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Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition
The COVID-19 pandemic has caused millions of fatalities since 2019. Despite the availability of vaccines for this disease, new strains are causing rapid ailment and are a continuous threat to vaccine efficacy. Here, molecular docking and simulations identify strong inhibitors of the allosteric site...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8746673/ https://www.ncbi.nlm.nih.gov/pubmed/35011458 http://dx.doi.org/10.3390/molecules27010223 |
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author | Faisal, Shah Badshah, Syed Lal Kubra, Bibi Sharaf, Mohamed Emwas, Abdul-Hamid Jaremko, Mariusz Abdalla, Mohnad |
author_facet | Faisal, Shah Badshah, Syed Lal Kubra, Bibi Sharaf, Mohamed Emwas, Abdul-Hamid Jaremko, Mariusz Abdalla, Mohnad |
author_sort | Faisal, Shah |
collection | PubMed |
description | The COVID-19 pandemic has caused millions of fatalities since 2019. Despite the availability of vaccines for this disease, new strains are causing rapid ailment and are a continuous threat to vaccine efficacy. Here, molecular docking and simulations identify strong inhibitors of the allosteric site of the SARS-CoV-2 virus RNA dependent RNA polymerase (RdRp). More than one hundred different flavonoids were docked with the SARS-CoV-2 RdRp allosteric site through computational screening. The three top hits were Naringoside, Myricetin and Aureusidin 4,6-diglucoside. Simulation analyses confirmed that they are in constant contact during the simulation time course and have strong association with the enzyme’s allosteric site. Absorption, distribution, metabolism, excretion and toxicity (ADMET) data provided medicinal information of these top three hits. They had good human intestinal absorption (HIA) concentrations and were non-toxic. Due to high mutation rates in the active sites of the viral enzyme, these new allosteric site inhibitors offer opportunities to drug SARS-CoV-2 RdRp. These results provide new information for the design of novel allosteric inhibitors against SARS-CoV-2 RdRp. |
format | Online Article Text |
id | pubmed-8746673 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87466732022-01-11 Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition Faisal, Shah Badshah, Syed Lal Kubra, Bibi Sharaf, Mohamed Emwas, Abdul-Hamid Jaremko, Mariusz Abdalla, Mohnad Molecules Article The COVID-19 pandemic has caused millions of fatalities since 2019. Despite the availability of vaccines for this disease, new strains are causing rapid ailment and are a continuous threat to vaccine efficacy. Here, molecular docking and simulations identify strong inhibitors of the allosteric site of the SARS-CoV-2 virus RNA dependent RNA polymerase (RdRp). More than one hundred different flavonoids were docked with the SARS-CoV-2 RdRp allosteric site through computational screening. The three top hits were Naringoside, Myricetin and Aureusidin 4,6-diglucoside. Simulation analyses confirmed that they are in constant contact during the simulation time course and have strong association with the enzyme’s allosteric site. Absorption, distribution, metabolism, excretion and toxicity (ADMET) data provided medicinal information of these top three hits. They had good human intestinal absorption (HIA) concentrations and were non-toxic. Due to high mutation rates in the active sites of the viral enzyme, these new allosteric site inhibitors offer opportunities to drug SARS-CoV-2 RdRp. These results provide new information for the design of novel allosteric inhibitors against SARS-CoV-2 RdRp. MDPI 2021-12-30 /pmc/articles/PMC8746673/ /pubmed/35011458 http://dx.doi.org/10.3390/molecules27010223 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Faisal, Shah Badshah, Syed Lal Kubra, Bibi Sharaf, Mohamed Emwas, Abdul-Hamid Jaremko, Mariusz Abdalla, Mohnad Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition |
title | Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition |
title_full | Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition |
title_fullStr | Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition |
title_full_unstemmed | Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition |
title_short | Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition |
title_sort | computational study of sars-cov-2 rna dependent rna polymerase allosteric site inhibition |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8746673/ https://www.ncbi.nlm.nih.gov/pubmed/35011458 http://dx.doi.org/10.3390/molecules27010223 |
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