Author: Muhammad, Ijaz; Rahman, Noor; Gul-e-Nayab; Niaz, Sadaf; Basharat, Zarrin; Rastrelli, Luca; Jayanthi, Sivaraman; Efferth, Thomas; Khan, Haroon
Title: Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants Cord-id: d0vt8mba Document date: 2021_4_16
ID: d0vt8mba
Snippet: BACKGROUND: COVID-19, declared a pandemic in March 2020 by the World Health Organization is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The virus has already killed more than 2.3 million people worldwide. OBJECT: The principal intent of this work was to investigate lead compounds by screening natural product library (NPASS) for possible treatment of COVID-19. METHODS: Pharmacophore features were used to screen a large database to get a small dataset for structure-base
Document: BACKGROUND: COVID-19, declared a pandemic in March 2020 by the World Health Organization is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The virus has already killed more than 2.3 million people worldwide. OBJECT: The principal intent of this work was to investigate lead compounds by screening natural product library (NPASS) for possible treatment of COVID-19. METHODS: Pharmacophore features were used to screen a large database to get a small dataset for structure-based virtual screening of natural product compounds. In the structure-based screening, molecular docking was performed to find a potent inhibitor molecule against the main protease (M(pro)) of SARS-CoV-2 (PDB ID: 6Y7M). The predicted lead compound was further subjected to Molecular Dynamics (MD) simulation to check the stability of the leads compound with the evolution of time. RESULTS: In pharmacophore-based virtual screening, 2,361 compounds were retained out of 30,927. In the structure-based screening, the lead compounds were filtered based on their docking scores. Among the 2,360 compounds, 12 lead compounds were selected based on their docking score. Kazinol T with NPASS ID: NPC474104 showed the highest docking score of -14.355 and passed criteria of Lipinski’s drug-like parameters. Monitoring ADMET properties, Kazinol T showed its safety for consumption. Docking of Kazinol T with two Asian mutants (R60C and I152V) showed variations in binding and energy parameters. Normal mode analysis for ligand-bound and unbound form of protease along with its mutants, revealed displacement and correlation parameters for C-alpha atoms. MD simulation results showed that all ligand-protein complexes remained intact and stable in a dynamic environment with negative Gibbs free energy. CONCLUSIONS: The natural product Kazinol T was a predicted lead compound against the main protease of SARS-CoV-2 and will be the possible treatment for COVID-19.
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