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Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2

SARS-CoV-2 caused the current COVID-19 pandemic and there is an urgent need to explore effective therapeutics that can inhibit enzymes that are imperative in virus reproduction. To this end, we computationally investigated the MPD3 phytochemical database along with the pool of reported natural antiv...

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Autores principales: Muhseen, Ziyad Tariq, Hameed, Alaa R., Al-Hasani, Halah M. H., Ahmad, Sajjad, Li, Guanglin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865386/
https://www.ncbi.nlm.nih.gov/pubmed/33525411
http://dx.doi.org/10.3390/molecules26030674
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author Muhseen, Ziyad Tariq
Hameed, Alaa R.
Al-Hasani, Halah M. H.
Ahmad, Sajjad
Li, Guanglin
author_facet Muhseen, Ziyad Tariq
Hameed, Alaa R.
Al-Hasani, Halah M. H.
Ahmad, Sajjad
Li, Guanglin
author_sort Muhseen, Ziyad Tariq
collection PubMed
description SARS-CoV-2 caused the current COVID-19 pandemic and there is an urgent need to explore effective therapeutics that can inhibit enzymes that are imperative in virus reproduction. To this end, we computationally investigated the MPD3 phytochemical database along with the pool of reported natural antiviral compounds with potential to be used as anti-SARS-CoV-2. The docking results demonstrated glycyrrhizin followed by azadirachtanin, mycophenolic acid, kushenol-w and 6-azauridine, as potential candidates. Glycyrrhizin depicted very stable binding mode to the active pocket of the Mpro (binding energy, −8.7 kcal/mol), PLpro (binding energy, −7.9 kcal/mol), and Nucleocapsid (binding energy, −7.9 kcal/mol) enzymes. This compound showed binding with several key residues that are critical to natural substrate binding and functionality to all the receptors. To test docking prediction, the compound with each receptor was subjected to molecular dynamics simulation to characterize the molecule stability and decipher its possible mechanism of binding. Each complex concludes that the receptor dynamics are stable (Mpro (mean RMSD, 0.93 Å), PLpro (mean RMSD, 0.96 Å), and Nucleocapsid (mean RMSD, 3.48 Å)). Moreover, binding free energy analyses such as MMGB/PBSA and WaterSwap were run over selected trajectory snapshots to affirm intermolecular affinity in the complexes. Glycyrrhizin was rescored to form strong affinity complexes with the virus enzymes: Mpro (MMGBSA, −24.42 kcal/mol and MMPBSA, −10.80 kcal/mol), PLpro (MMGBSA, −48.69 kcal/mol and MMPBSA, −38.17 kcal/mol) and Nucleocapsid (MMGBSA, −30.05 kcal/mol and MMPBSA, −25.95 kcal/mol), were dominated mainly by vigorous van der Waals energy. Further affirmation was achieved by WaterSwap absolute binding free energy that concluded all the complexes in good equilibrium and stability (Mpro (mean, −22.44 kcal/mol), PLpro (mean, −25.46 kcal/mol), and Nucleocapsid (mean, −23.30 kcal/mol)). These promising findings substantially advance our understanding of how natural compounds could be shaped to counter SARS-CoV-2 infection.
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spelling pubmed-78653862021-02-07 Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2 Muhseen, Ziyad Tariq Hameed, Alaa R. Al-Hasani, Halah M. H. Ahmad, Sajjad Li, Guanglin Molecules Article SARS-CoV-2 caused the current COVID-19 pandemic and there is an urgent need to explore effective therapeutics that can inhibit enzymes that are imperative in virus reproduction. To this end, we computationally investigated the MPD3 phytochemical database along with the pool of reported natural antiviral compounds with potential to be used as anti-SARS-CoV-2. The docking results demonstrated glycyrrhizin followed by azadirachtanin, mycophenolic acid, kushenol-w and 6-azauridine, as potential candidates. Glycyrrhizin depicted very stable binding mode to the active pocket of the Mpro (binding energy, −8.7 kcal/mol), PLpro (binding energy, −7.9 kcal/mol), and Nucleocapsid (binding energy, −7.9 kcal/mol) enzymes. This compound showed binding with several key residues that are critical to natural substrate binding and functionality to all the receptors. To test docking prediction, the compound with each receptor was subjected to molecular dynamics simulation to characterize the molecule stability and decipher its possible mechanism of binding. Each complex concludes that the receptor dynamics are stable (Mpro (mean RMSD, 0.93 Å), PLpro (mean RMSD, 0.96 Å), and Nucleocapsid (mean RMSD, 3.48 Å)). Moreover, binding free energy analyses such as MMGB/PBSA and WaterSwap were run over selected trajectory snapshots to affirm intermolecular affinity in the complexes. Glycyrrhizin was rescored to form strong affinity complexes with the virus enzymes: Mpro (MMGBSA, −24.42 kcal/mol and MMPBSA, −10.80 kcal/mol), PLpro (MMGBSA, −48.69 kcal/mol and MMPBSA, −38.17 kcal/mol) and Nucleocapsid (MMGBSA, −30.05 kcal/mol and MMPBSA, −25.95 kcal/mol), were dominated mainly by vigorous van der Waals energy. Further affirmation was achieved by WaterSwap absolute binding free energy that concluded all the complexes in good equilibrium and stability (Mpro (mean, −22.44 kcal/mol), PLpro (mean, −25.46 kcal/mol), and Nucleocapsid (mean, −23.30 kcal/mol)). These promising findings substantially advance our understanding of how natural compounds could be shaped to counter SARS-CoV-2 infection. MDPI 2021-01-28 /pmc/articles/PMC7865386/ /pubmed/33525411 http://dx.doi.org/10.3390/molecules26030674 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Muhseen, Ziyad Tariq
Hameed, Alaa R.
Al-Hasani, Halah M. H.
Ahmad, Sajjad
Li, Guanglin
Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2
title Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2
title_full Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2
title_fullStr Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2
title_full_unstemmed Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2
title_short Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2
title_sort computational determination of potential multiprotein targeting natural compounds for rational drug design against sars-cov-2
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865386/
https://www.ncbi.nlm.nih.gov/pubmed/33525411
http://dx.doi.org/10.3390/molecules26030674
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