An in silico analysis of effective siRNAs against COVID-19 by targeting the leader sequence of SARS-CoV-2

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a retrovirus having genome size of around 30 kb. Its genome contains a highly conserved leader sequence at its 5′ end, which is added to all subgenomic mRNAs at their 5′ terminus by a discontinuous transcription mechanism and regulates their translation. Targeting the leader sequence by RNA interference can be an effective approach to inhibit the viral replication. In the present study an in-silico prediction of highly effective siRNAs was performed to target the leader sequence using the online software siDirect version 2.0. Low seed-duplex stability, exact complementarity with target, at least three mismatches with any off-target and least number of off-targets, were considered as effective criteria for highly specific siRNA. Further validation of siRNA affinity for the target was accomplished by molecular docking by HNADOCK online server. Our results revealed four potential siRNAs, of which siRNA having guide strand sequence 5′GUUUAGAGAACAGAUCUACAA3′ met almost all specificity criteria with no off-targets for guide strand. Molecular docking of all predicted siRNAs (guide strand) with the target leader sequence depicted highest binding score of −327.45 for above-mentioned siRNA. Furthermore, molecular docking of the passenger strand of the best candidate with off-target sequences gave significantly low binding scores. Hence, 5′GUUUAGAGAACAGAUCUACAA3′ siRNA possess great potential to silence the leader sequence of SARS-CoV-2 with least off-target effect. Present study provides great scope for development of gene therapy against the prevailing COVID-19 disease, thus further research in this concern is urgently demanded.