Computational Investigation on Natural Quinazoline Alkaloids as Potential Inhibitors of the Main Protease (Mpro) of SARS-CoV-2

Abstract

Drug discovery is still behind in the race compared to vaccine discovery in fighting COVID-19. In this study, we have selected 41 quinazoline alkaloids from two natural product databases to create an adequate library and performed detailed computational studies against the main protease ([Formula: see text]) of SARS-CoV-2 using two reference compounds, namely famotidine and X77. The screening of the library was carried out by blending the rigid docking and pharmacokinetic analysis that resulted in nine alkaloids as initial leads against [Formula: see text]. These initial leads were further subjected to advanced flexible docking and were compared with reference compounds (famotidine and X77) for the analysis of structure-based interactions. For further selection, a second screening was carried out based on binding energies and interaction profiles that yielded three alkaloids, namely CNP0416047, 3-hydroxy anisotine and anisotine as final leads. The stereo-electronic features of lead alkaloids were further investigated through additional E-pharmacophore mapping against crystallized X77 reference compound. Additionally, the reactivity of lead alkaloids at the binding sites of the protein was estimated by measuring the electron distribution on the frontier molecular orbitals and HOMO–LUMO band energies. Finally, the stabilities of complexes between lead alkaloids with the protein were accessed extensively using robust molecular dynamics simulation through RMSD, RMSF, Rg and MM-PBSA calculation. Thus, this study identifies three natural quinazoline alkaloids as potential lead inhibitors of [Formula: see text] through extensive computational analysis.