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A multilevel approach for screening natural compounds as an antiviral agent for COVID-19
The COVID-19 has a worldwide spread, which has prompted concerted efforts to find successful drug treatments. Drug design focused on finding antiviral therapeutic agents from plant-derived compounds which may disrupt the attachment of SARS-CoV-2 to host cells is with a pivotal need and role in the l...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090871/ https://www.ncbi.nlm.nih.gov/pubmed/35576744 http://dx.doi.org/10.1016/j.compbiolchem.2022.107694 |
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author | Vasighi, Mahdi Romanova, Julia Nedyalkova, Miroslava |
author_facet | Vasighi, Mahdi Romanova, Julia Nedyalkova, Miroslava |
author_sort | Vasighi, Mahdi |
collection | PubMed |
description | The COVID-19 has a worldwide spread, which has prompted concerted efforts to find successful drug treatments. Drug design focused on finding antiviral therapeutic agents from plant-derived compounds which may disrupt the attachment of SARS-CoV-2 to host cells is with a pivotal need and role in the last year. Herein, we provide an approach based on drug design methods combined with machine learning approaches to classify and discover inhibitors for COVID-19 from natural products. The spike receptor-binding domain (RBD) was docked with database of 125 ligands. The docking protocol based on several steps was performed within Autodock Vina to identify the high-affinity binding mode and to reveal more insights into interaction between the phytochemicals and the RBD domain. A protein-ligand interaction analyzer has been developed. The drug-likeness properties of explored inhibitors are analyzed in the frame of exploratory data analyses. The developed computational protocol yielded a comprehensive pipeline for predicting the inhibitors to prevent the entry RBD region. |
format | Online Article Text |
id | pubmed-9090871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90908712022-05-11 A multilevel approach for screening natural compounds as an antiviral agent for COVID-19 Vasighi, Mahdi Romanova, Julia Nedyalkova, Miroslava Comput Biol Chem Article The COVID-19 has a worldwide spread, which has prompted concerted efforts to find successful drug treatments. Drug design focused on finding antiviral therapeutic agents from plant-derived compounds which may disrupt the attachment of SARS-CoV-2 to host cells is with a pivotal need and role in the last year. Herein, we provide an approach based on drug design methods combined with machine learning approaches to classify and discover inhibitors for COVID-19 from natural products. The spike receptor-binding domain (RBD) was docked with database of 125 ligands. The docking protocol based on several steps was performed within Autodock Vina to identify the high-affinity binding mode and to reveal more insights into interaction between the phytochemicals and the RBD domain. A protein-ligand interaction analyzer has been developed. The drug-likeness properties of explored inhibitors are analyzed in the frame of exploratory data analyses. The developed computational protocol yielded a comprehensive pipeline for predicting the inhibitors to prevent the entry RBD region. Published by Elsevier Ltd. 2022-06 2022-05-11 /pmc/articles/PMC9090871/ /pubmed/35576744 http://dx.doi.org/10.1016/j.compbiolchem.2022.107694 Text en © 2022 Published by Elsevier Ltd. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Vasighi, Mahdi Romanova, Julia Nedyalkova, Miroslava A multilevel approach for screening natural compounds as an antiviral agent for COVID-19 |
title | A multilevel approach for screening natural compounds as an antiviral agent for COVID-19 |
title_full | A multilevel approach for screening natural compounds as an antiviral agent for COVID-19 |
title_fullStr | A multilevel approach for screening natural compounds as an antiviral agent for COVID-19 |
title_full_unstemmed | A multilevel approach for screening natural compounds as an antiviral agent for COVID-19 |
title_short | A multilevel approach for screening natural compounds as an antiviral agent for COVID-19 |
title_sort | multilevel approach for screening natural compounds as an antiviral agent for covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090871/ https://www.ncbi.nlm.nih.gov/pubmed/35576744 http://dx.doi.org/10.1016/j.compbiolchem.2022.107694 |
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