A Computational Approach for Predicting Role of Human MicroRNAs in MERS-CoV Genome

A Computational Approach for Predicting Role of Human MicroRNAs in MERS-CoV Genome

Md. Zakir Hossain, Rozina Akter, Md Mahmudul Hasan, Md. Shahin Ullah, Md. Jaynul Abedin, G. M. Ahsan Ullah

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.

2014

DOI: 10.1155/2014/967946

Advances in Bioinformatics

Hindawi Limited

Biology (General), Statistics