Drug repurposing against SARS-CoV-2 using E-pharmacophore based virtual screening, molecular docking and molecular dynamics with main protease as the target

Abstract

Since its first report in December 2019 from China, the COVID-19 pandemic caused by the beta-coronavirus SARS-CoV-2 has spread at an alarming pace infecting about 5.59 million, and claiming the lives of more than 0.35 million individuals across the globe. The lack of a clinically approved vaccine or drug remains the biggest bottleneck in combating the pandemic. Drug repurposing can expedite the process of drug development by identifying known drugs which are effective against SARS-CoV-2. The SARS-CoV-2 main protease is a promising drug target due to its indispensable role in viral multiplication inside the host. In the present study an E-pharmacophore hypothesis was generated using a crystal structure of the viral protease in complex with an imidazole carbaximide inhibitor. Drugs available in the superDRUG2 database were used to identify candidate drugs for repurposing. The hits obtained from the pharmacophore based screening were further screened using a structure based approach involving molecular docking at different precisions. The binding energies of the most promising compounds were estimated using MM-GBSA. The stability of the interactions between the selected drugs and the target were further explored using molecular dynamics simulation at 100 ns. The results showed that the drugs Binifibrate and Bamifylline bind strongly to the enzyme active site and hence they can be repurposed against SARS-CoV-2. However, U.S Food and Drug Administration have withdrawn Binifibrate from the market as it was having some adverse health effects on patients.Communicated by Ramaswamy H. Sarma.

Keywords: E-pharmacophore; SARS-CoV-2; drug repurposing; main protease; molecular docking; molecular dynamics.

Figure 1.

E-pharmacophore model for M^pro-X77 complex mapped to the bound inhibitor X77: The left panel shows the bound inhibitor X77 (ball-and-stick model) in the active site of M^pro (ribbon model). The E-pharmacophore features of the inhibitor are shown in red. The right panel is a zoomed in image of the inhibitor, X77 with the pharmacophore features marked in red.

Figure 2.

Energy optimised pharmacophore hypothesis AARRR. A3 and A4 are hydrogen bond acceptors; R9, R10 and R11 are aromatic rings. The distances between the pharmacophore features are also shown.

Figure 3.

The docked pose of X77 (red) superimposed on the crystal structure (green).

Figure 4.

Interactions between standard inhibitor X77 and M^pro active site residues. (a) X77-M^pro interactions in the crystal structure. (b) X77-M^pro interactions in the docked structure.

Figure 5:

Conformation of drugs with highest binding energies bound in the active site of M^pro and surrounding protein residues. (a) Afatinib (b) Bamifylline (c) Ezetimibe (d) Binifibrate (e) Macimorelin acetate (f), Rilmazafone.

Figure 6.

Protein and ligand RMSD of SARS-CoV-2 M^pro in complex with (a) Binifibrate, (b) Macimorelin acetate, (c) Bamifylline and (d) Rilmazafone as observed in the 100 ns MD simulations.

Figure 7.

Schematic diagram of the ligand interactions with surrounding protein residues. (a) Binifibrate, (b) Macimorelin acetate, (c) Bamifylline and (d) Rilmazafone during the course of MD simulation.

Figure 8.

The comparison of binding energy values before and after MD simulation.