| 基于网络药理学和GEO数据集的翻白草治疗2型糖尿病分子机制探讨 |
| 投稿时间：2023-04-14 点此下载全文
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| 引用本文：何旭,马鑫彦,赵薇,张印江,鲁碧楠,庞宗然.基于网络药理学和GEO数据集的翻白草治疗2型糖尿病分子机制探讨[J].中国现代中药,2023,25(9):1949-1956 |
| DOI：10.13313/j.issn.1673-4890.20230414006 |
| 摘要点击次数: 461 |
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| 作者中文名 | 作者英文名 | 单位中文名 | 单位英文名 | E-Mail |
| 何旭 |
HE Xu |
中央民族大学 药学院，北京 100081
民族医药教育部重点实验室，北京 100081
大理白族自治州人民医院 药剂科，云南 大理 671000 |
School of Pharmacy, Minzu University of China, Beijing 100081, China
Key Laboratory of Ethnomedicine, Ministry of Education, Beijing 100081, China
Pharmacy Department, People's Hospital of Dali Bai Autonomous Prefecture, Dali 671000, China |
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| 马鑫彦 |
MA Xin-yan |
中央民族大学 药学院，北京 100081
民族医药教育部重点实验室，北京 100081 |
School of Pharmacy, Minzu University of China, Beijing 100081, China
Key Laboratory of Ethnomedicine, Ministry of Education, Beijing 100081, China |
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| 赵薇 |
ZHAO Wei |
中央民族大学 药学院，北京 100081
民族医药教育部重点实验室，北京 100081 |
School of Pharmacy, Minzu University of China, Beijing 100081, China
Key Laboratory of Ethnomedicine, Ministry of Education, Beijing 100081, China |
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| 张印江 |
ZHANG Yin-jiang |
中央民族大学 药学院，北京 100081
民族医药教育部重点实验室，北京 100081 |
School of Pharmacy, Minzu University of China, Beijing 100081, China
Key Laboratory of Ethnomedicine, Ministry of Education, Beijing 100081, China |
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| 鲁碧楠* |
LU Bi-nan |
中央民族大学 药学院，北京 100081
民族医药教育部重点实验室，北京 100081 |
School of Pharmacy, Minzu University of China, Beijing 100081, China
Key Laboratory of Ethnomedicine, Ministry of Education, Beijing 100081, China |
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| 庞宗然 |
PANG Zong-ran |
中央民族大学 药学院，北京 100081
民族医药教育部重点实验室，北京 100081 |
School of Pharmacy, Minzu University of China, Beijing 100081, China
Key Laboratory of Ethnomedicine, Ministry of Education, Beijing 100081, China |
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| 中文摘要:目的 网络药理学结合GEO数据集探讨翻白草治疗2型糖尿病的分子机制。方法 通过中药系统药理学数据库与分析平台（TCMSP）下载翻白草化学成分信息，经SwissADME对各成分进行筛选和SwissTargetPrediction预测靶点后，得到药物作用靶点。采用R软件下载GEO数据中GSE系列，提取表达矩阵，对原始数据进行归一化处理后提取临床信息，采用limma程序包进行2型糖尿病差异基因分析。通过微生信在线平台获取药物作用靶点和疾病差异基因交集，即为翻白草治疗2型糖尿病的潜在作用靶点，对潜在作用靶点进行生物信息学分析，采用分子对接方法对分析结果进行验证。结果 筛选得到翻白草中20个化学成分，经SwissTargetPrediction预测后，得到374个药物作用靶点，R软件分析获得2型糖尿病差异基因658个，取交集后得到17个潜在作用靶点。经过基因本体（GO）富集分析和京都基因与基因组百科全书（KEGG）通路分析可知，翻白草有效成分有原儿茶酸、咖啡酸、山柰酚、3,4,5-三羟基苯甲酸、罗索酸，通过作用蛋白激酶C-θ（PKC-θ）、核转录因子-κB p65亚单位（RELA）、核糖体蛋白S6激酶α3（RPS6KA3）、信号传导和转录激活因子3（STAT3）、乳酸脱氢酶B（LDHB）和6-磷酸果糖激酶-2/果糖-2,6-二磷酸酶同工酶3（PFKFB3）靶点，参与胰岛素抵抗通路（P<0.01）、低氧诱导因子-1（HIF-1）信号通路（P<0.01）和脂肪细胞因子信号通路（P<0.01）来发挥治疗2型糖尿病作用。分子对接结果显示，PKC-θ、RELA、STAT3与咖啡酸，RPS6KA3与罗索酸，LDHB与3,4,5-三羟基苯甲酸，PFKFB3与山柰酚之间均具有较好的对接活性。结论 通过网络药理学结合GEO数据集，初步预测了翻白草治疗2型糖尿病的潜在靶点和可能的作用机制，为翻白草治疗2型糖尿病的进一步研究提供理论依据。 |
| 中文关键词:翻白草 2型糖尿病 GEO数据集 网络药理学 分子对接 |
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| Mechanism of Potentillae Discoloris Herba in Treating Type 2 Diabetes Mellitus: Based on Network Pharmacology Combined with GEO Datasets |
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| Abstract:Objective To explore the molecular mechanism of Potentillae Discoloris Herba in treating type 2 diabetes mellitus by combining network pharmacology with Gene Expression Omnibus (GEO) datasets.Methods The chemical constituents of Potentillae Discoloris Herba were downloaded from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). After component screening by SwissADME, SwissTargetPrediction was employed to predict the targets. R software was used to download the series GSE from GEO and extract the expression matrix. The clinical information was extracted after normalization of the raw data, and the limma package was used to analyze the differential genes of type 2 diabetes mellitus. Weishengxin online platform was used to identify the common targets shared by Potentillae Discoloris Herba and the disease, i.e., the potential targets of Potentillae Discoloris Herba in the treatment of type 2 diabetes mellitus. The bioinformatics analysis was then performed for the potential targets. Finally, the results were verified by molecular docking.Results A total of 20 chemical constituents and 374 targets of Potentillae Discoloris Herba and 658 differential genes of type 2 diabetes mellitus were obtained. Seventeen common targets shared by the herbal medicine and the disease were obtained as the potential targets. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the active components (protocatechuic acid, caffeic acid, kaempferol, 3,4,5-trihydroxybenzoic acid, and rosolic acid) of Potentillae Discoloris Herba acted on protein kinase C (PKC)-θ, nuclear factor-kappa B p65 (RELA), ribosomal protein S6 kinase alpha-3 (RRPS6KA3), signal transducer and activator of transcription 3 (STAT3), lactate dehydrogenase (LDHB), and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) to participate in the insulin resistance pathway (P<0.01), hypoxia-inducible factor-1 (HIF-1) signaling pathway (P<0.01), and adipocytokine signaling pathway (P<0.01), thus treating type 2 diabetes mellitus. The results of molecular docking showed strong binding of PKC-θ, RELA, and STAT3 with caffeic acid, of RPS6KA3 with rosolic acid, of LDHB with 3,4,5-trihydroxybenzoic acid, and of PFKFB3 with kaempferol.Conclusion By combining network pharmacology with GEO datasets, this study predicted the potential targets and possible mechanism of Potentillae Discoloris Herba in the treatment of type 2 diabetes mellitus. The results provide a theoretical basis for further research on the treatment of type 2 diabetes mellitus. |
| keywords:Potentillae Discoloris Herba type 2 diabetes mellitus GEO dataset network pharmacology molecular docking |
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