A Computational Approach for Predicting Role of Human MicroRNAs in MERS-CoV Genome
Author(s) -
Md. Mahmudul Hasan,
Rozina Akter,
Md. Shahin Ullah,
Md. Jaynul Abedin,
G. M. Ahsan Ullah,
Md Zakir Hossain
Publication year - 2014
Publication title -
advances in bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.33
H-Index - 20
eISSN - 1687-8035
pISSN - 1687-8027
DOI - 10.1155/2014/967946
Subject(s) - microrna , gene , genome , computational biology , middle east respiratory syndrome coronavirus , biology , virology , covid-19 , genetics , medicine , disease , pathology , infectious disease (medical specialty)
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.
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