Serveur d'exploration MERS

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

Identifieur interne : 001D67 ( Main/Exploration ); précédent : 001D66; suivant : 001D68

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

Auteurs : Md Mahmudul Hasan [États-Unis] ; Rozina Akter [États-Unis] ; Md. Shahin Ullah [Bangladesh] ; Md. Jaynul Abedin [Bangladesh] ; G. M. Ahsan Ullah [Bangladesh] ; Md. Zakir Hossain [États-Unis]

Source :

RBID : PMC:4283225

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.


Url:
DOI: 10.1155/2014/967946
PubMed: 25610462
PubMed Central: 4283225


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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