A computational approach for rational discovery of inhibitors for non-structural protein 1 of SARS-CoV-2. (August 2021) - Singh, Rahul; Bhardwaj, Vijay Kumar; Das, Pralay; Purohit, Rituraj
Abstract: Background: Non-structural protein 1 (Nsp1), a virulence agent of SARS-CoV-2, has emerged as an important target for drug discovery. Nsp1 shuts down the host gene function by associating with the 40S ribosomal subunit. Methods: Molecular interactions, drug-likeness, physiochemical property predictions, and robust molecular dynamics (MD) simulations were employed to discover novel Nsp1 inhibitors. In this study, we evaluated a series of molecules based on the plant ( Cedrus deodara ) derived α, β, γ -Himachalenes scaffolds. Results: The results obtained from estimated affinity and ligand efficiency suggested that BCH10, BCH15, BCH16, and BCH17 could act as potential inhibitors of Nsp1. Moreover, MD simulations comprising various MD driven time-dependent analyses and thermodynamic free energy calculations also suggested stable protein-ligand complexes and strong interactions with the binding site. Furthermore, the selected molecules passed drug likeliness parameters and the physiochemical property analysis showed acceptable bioactivity scores. Conclusion: The structural parameters of dynamic simulations revealed that the reported molecules could act as lead compounds against SARS-CoV-2 Nsp1 protein. Graphical abstract: Image 1 Highlights: Computational approaches implemented for lead identification against SARS-CoV-2. Four molecules confer strong binding toward Nsp1 protein of SARS-CoV-2. The in-silico physiochemical analysis showed molecules are biologically active. The results of this study provide crucial data to develop antiviral drugs for COVID-19.