| 引用本文: | 王洋洋,陈楚,马芳,李俏飞,闻新丽.网络药理学联合分子对接技术探究参赭培气汤治疗胃食管反流病的作用机制[J].中国现代应用药学,2022,39(23):3062-3069. |
| WANGYangyang,CHEN Chu,MA Fang,LI Qiaofei,WEN Xinli.Study on the Mechanism of Shenzhe Peiqi Decoction in the Treatment of Gastroesophageal Reflux Disease by Network Pharmacology Combined with Molecular Docking Technology[J].Chin J Mod Appl Pharm(中国现代应用药学),2022,39(23):3062-3069. |
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| 摘要: |
| 目的 利用网络药理学联合分子对接技术探究参赭培气汤治疗胃食管反流病的作用机制。方法 通过中药系统药理学数据库和分析平台筛选出参赭培气汤的有效活性成分及对应的靶蛋白，通过Uniprot数据库将其转化成相应的基因名称；利用GeneGards数据库和Online Mendelian Inheritance in Man(OMIM)筛选胃食管反流病的靶基因；通过Venny在线平台获取相关交集基因，利用Cytoscape 3.9.0绘制“参赭培气汤-成分-靶点”可视化网络；结合STRING数据库和Cytoscape 3.9.0软件绘制蛋白互作网络图；利用metascape数据库进行靶点基因GO和KEGG富集分析；通过AutoDock软件进行分子对接，验证有效成分与靶蛋白间的结合活性。结果 总共有93个参赭培气汤的有效成分，253个靶基因，4256个疾病相关靶基因，获得141个中药-疾病共同靶基因。通过GO功能分析结果得出4872个生物学过程、735个分子功能、465个细胞组成，KEGG通路分析发现247条信号通路。结论 本研究预测了参赭培气汤通过ACTB、AKT1、IL-6、TP53、CASP3等多靶点及癌症信号通路治疗胃食管反流病的作用机制，为深入研究参赭培气汤治疗胃食管反流病提供理论依据。 |
| 关键词: 参赭培气汤 胃食管反流病 网络药理学 分子模拟对接 作用机制 |
| DOI：10.13748/j.cnki.issn1007-7693.2022.23.003 |
| 分类号:R966 |
| 基金项目:国家重点研发计划“中医药现代化研究”专项(2018YFC1705402)；陕西省中医医院博士启动基金(2021-32) |
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| Study on the Mechanism of Shenzhe Peiqi Decoction in the Treatment of Gastroesophageal Reflux Disease by Network Pharmacology Combined with Molecular Docking Technology |
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WANGYangyang1, CHEN Chu2, MA Fang1, LI Qiaofei1, WEN Xinli2
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1.Shanxi University of Chinese Medicine, Xianyang 712046, China;2.Shanxi Provincial Hospital of Chinese Medicine, Xi'an 710000, China
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| Abstract: |
| OBJECTIVE To investigate the mechanism of Shenzhe Peiqi decoction in the treatment of gastroesophageal reflux disease by network pharmacology combined with molecular docking technology. METHODS The active ingredients and corresponding target proteins of Shenzhe Peiqi decoction were selected through the Traditional Chinese Medicine System Pharmacology database and analysis platform, and converted into corresponding gene names through the Uniprot database. Using the GeneGards database and Online Mendelian Inheritance in Man(OMIM) screened the target genes of gastroesophageal reflux disease. Obtained relevant intersection genes through the Venny online platform, and used Cytoscape 3.9.0 to draw the “Shenzhe Peiqi decoction-ingredients-targets” visualization network. The STRING database and Cytoscape 3.9.0 software were used to draw the protein-protein interaction network diagram. The metascape database were used for the enrichment analysis of target genes GO and KEGG. Molecular docking was performed by AutoDock software to verify the binding activity between the active ingredient and the target protein. RESULTS A total of 93 active ingredients of Shenzhe Peiqi decoction, 253 target genes, 4 256 disease-related target genes, and 141 common target genes of traditional Chinese medicine and diseases were obtained. Through GO function analysis, 4 872 biological processes, 735 molecular functions, and 465 cellular components were obtained, and KEGG pathway analysis found 247 signaling pathways. CONCLUSION This study predicts the mechanism of Shenzhe Peiqi decoction in the treatment of gastroesophageal reflux disease through multiple targets such as ACTB, AKT1, IL-6, TP53, CASP3 and pathway in cancer, in order to provide a theoretical basis for further study of Shenzhe Peiqi decoction in the treatment of gastroesophageal reflux disease. |
| Key words: Shenzhe Peiqi decoction gastroesophageal reflux disease network pharmacology molecular simulation docking mechanism |
