Network pharmacology research and experimental verification of Huangqi (Astragalus Radix) and Jinyingzi (Rosae Laevigatae Fructus) in treating benign prostatic hyperplasia

Q3 Medicine
Huan Zhou , Meng Yang , Yipin Yu , Hui Liu , Zhixing Qing , Qihua Chen
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引用次数: 0

Abstract

Objective

This study aimed to analyze the mechanism of action of Huangqi (Astragalus Radix, HQ) - Jinyingzi (Rosae Laevigatae Fructus, JYZ) in the treatment of benign prostatic hyperplasia (BPH) based on network pharmacology and to verify the prediction through animal experimentation.

Methods

Based on the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN-TCM) databases, and literature, the active components and related target genes of HQ and JYZ were screened. The BPH target genes were screened based on the DisGeNET and GeneGards databases, and Excel was used to merge and remove duplicates. The Perl language was used to obtain drug-BPH target genes by intersecting shared target genes. A drug-component-target gene network diagram was constructed using Cytoscape software. The drug-BPH intersection target genes were inputted into the STRING database, and the key target genes were selected according to the degree algorithm. The output formed the basis for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to determine the potential mechanism of HQ and JYZ in BPH treatment. High, medium, and low doses of HQ and JYZ extract were used to intervene in BPH rats, and then the prostate volume, wet weight, and prostate index of the BPH rats were determined. Changes in prostate histopathology and microvessel density (MVD) were evaluated using immunohistochemistry, and the optimal HQ and JYZ extract dose was confirmed. Finally, the optimal dose was used to intervene in a BPH rat model, and AKT1 and VEGF expressions were examined by immunohistochemistry.

Results

Based on network pharmacology, 33 active components and 772 target genes were identified from HQ and JYZ, along with 817 BPH target genes and 112 drug-BPH common target genes. Among them were 10 key target genes, including AKT1, JUN, MAPK1, IL-6, TNF, ESR1, and VEGFA. KEGG enrichment analysis revealed 135 signaling pathways, including PI3K/AKT, IL-17, TNF, p53, MAPK, VEGF, JAK-STAT, and NF-κB pathways. The animal experiment showed that HQ and JYZ significantly improved prostate volume, wet weight, prostate index, and prostate histopathology of BPH rats, reducing MVD. In addition, HQ and JYZ inhibited the expression of AKT1 and VEGF in the prostate tissue of rats, promoted epithelial cell apoptosis, and inhibited angiogenesis, consistent with the prediction.

Conclusion

The combination of HQ and JYZ is effective for BPH therapy through multi-compound and multi-target collaboration. Its possible mechanism in treating BPH includes regulation of AKT1, VEGF protein, PI3K/Akt, and VEGF signaling pathways related to apoptosis, angiogenesis, and inflammation, with potential for clinical use and research.

黄芪、金莹子治疗良性前列腺增生的网络药理学研究及实验验证
目的基于网络药理学分析黄芪-金莹子治疗良性前列腺增生(BPH)的作用机制,并通过动物实验验证其预测。方法基于中药系统药理学数据库与分析平台(TCMSP)、中药分子机制生物信息学分析工具(BATMAN-TCM)数据库及文献资料,筛选黄芪芪和JYZ的有效成分及相关靶基因。根据DisGeNET和GeneGards数据库筛选BPH靶基因,并使用Excel进行合并和去除重复基因。利用Perl语言通过交叉共享靶基因获得药物bph靶基因。利用Cytoscape软件构建药物组分-靶基因网络图。将药物- bph交叉靶基因输入STRING数据库,根据度算法选择关键靶基因。该结果为基因本体(GO)和京都基因与基因组百科全书(KEGG)途径富集分析奠定了基础,以确定HQ和JYZ治疗BPH的潜在机制。采用高、中、低剂量黄芪和JYZ提取物对BPH大鼠进行干预,测定BPH大鼠前列腺体积、湿重和前列腺指数。采用免疫组化方法观察大鼠前列腺组织病理学和微血管密度的变化,确定黄芪和JYZ提取物的最佳剂量。最后,采用最佳剂量干预BPH大鼠模型,免疫组化检测AKT1和VEGF的表达。结果基于网络药理学方法,从黄芪和江蓠中共鉴定出有效成分33个,靶基因772个,BPH靶基因817个,药物-BPH共同靶基因112个。其中有10个关键靶基因,包括AKT1、JUN、MAPK1、IL-6、TNF、ESR1和VEGFA。KEGG富集分析发现135条信号通路,包括PI3K/AKT、IL-17、TNF、p53、MAPK、VEGF、JAK-STAT和NF-κB通路。动物实验结果显示,黄芪芪和JYZ均能显著改善BPH大鼠前列腺体积、湿重、前列腺指数和前列腺组织病理学,降低MVD。此外,黄芪和JYZ抑制大鼠前列腺组织中AKT1和VEGF的表达,促进上皮细胞凋亡,抑制血管生成,与预测一致。结论黄芪与JYZ联合治疗BPH是一种多化合物、多靶点协同治疗的有效方法。其治疗BPH的可能机制包括调控AKT1、VEGF蛋白、PI3K/Akt以及与细胞凋亡、血管生成和炎症相关的VEGF信号通路,具有临床应用和研究潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Digital Chinese Medicine
Digital Chinese Medicine Medicine-Complementary and Alternative Medicine
CiteScore
1.80
自引率
0.00%
发文量
126
审稿时长
63 days
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