (PCa). We employed network pharmacology and molecular docking technology to retrieving the active ingredients and corresponding targets of Astragalus-Scorpion by using TCMSP, BATMAN-TCM, TCMID and Swiss Target Prediction Databases. The targets related to PCa were retrieved through GeneCards. Cytoscape software was used to construct the 'active ingredient-target disease' network, and GO and KEGG enrichment analyses were performed on the common targets. Autodock software was used for molecular docking verification. In total, 26 active ingredients, 340 potential targets related to active ingredients and 122 common targets were screened from Astragalus-Scorpion drug pair. The core targets of the protein-protein interaction (PPI) network were JUN, AKT1, IL6, MAPK1 and RELA, whereas the core active ingredients were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin. Nearly 762 GO entries and 154 pathways were obtained by using the pathway enrichment analysis. Molecular docking results revealed that quercetin and kaempferol bind to AKT1 and formononetin binds to RELA, all of which were found to be stable bounds.

摘要

本研究旨在探讨黄芪-蝎子药对治疗前列腺癌(PCa)的分子机制。我们采用网络药理学和分子对接技术,通过 TCMSP、BATMAN-TCM、TCMID 和 Swiss Target Prediction 数据库检索黄芪-蝎子的活性成分和相应的靶点。通过 GeneCards 检索与 PCa 相关的靶点。使用 Cytoscape 软件构建“活性成分-靶标-疾病”网络,并对共同靶标进行 GO 和 KEGG 富集分析。使用 Autodock 软件进行分子对接验证。从黄芪-蝎子药对中筛选出 26 种活性成分、340 种潜在的活性成分相关靶点和 122 个共同靶点。蛋白质-蛋白质相互作用(PPI)网络的核心靶标为 JUN、AKT1、IL6、MAPK1 和 RELA,核心活性成分为槲皮素、山奈酚、芒柄花素、7-O-甲基异牡荆素和毛蕊异黄酮。通过通路富集分析获得了近 762 个 GO 条目和 154 条通路。分子对接结果表明,槲皮素和山奈酚与 AKT1 结合,芒柄花素与 RELA 结合,均为稳定结合。

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