Synthesis and Identification of Novel Potential Molecules Against COVID-19 Main Protease Through Structure-Guided Virtual Screening Approach

Abstract

The novel coronavirus disease that arises in the end of 2019 (COVID-19) in Wuhan, China, has rapidly spread over the globe and was considered as a world pandemic. Currently, various antiviral therapies or vaccines are available, and many researches are ongoing for further treatments. Targeting the coronavirus' main protease (key enzyme: 3CLpro) is growing in importance in anti-SARS-CoV-2 drug discovery process. The present study aims at predicting the antiviral activity of two novel compounds using in silico approaches that might become potential leads against SARS-CoV-2. The 3D structures of the new compounds are elucidated by single-crystal X-ray techniques. The interactions between different units of 4 and 5 were emphasized by analyzing their corresponding Hirshfeld surfaces and ESP plots. NBO and FMO analyses were investigated as well. Molecular docking combined with molecular dynamics simulations (MDs) was performed to investigate the binding modes and molecular interactions of 4 and 5 with the amino acids of coronavirus main protease (6LU7) protein. The best docking scores were obtained for both ligands through the major binding interactions via hydrogen/hydrophobic bonds with the key amino acids in the active site: HIS41, CYS145, MET49, MET165, HIS172, and GLU166 amino acids. A MD simulation study was also performed for 100 ns to validate the stability behavior of the main protease 3CLpro-ligand complexes. The MD simulation study successfully confirmed the stability of the ligands in the binding site as potent anti-SARS-CoV-2 (COVID-19) inhibitors. Additionally, MMPBSA energy of both docked complexes was determined as a validation assay of docking and MD simulations to validate compound conformation and interaction stability with 3CLpro. The synthesized compounds might be helpful in the fight against COVID-19 prior to biological activity confirmation in vitro and in vivo.

Keywords: Benzodiazepine; COVID-19; Molecular docking; Molecular dynamics simulation; Quinoxaline; SARS-CoV-2.