Background: The unusual pneumonia outbreak that originated in the city of Wuhan, China in December
2019 was found to be caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or
Methods: In this work, we have performed an in silico design and prediction of potential siRNAs based on genetic
diversity and recombination patterns, targeting various genes of SARS-CoV-2 for antiviral therapeutics.
We performed extensive sequence analysis to analyze the genetic diversity and phylogenetic relationships, and
to identify the possible source of virus reservoirs and recombination patterns, and the evolution of the virus as
well as we designed the siRNAs which can be used as antivirals against SARS-CoV-2.
Results: The sequence analysis and phylogenetic relationships indicated high sequence identity and closed clusters
with many types of coronavirus. In our analysis, the full-genome of SARS-CoV-2 showed the highest sequence
(nucleotide) identity with SARS-bat-ZC45 (87.7%). The overall sequence identity ranged from 74.3%
to 87.7% with selected SARS viruses. The recombination analysis indicated the bat SARS virus is a potential
recombinant and serves as a major and minor parent. We have predicted 442 siRNAs and finally selected only
19 functional, and potential siRNAs.
Conclusion: The siRNAs were predicted and selected based on their greater potency and specificity. The predicted
siRNAs need to be validated experimentally for their effective binding and antiviral activity.