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

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 ( M pro ) 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 M pro . 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 M pro through extensive computational analysis. This study performed a full-scale in silico investigations on natural quinazoline alkaloids against the main protease (MPro) of SARS_CoV_2 by examining forty one natural quinazoline alkaloids and identified three alkaloids (CNP0416047, 3-hydroxy anisotine and anisotine) as final lead compounds. The screening and structure-based analysis of these ligands were carried out by blending different computational techniques such as rigid docking, pharmacokinetics, flexible docking, E-pharmacophore mapping, DFT studies and MD simulations. Mostly, this study added values to quinazoline alkaloids which are fascinating natural pharmacophores and opened the possibilities of in vitro studies of these hit alkaloids in future. [ABSTRACT FROM AUTHOR]