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The Middle East respiratory syndrome coronavirus (MERS-CoV) is a virus that manifests itself in viral infection with fever, cough, shortness of breath, renal failure and severe acute pneumonia, which often result in a fatal outcome. MERS-CoV has been shown to spread between people who are in close contact. Transmission from infected patients to healthcare personnel has also been observed and is irredeemable with present technology. Genetic studies on MERS-CoV have shown that ORF1ab encodes replicase polyproteins and play a foremost role in viral infection. Therefore, ORF1ab replicase polyprotein may be used as a suitable target for disease control. Viral activity can be controlled by RNA interference (RNAi) technology, a leading method for post transcriptional gene silencing in a sequence-specific manner. However, there is a genetic inconsistency in different viral isolates; it is a great challenge to design potential RNAi (miRNA and siRNA) molecules which can silence the respective target genes rather than any other viral gene simultaneously. In the current study, four effective miRNA and five siRNA molecules for silencing of nine different strains of MERS-CoV were rationally designed and corroborated using computational methods, which might lead to knockdown the activity of virus. siRNA and miRNA molecules were predicted against ORF1ab gene of different strains of MERS-CoV as effective candidate using computational methods. Thus, this method may provide an insight for the chemical synthesis of antiviral RNA molecule for the treatment of MERS-CoV, at genomic level.

interdisciplinary sciences: computational life sciences

Design of Potential RNAi (miRNA and siRNA) Molecules for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Gene Silencing by Computational Method