A Computational Approach for Predicting Role of Human MicroRNAs in MERS-CoV Genome. (22nd December 2014)

• Record Type: Journal Article
• Authors: Hasan, Md Mahmudul; Akter, Rozina; Ullah, Md. Shahin; Abedin, Md. Jaynul; Ullah, G. M. Ahsan; Hossain, Md. Zakir
• Other Names: Hong Huixiao Academic Editor.
• Is Part Of: Advances in bioinformatics. Volume 2014(2014)
• Publication Date: 2014-12-22
• Subjects: Bioinformatics -- Periodicals; Bioinformatics; Computational Biology -- Periodicals; Periodicals; 570.285
• DOI: 10.1155/2014/967946
• Languages: English
• ISSNs: 1687-8027

Abstract

Abstract : The new epidemic Middle East Respiratory Syndrome (MERS) is caused by a type of human coronavirus called MERS-CoV which has global fatality rate of about 30%. We are investigating potential antiviral therapeutics against MERS-CoV by using host microRNAs (miRNAs) which may downregulate viral gene expression to quell viral replication. We computationally predicted potential 13 cellular miRNAs from 11 potential hairpin sequences of MERS-CoV genome. Our study provided an interesting hypothesis that those miRNAs, that is, hsa-miR-628-5p, hsa-miR-6804-3p, hsa-miR-4289, hsa-miR-208a-3p, hsa-miR-510-3p, hsa-miR-18a-3p, hsa-miR-329-3p, hsa-miR-548ax, hsa-miR-3934-5p, hsa-miR-4474-5p, hsa-miR-7974, hsa-miR-6865-5p, and hsa-miR-342-3p, would be antiviral therapeutics against MERS-CoV infection.