Structure-Based Virtual Screening and Molecular Dynamics Simulation to Identify Potential SARS-CoV-2 Spike Receptor Inhibitors from Natural Compound Database.

The outbreak of respiratory disease, COVID-19 caused by SARS-CoV-2 has now been spread globally and the number of new infections is rising every moment. There are no specific medications that are currently available to combat the disease. The spike receptor of SARS-CoV-2 facilitates the viral entry into a host cell and initiation of infection. Targeting the viral entry at the initial stage has a better advantage than inhibiting it in later stages of the viral life cycle. This study deals with identification of the potential natural molecule or its derivatives from MolPort Databank as SARS-CoV-2 spike receptor inhibitors using structure-based virtual screening followed by molecular dynamics simulation. On the basis of ADME properties, docking score, MMGBSAbinding energy, 150 ns molecular docking studies, and final molecular dynamics analysis, two natural compounds - (MolPort-002-535-004) docking score -9.10 kcal mol-1 and (MolPort-005-910-183) docking score -8.5 kcal mol, are selected as potential in-silico spike receptor inhibitors. Both hits are commercially available and can be further used for and studies. Findings of this study can facilitate rational drug design against SARS-CoV-2 spike receptor.