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Prevention of SARS-CoV-2 Proliferation with a Novel and Potent Main Protease Inhibitor by Docking, ADMET, MM-PBSA, and Molecular Dynamics Simulation
Journal of Computational Biophysics and Chemistry ; 20(3):305-322, 2021.
Article in English | Web of Science | ID: covidwho-1582945
ABSTRACT
COVID-19 is the last disease caused by SARS-CoV-2 associated with a severe immune response and lung damage. The main protease (M-pro) has a vital role in SARS-CoV-2 proliferation. Moreover, humans lack homologous M-pro, which makes the M-pro a suitable drug target for the development of SARS-CoV-2 drugs. The purchasable L5000 library (Selleckchem Inc) includes 99,040 compounds that were used for virtual screening. After molecular docking and ADME studies, we selected a compound (WAY-604395) with a potent binding affinity to the M-pro active site and acceptable ADME properties compared to the reference drug (nelfinavir). Molecular dynamics (MD) simulation outcomes have proved that the M-pro-WAY604395 complex possesses a considerable value of flexibility, stability, compactness and binding energy. Our Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculation demonstrates that WAY-604395 is more potent (-272.19kcal mol-1) in comparison with nelfinavir (-173.39mol-1) against SARS-CoV-2 M-pro. In conclusion, we suggest that WAY-604395 has the potential for the treatment of SARS-CoV-2 by inhibition of the M-pro. Computational modeling was performed to investigate the binding effects of WAY-604395 on SARS-CoV-2 main protease. Through molecular docking and molecular dynamics, compound WAY-604395 was selected to inhibit Mpro. ADME analysis showed that WAY-604395 is not prohibited for human use.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Journal of Computational Biophysics and Chemistry Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Journal of Computational Biophysics and Chemistry Year: 2021 Document Type: Article