In silico identification of novel SARS-COV-2 2'-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches

Abstract

The novel coronavirus disease COVID-19, caused by the virus SARS CoV-2, has exerted a significant unprecedented economic and medical crisis, in addition to its impact on the daily life and health care systems all over the world. Regrettably, no vaccines or drugs are currently available for this new critical emerging human disease. Joining the global fight against COVID-19, in this study we aim at identifying a potential novel inhibitor for SARS COV-2 2'-O-methyltransferase (nsp16) which is one of the most attractive targets in the virus life cycle, responsible for the viral RNA protection via a cap formation process. Firstly, nsp16 enzyme bound to Sinefungin was retrieved from the protein data bank (PDB ID: 6WKQ), then, a 3D pharmacophore model was constructed to be applied to screen 48 Million drug-like compounds of the Zinc database. This resulted in only 24 compounds which were subsequently docked into the enzyme. The best four score-ordered hits from the docking outcome exhibited better scores compared to Sinefungin. Finally, three molecular dynamics (MD) simulation experiments for 150 ns were carried out as a refinement step for our proposed approach. The MD and MM-PBSA outputs revealed compound 11 as the best potential nsp16 inhibitor herein identified, as it displayed a better stability and average binding free energy for the ligand-enzyme complex compared to Sinefungin.

Keywords: 3D pharmacophore; COVID-19 therapies; MM-PBSA calculations; SARS COV-2 2′-O-methyltransferase (nsp16) Inhibitor; molecular dynamics.

Figure 1.

The virtual screening steps and the implemented protocol for the identification of potential inhibitors for SARS COV-2 2′-O-methyltransferase (nsp16).

Figure 2.

2D Binding of sinefungine within SARS-COV-2 2′-O-methyltransferase binding site after 10 ns of equilibration.

Figure 3.

The generated 3D pharmacophore; Blue spheres represent acceptor features, pale pink sphere represents donor features, dark pink spheres represent cationic donor features and orange sphere represents aromatic feature.

Figure 4.

Chemical structures for compounds 5, 9, 11 and 24.

Figure 5.

2D interactions of compounds 5 (A), 9 (B), 11 (C) and 24 (D) within SARS-COV-2 2′-O-methyltransferase binding site.

Figure 6.

3D representation for inhibitors 5 (A), 9 (B), 11 (C) and 24 (D) displaying their interactions within SARS-COV-2 2′-O-methyltransferase binding site.

Figure 7.

The RMSD of three dynamic simulation experiments. Green colour represents SARS COV-2 2′-O-methyltransferase without a ligand; blue line represents SARS COV-2 2′-O-methyltransferase complex with Sinefungine, and Red line represents SARS COV-2 2′-O-methyltransferase complex with compound 11.