Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease

Abstract

The study aims to evaluate the potency of two hundred natural antiviral phytocompounds against the active site of the Severe Acquired Respiratory Syndrome - Coronavirus − 2 (SARS-CoV-2) Main-Protease (M^pro) using AutoDock 4.2.6. The three- dimensional crystal structure of the M^pro (PDB Id: 6LU7) was retrieved from the Protein Data Bank (PDB), the active site was predicted using MetaPocket 2.0. Food and Drug Administration (FDA) approved viral protease inhibitors were used as standards for comparison of results. The compounds theaflavin-3-3’-digallate, rutin, hypericin, robustaflavone, and (-)-solenolide A with respective binding energy of −12.41 (Ki = 794.96 pM); −11.33 (Ki = 4.98 nM); −11.17 (Ki = 6.54 nM); −10.92 (Ki = 9.85 nM); and −10.82 kcal/mol (Ki = 11.88 nM) were ranked top as Coronavirus Disease − 2019 (COVID-19) M^pro inhibitors. The interacting amino acid residues were visualized using Discovery Studio 3.5 to elucidate the 2-dimensional and 3-dimensional interactions. The study was validated by i) re-docking the N3-peptide inhibitor-M^pro and superimposing them onto co-crystallized complex and ii) docking decoy ligands to M^pro. The ligands that showed low binding energy were further predicted for and pharmacokinetic properties and Lipinski’s rule of 5 and the results are tabulated and discussed. Molecular dynamics simulations were performed for 50 ns for those compounds using the Desmond package, Schrödinger to assess the conformational stability and fluctuations of protein-ligand complexes during the simulation. Thus, the natural compounds could act as a lead for the COVID-19 regimen after in-vitro and in- vivo clinical trials.

Communicated by Ramaswamy H. Sarma

Graphical Abstract

Keywords:

• Antiviral phytocompounds
• SARS-CoV-2
• main-protease
• COVID-19
• decoy ligands
• pharmacokinetic properties
• molecular dynamics simulations

Acknowledgements

The authors sincerely thank Vels Institute of Science, Technology and Advanced Studies for the successful completion of the research work, Mr. Suyash Pant, National Institute of Pharmaceutical Education and Research, Kolkata, West Bengal, and Kumaun University, Bhimtal campus for performing Molecular Dynamics Simulations. We are also grateful to Dr. Priyanka Purkayastha, Senior Data Engineer, FedEx, the Netherlands to help attain publishable status and reviewers for providing valuable suggestions.

Disclourse statement

The authors declare a conflict of interest as none.