In silico identification of a potential inhibitor of the SARS-CoV-2 S-glycoprotein receptor-binding domain interaction with human ACE2

Introduction: SARS-CoV-2 is an emerging pathogen that has strongly affected humanity over the past few years. Its S-glycoprotein receptor-binding domain provides the primary recognition of the host cell and initiates the viral penetration.The goal of our work was to find potential inhibitors of the entry stage of the SARS-CoV-2 life cycle. Methodology: firstly seven investigated compounds were prepared by generating their three-dimensional coordinates and protonating according to neutral pH in the OpenBabel ObGUI interface. Next, the mini-library was docked into the RBD interaction site with hACE2 using the AutoDock Vina. Part of the target amino acid residues was considered mobile. Based on the affinity assessment, four substances were selected for research in a simulation experiment implemented within the CHARMM-GUI, GROMACS and gmx_MMPBSA functionality. Results: only four out of seven studied compounds were characterized by the optimal initial pattern of interactions and the calculated affinity. Further simulation studies allowed to discard three more on the basis of their dissociation from the docking site within 5ns from the simulation beginning. The last compound pyrazolothiadiazepine 1794 had an optimal position and the RMSD value of 1-2 Å during 150ns of simulation. At the same time, the calculated binding free energy of 1794 with RBD was -20.59 kcal/mol. Conclusion: on the basis of molecular dynamics simulation analysis of the ligand-receptor complex, compound 1794 was selected as a potential inhibitor of the SARS-CoV-2 RBD interaction with human ACE2. It is characterized by the RMSD within 1-2 Å and a calculated ΔG of -20.59 kKal/mol.