| 引用本文: | 周森,李侃,安海倩,刘明龙,王喆,刘天喜.基于网络药理学的“黄芪-当归”药对抗肾纤维化的作用机制研究[J].中国现代应用药学,2023,40(2):179-190. |
| ZHOU Sen,LI Kan,AN Haiqian,LIU Minglong,WANG Zhe,LIU Tianxi.Study on the Anti-renal Fibrosis Mechanism of Astragali Radix and Angelicae Sinensis Radix Based on Network Pharmacology[J].Chin J Mod Appl Pharm(中国现代应用药学),2023,40(2):179-190. |
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| 基于网络药理学的“黄芪-当归”药对抗肾纤维化的作用机制研究 |
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周森1,2, 李侃1,2, 安海倩1,2, 刘明龙1,2, 王喆1,2, 刘天喜1,2
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1.兰州大学第一医院肾病科, 兰州 730000;2.兰州大学第一临床医学院, 兰州 730000
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| 摘要: |
| 目的 基于网络药理学的方法探讨“黄芪-当归”药对抗肾纤维化(renal fibrosis，RF)的作用机制。方法 基于中药系统药理学技术平台(TCMSP)检索并筛选“黄芪-当归”药对的潜在活性成分，结合SwissTargetPrediction数据库，获得潜在活性成分所对应的作用靶点，并与通过GeneCards和OMIM数据库检索获得的RF相关靶点进行映射，获得“黄芪-当归”药对抗RF的潜在作用靶点，对得到的靶点通过STRING数据库构建蛋白-蛋白相互作用(protein-protein interaction，PPI)网络，并筛选核心靶点和Hub靶点；利用DAVID数据库对核心靶点进行基因本体论和KEGG通路富集分析，通过构建“药对-活性成分-核心靶点-通路”网络，并利用分子对接技术对关键靶点和化合物的相互作用进行验证，系统阐释“黄芪-当归”药对抗RF的作用机制。结果 基于TCMSP和SwissTargetPrediction数据库，共获得“黄芪-当归”药对60个潜在活性成分和763个作用靶点，通过与RF相关靶点进行映射，获得352个交集靶点。通过构建PPI网络并进一步筛选，获得“黄芪-当归”药对抗RF的30个核心靶点和9个Hub靶点，包括MMP9、IL6、EGFR、CASP3、MMP2等。核心靶点KEGG分析结果表明“黄芪-当归”药对可能通过TNF、ErbB、FoxO、MAPK、PI3K-Akt、HIF-1等与炎症、免疫相关的信号通路而发挥抗RF的作用。将关键活性成分和靶点进行分子对接，提示活性成分与靶点间具有较好的结合活性。结论 本研究初步明确了“黄芪-当归”药对多成分、多靶点、多通路抗RF的复杂过程，为系统研究其抗RF的药效物质基础及作用机制奠定基础。 |
| 关键词: 黄芪 当归 肾纤维化 作用机制 网络药理学 |
| DOI：10.13748/j.cnki.issn1007-7693.2023.02.005 |
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| 基金项目:甘肃省青年科技基金计划(20JR5RA350) |
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| Study on the Anti-renal Fibrosis Mechanism of Astragali Radix and Angelicae Sinensis Radix Based on Network Pharmacology |
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ZHOU Sen1,2, LI Kan1,2, AN Haiqian1,2, LIU Minglong1,2, WANG Zhe1,2, LIU Tianxi1,2
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1.Department of Nephrology, First Hospital of Lanzhou University, Lanzhou 730000, China;2.First Clinical Medical College of Lanzhou University, Lanzhou 730000, China
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| Abstract: |
| OBJECTIVE To explore the action mechanism of Astragali Radix and Angelicae Sinensis Radix in the treatment of renal fibrosis(RF) by means of network pharmacology. METHODS Based on TCMSP, the potential active components of Astragali Radix and Angelicae Sinensis Radix were searched and screened. Combined with SwissTargetPrediction database, the action targets were obtained, and mapped with the RF related targets retrieved from GeneCards and OMIM databases to obtain the potential action targets. The protein-protein interaction(PPI) network was constructed through STRING database, and the core targets and Hub targets were screened; DAVID database, Gene Ontology and KEGG pathway enrichment analysis were carried out on the core targets. By constructing the “drug pair-active ingredient-core target-pathway” network, together with molecular docking technology, the interaction between key targets and compounds were verified, and the mechanism of Astragali Radix and Angelicae Sinensis Radix against RF was further systematically explained. RESULTS Based on TCMSP and SwissTargetPrediction databases, a total of 60 potential active components and 763 action targets of Astragali Radix and Angelicae Sinensis Radix were obtained. There were 352 intersection targets obtained by mapping with RF related targets. Through the construction of PPI network and further screening, 30 core targets and 9 Hub targets of Astragali Radix and Angelicae Sinensis Radix against RF were obtained, including MMP9, IL6, EGFR, CASP3, MMP2 and so on. The results of KEGG analysis of the core target showed that Astragali Radix and Angelicae Sinensis Radix might play an anti-RF role through TNF, ErbB, FoxO, MAPK, PI3K-Akt, HIF-1 and other signal pathways related to inflammation and immunity. The molecular docking of the main active ingredients and the targets revealed they were highly active to bind. CONCLUSION The result of the study preliminarily verified the mechanisms of Astragali Radix and Angelicae Sinensis Radix in treatment of RF through multi-ingredients, multi-target and multi-pathway interactions, and lay foundation for further studies on the material basis and mechanism of action. |
| Key words: Astragali Radix Angelicae Sinensis Radix renal fibrosis action mechanism network pharmacology |
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