基于网络药理学和生物信息学的辛伐他汀分子生物学机制研究  

Molecular biological mechanism of simvastatin based on network pharmacology and bioinformatics

作　　者：刘慧 陆嘉骏 樊璐 雒舒雅 王天宇 肖庆桓 刘美 LIU Hui;LU Jia-jun;FAN Lu;LUO Shu-ya;WANG Tian-yu;XIAO Qing-heng;LIU Mei(Department of Ion Channel Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122,Liaoning Province,China)

机构地区：[1]中国医科大学药学院离子通道药理研究室

出　　处：《中国临床药理学杂志》2019年第14期1510-1513,共4页The Chinese Journal of Clinical Pharmacology

基　　金：国家自然科学基金资助项目(81802659);中国博士后科学基金面上基金资助项目(2018M641738)

摘　　要：目的通过生物信息学分析研究辛伐他汀作用前后的差异表达基因,找出参与辛伐他汀体内作用的关键基因,并对其所涉及的功能进行分析预测。方法从美国国立生物技术信息中心公共基因芯片数据平台下载辛伐他汀对人外周血单核细胞-巨噬细胞基因表达谱影响的mRNA基因芯片数据集GSE4883,包含辛伐他汀给药组6个样本及对照组3个样本,用R语言Limma函数包筛选差异表达的mRNA,并用Benjamini&Hochberg错误发现率对原始P值进行多重矫正,并进一步用DAVID数据库对靶基因进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)信号通路富集分析,之后用STRING数据库构建蛋白质相互作用网络,同时用Cytoscape对模块中的基因共表达关系进行可视化,筛选关键基因。结果共筛选出214个辛伐他汀作用前后差异表达的基因。GO分析显示,差异表达基因生物学功能主要涉及免疫反应、细胞对白细胞介素-1、干扰素的反应和单核细胞趋化性。KEGG分析显示,差异表达基因主要和细胞因子与细胞因子受体相互作用、类风湿关节炎和趋化因子信号通路等有关。蛋白质相互作用网络筛选出KIF11、CDK1、NDC80、RRM2、NCAPG、NUF2、MAD2L1、KIF15、TOP2A和HELLS 10个关键基因。结论生物信息学能有效筛选和分析辛伐他汀作用后的相关差异表达基因,通过对辛伐他汀作用后的表达谱进行分析,为进一步探讨辛伐他汀作用的分子机制及靶点提供思路,同时为他汀类药物的潜在应用探索提供理论依据。Objective To analyze the molecular biological mechanism of simvastatin in the treatment of human based on network pharmacology and bioinformatics methods. Methods The human mRNA gene chip dataset GSE4883 ( 6 samples of simvastatin group and 3 samples of control group) was downloaded from common gene chip data platform in National Center for Biotechnology Information. Differentially expressed mRNAs was screened by using Limma package based on Benjamini & Hochberg false discovery rate algorithm of R language. Gene ontologies ( GOs) and Kyoto Encyclopedia of Genes and Genomes ( KEGG) signal pathway enrichment analysis were performed by using DAVID database. The protein - protein interaction network was constructed by STRING - db database, and hub genes were obtained by Cytoscape. Results The differential expression of mRNA gene chip data set GSE4883 showed that 214 mRNAs were differentially expressed. GO analysis indicated that several functional pathways,such as immune response,cellular response to interleukin - 1,interferon and monocyte chemotaxis were enriched. KEGG pathway analysis showed some related pathways,including cytokine - cytokine receptor interaction,rheumatoid arthritis andchemokine signaling pathways. Ten hub genes were obtained from the protein - protein interaction network,including KIF11,CDK1,NDC80, RRM2,NCAPG,NUF2,MAD2L1,KIF15,TOP2A and HELLS. Conclusion Bioinformatic methods for screening simvastatin related DEGs can provide a new way for new biomarkers of simvastatin treatment. The genes identified in the present study might be prognostic factors as well as potential therapeutic targets in the usage of simvastatin.

关 键 词：辛伐他汀 关键基因 蛋白互作网络 生物信息学 

分 类 号：R972.6[医药卫生—药品]