Screening Malaria-box compounds to identify potential inhibitors against SARS-CoV-2 Mpro, using molecular docking and dynamics simulation studies

Abstract

Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) Main protease (M^pro) is one of the vital drug targets amongst all the coronaviruses, as the protein is indispensable for virus replication. The study aimed to identify promising lead molecules against M^pro enzyme through virtual screening of Malaria Venture (MMV) Malaria Box (MB) comprising of 400 experimentally proven compounds. The binding affinities were studied using virtual screening based molecular docking, which revealed five molecules having the highest affinity scores compared to the reference molecules. Utilizing the established 3D structure of M^pro the binding affinity conformations of the docked complexes were studied by Molecular Dynamics (MD) simulations. The MD simulation trajectories were analysed to monitor protein deviation, relative fluctuation, atomic gyration, compactness covariance, residue-residue map and free energy landscapes. Based on the present study outcome, we propose three Malaria_box (MB) compounds, namely, MB_241, MB_250 and MB_266 to be the best lead compounds against M^pro activity. The compounds may be evaluated for their inhibitory activities using experimental techniques.

Keywords: COVID-19; M(pro); MMV Malaria_box; SARS-CoV-2; Virtual screening and MD simulations.

Graphical abstract

Fig. 1

Schematic diagram of SARS-CoV-2 surface proteins and M^pro, including ACE2 receptor binding, viral fusion and entry of virus in host cell as well as overall representation of in silico work-flow implemented in the current study.

Fig. 2

Representation of the binding poses, H-bonds and the amino acid residues in the active pocket of M^pro ligand interaction site (A) MB_183, (B) MB_241, (C) MB_250, (D) MB_266, (E) MB_380, (F) N3 inhibitor and (G) Boceprevir drug.

Fig. 3

The interactive site between M^pro-ligands after docking studies depicting H-bonds, hydrophobic interactions, Van der Waal's interactions around 4 Å of the binding cavity A) MB_183, (B) MB_241, (C) MB_250 (D) MB_266, (E) MB_380, (F) N3 inhibitor and (G) Boceprevir drug.

Fig. 4

RMSD and RMSF analysis of the complexes of native protein, complexes of shortlisted ligands and reference complexes (A) RMSD plot (B) PDF of RMSD (C) Combined RMS fluctuations.

Fig. 5

SASA and radius of gyration (Rg) during MD simulations (A) Rg plot of native, MB_183, MB_241, MB_250, MB_266 and MB_380, N3 and Boceprevir docked complexes (B) The average PDF of Rg for the docked complexes (C) SASA analysis plot of M^pro-docked complexes(D) The PDF plot representing the SASA average values for the docked complexes.

Fig. 6

Hydrogen bonds and Eigen-vector plot of the docked complexes (A) Number of H-bonds in MB_183, (B) MB_241, (C) MB_250, (D) MB_266 (E) MB_380, (F) N3 inhibitor and (G) Boceprevir drug (H). The dynamic energy fluctuation plotted between two eigenvector 1 and 2 generated for the docked complexes showing conformational space of Cα-atoms.

Fig. 7

Density distribution of docked complexes obtained in the MD trajectories during simulation time-frames (A) Native, (B) MB_183, (C) MB_241, (D) MB_250, (E) MB_266 (F) MB_380, (G) N3 inhibitor, (H) Boceprevir drug.

Fig. 8

Depiction of residue contact map and the mean smallest distance between the Cα-atoms of each amino acid residues of M^pro corresponding to docked compounds (A) Native (B) MB_183, (C) MB_241, (D) MB_250, (E) MB_266 (F) MB_380, (G) N3 inhibitor and (H) Boceprevir drug. (Red, yellow and orange colours indicate strong correlations, whereas longer distance is shown in blue colour).