Computational investigation for identification of potential phytochemicals and antiviral drugs as potential inhibitors for RNA-dependent RNA polymerase of COVID-19

Abstract

Since the SARS/MERS epidemic, scientists across the world have been racing to identify the novel-CoVs as it has been predicted that next epidemic can very well be a result from a new mutation of CoV, for which hundred mutations have already been discovered, and the same fear has come true with world facing a raging pandemic due to COVID-19, an infectious disease caused by a newly discovered coronavirus. COVID-19 or Severe acute respiratory syndrome coronavirus2 (SARS-CoV-2), is a single stranded RNA virus. COVID −19 is highly contagious and has resulted in current global pandemic with almost no country of the world unaffected by this virus. Owing to the lack of effective therapeutics or vaccines, the best measures to control human coronaviruses remain a strong public health surveillance system coupled with rapid diagnostic testing and quarantine/social; distancing/lockdowns as and when necessary. In the present study, we have used the insilico approach for the prediction of novel drug molecules from available antiviral drugs and also from natural compounds that can be best target against RNA-dependent RNA-polymerase (Pol/RdRp) protein of SARS-CoV-2 which can be suitable drugs for the treatment of COVID-19 virus. From the current study we observed that three antiviral and three phyto-chemicals have minimum binding energy with the target protein which were further evaluated in molecular dynamics studies and could specifically bind to RdRp protein of COVID-19. Based on results we suggest that these drugs may act as best or novel inhibitor that may be used for the treatment of SARS-CoV-2. Communicated by Ramaswamy H. Sarma