Drug Repurposing to Identify Nilotinib as a Potential SARS-CoV-2 Main Protease Inhibitor: Insights from a Computational and In Vitro Study

Abstract

COVID-19, an acute viral pneumonia, has emerged as a devastating pandemic. Drug repurposing allows researchers to find different indications of FDA-approved or investigational drugs. In this current study, a sequence of pharmacophore and molecular modeling-based screening against COVID-19 M^pro (PDB: 6LU7) suggested a subset of drugs, from the Drug Bank database, which may have antiviral activity. A total of 44 out of 8823 of the most promising virtual hits from the Drug Bank were subjected to molecular dynamics simulation experiments to explore the strength of their interactions with the SARS-CoV-2 M^pro active site. MD findings point toward three drugs (DB04020, DB12411, and DB11779) with very low relative free energies for SARS-CoV-2 M^pro with interactions at His41 and Met49. MD simulations identified an additional interaction with Glu166, which enhanced the binding affinity significantly. Therefore, Glu166 could be an interesting target for structure-based drug design. Quantitative structural-activity relationship analysis was performed on the 44 most promising hits from molecular docking-based virtual screening. Partial least square regression accurately predicted the values of independent drug candidates' binding energy with impressively high accuracy. Finally, the EC₅₀ and CC₅₀ of 10 drug candidates were measured against SARS-CoV-2 in cell culture. Nilotinib and bemcentinib had EC₅₀ values of 2.6 and 1.1 μM, respectively. In summary, the results of our computer-aided drug design provide a roadmap for rational drug design of M^pro inhibitors and the discovery of certified medications as COVID-19 antiviral therapeutics.

Fig. 1.

Recently discovered SARS-CoV-2 M^pro cocrystal structures. A. COVID-19 M^pro in complex with an inhibitor N3 (PDB: 6LU7). B. SARS-CoV-2 M^pro in complex with inhibitor Z18197050 (PDB: 5R80). C. COVID-19 M^pro in complex with inhibitor Z45617795 (PDB:5R7Y)

Fig. 2.

A. Workflow to identify repurposed therapeutics as potential SARS-COV-2 M^pro inhibitors B. Top ten drugs biologically evaluated for SARS-COV-2 replication inhibition.

Fig. 3.

Structure based pharmacophore models generated by LigandScout. A. Structure based pharmacophore model for M^pro-N3 complex (PDB: 6LU7) mapped to bound inhibitor N3. B. Structure based pharmacophore model for M^pro-Z45617795 complex (PDB: 5R7Y) mapped to bound inhibitor Z45617795. C. Structure based pharmacophore model for M^pro- Z18197050 complex (PDB: 5R80) mapped to bound inhibitor Z18197050. D. Fourteen featured Merged pharmacophore, generated by aligning 3 SB pharmacophore models by reference point (6LU7 SB pharmacophore model), generating shared feature pharmacophores, then merging and interpolating overlapping features using LigandScout’s alignment module. Merged pharmacophore contains 4 hydrophobic features, 8 hydrogen-bond donner features, and 2 hydrogen-bond acceptor features. Exclusion volumes are not shown. : Hydrophobic interaction, : hydrogen-bond donner, : hydrogen-bond acceptor, : positive ionizable area.

Fig. 4.

Conformation of drugs with high binding affinities bound in the active site of M^pro (PDB: 6LU7) and surrounding protein residues. (A) Bemcentinib (B) Nilotinib (C) Enasidenib (D) Tegobuvir (E) Ziresovir (F) Selinexor (G) Nafamostat.

Fig. 5.

The RMSD deviation for all 44 drugs.

Fig. 6.

Key interactions for the top three drugs during the MD simulations.

Fig. 7.

Inhibitory activity of Nilotinib, Bemcentinib, and Remdesivir (positive control) in Vero-E6 cell.

Fig. 8.

Scores Plots of PCA showing groupings of drug candidates based on similarity and differences in drugs QSAR