Prediction of genes and protein-protein interaction networking for miR-221-5p using bioinformatics analysis

被引:2
|
作者
Othman, Shanmugapriya Nurulhasanah [1 ]
Sasidharan, Sreenivasan [1 ]
机构
[1] Univ Sains Malaysia, Inst Res Mol Med, George Town 11800, Malaysia
来源
GENE REPORTS | 2019年 / 16卷
关键词
microRNA; Gene targets prediction; Gene ontology; Apoptosis; Protein-protein interaction networking; NF-KAPPA-B; CELL-CYCLE ARREST; PROSTATE-CANCER; INDUCED APOPTOSIS; ERK ACTIVATION; SIGNAL-TRANSDUCTION; CERVICAL-CANCER; MESSENGER-RNA; RIBOSOMAL-PROTEINS; YEAST; 2-HYBRID;
D O I
10.1016/j.genrep.2019.100426
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Recent scientific investigations on P. longifolia leaf extract revealed its anti-cancer property via the regulation of miR-221-5p. However, there were no further investigations performed to report the role miR-221-5p through the regulation of its target genes and the subsequent protein-protein interaction networking which is important in cancer pathogenesis. Therefore, in silico approach was utilized to predict the target genes and protein-protein interaction networking related to miR-221. Therefore, the current research was conducted to analyse the predicted target genes and biological pathways for miR-221-5p as well as to investigate the protein-protein interaction networking using authoritative bioinformatics tools. In this study, computational workflow was proposed to identify the predicted target genes of miR-221-5p using miRGate database, followed by gene enrichment analysis by DAVID and Enrichr bioinformatics and finally protein-protein interaction networking analysis using STRING resource. miR-Gate bioinformatics tool predicted a total of 4910 protein coding gene targets for miR-221-5p, which includes 326 apoptotic genes based on 5 different computation approaches and 4 different validated prediction methods. The gene enrichment analysis through DAVID and Enrichr bioinformatics tools revealed that the predicted genes are involved in the regulation apoptotic pathway based on the gene ontology analysis accounting an enrichment score as high as 7.41 and a false discovery rate as low as 0.12. The protein-protein interaction networking analysis through STRING bioinformatics tool revealed the functional enrichment of the protein network of the post-transcriptional of the predicted gene targets of miR-221-5p are highly related to the regulation of apoptosis with an interaction confidence score of 0.99. The bioinformatics analysis of miR-221-5p revealed the essential role of miR-221-5p in various biological processes, especially in apoptosis regulation, suggesting the regulation of miR-221-5p to be an efficient gene therapeutic target for cancer as a clinically admissible treatment approach.
引用
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页数:13
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