To fight against the devastating COVID-19 pandemic, identifying robust anti-SARS-CoV-2 therapeutics from all possible directions is demanding. To contribute to this effort, we selected a human metabolites database containing thousands of water and lipid-soluble metabolites to screen against 3-chymotrypsin-like proteases (3CL pro ) protein of SARS-CoV-2. This protease has a critical role in the virus life cycle, making it a potential drug target against COVID-19. The top 8 hits, obtained from virtual screening, displayed a docking score varying between ~ -11 to ~ -14 kcal/mol. The virtual screening study is complemented by molecular dynamics simulations in conjunction with the molecular mechanics generalized Born surface area (MM/GBSA) scheme. Molecular docking and molecular dynamics studies revealed that (HMDB0132640) has the best glide docking score, -14.06 kcal/mol, and MM-GBSA binding free energy, -18.08 kcal/mol. The other three lead molecules are also selected along with the top lead through a critical inspection of their pharmacokinetics properties. HMDB0132640 displayed a better binding affinity compared to the other three compounds (HMDB0127868, HMDB0134119, and HMDB0125821) due to increased favorable contributions from the intermolecular electrostatic and van der Waals interactions. Critical residues involved in the protein-ligand interactions were identified via per-residue decomposition of the binding free energy. Further, we have investigated the ligand-induced structural dynamics of the main protease. Overall, we have identified new compounds that can serve as potential leads for developing novel antiviral drugs against SARS-CoV-2 and elucidated molecular mechanisms of their binding to the main protease.
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Computational studies indicated the effectiveness of human metabolites against SARS-CoV-2 main protease.
Published:
01 November 2022
by MDPI
in 8th International Electronic Conference on Medicinal Chemistry
session Small molecules as drug candidates
Abstract:
Keywords: SARS-COV-2; Main Protease; Human metabolites; Virtual Screening; Molecular Dynamics; Free Energy
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