Identification of potential multi-target natural compounds against SARS-CoV-2 by targeting its essential proteins: A molecular docking and dynamics simulation approach to combat COVID-19

The emergence of SARS-CoV-2 is gravely affecting human society and causing millions of deaths. In addition to an effective vaccine, a potential drug is urgently required to combat COVID-19 instantly. To overcome this problem,  we employed computer-aided drug design strategies to discover potent natural compounds that can inhibit the SARS-CoV-2. For this virtual drug designing study, we selected six essential proteins of SARS-CoV-2, helicase, methyltransferase, RNA-dependent RNA polymerase, endoribonuclease, exoribonuclease, and 3C-like protein. Targeting these six proteins, the natural molecules derived from the NPASS database were screened in a structure-based virtual approach. After extensive analysis of binding affinity (docking score) and binding energy (MMGBSA score) of natural compounds for each target protein, we identified three multi-target natural compounds having stronger binding potential with at least three protein targets. Also, the molecular dynamics analysis (RMSD and RMSF) reveals the stable conformational changes of protein-ligand complexes inside the virtual biological dynamic environment. Conclusively, further in vitro and in vivo studies of these potent multi-target natural compounds can be used as an instant therapy to fight against COVID-19.