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A Computational Approach to Explore the Interaction of Semisynthetic Nitrogenous Heterocyclic Compounds with the SARS-CoV-2 Main Protease

In the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic, numerous attempts have been made to discover new potential antiviral molecules against its causative agent, SARS-CoV-2, many of which focus on its main protease (M(pro)). We hereby used two approaches based on molecular dock...

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Autores principales: Llanes, Alejandro, Cruz, Héctor, Nguyen, Viet D., Larionov, Oleg V., Fernández, Patricia L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7824519/
https://www.ncbi.nlm.nih.gov/pubmed/33375460
http://dx.doi.org/10.3390/biom11010018
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author Llanes, Alejandro
Cruz, Héctor
Nguyen, Viet D.
Larionov, Oleg V.
Fernández, Patricia L.
author_facet Llanes, Alejandro
Cruz, Héctor
Nguyen, Viet D.
Larionov, Oleg V.
Fernández, Patricia L.
author_sort Llanes, Alejandro
collection PubMed
description In the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic, numerous attempts have been made to discover new potential antiviral molecules against its causative agent, SARS-CoV-2, many of which focus on its main protease (M(pro)). We hereby used two approaches based on molecular docking simulation to explore the interaction of four libraries of semisynthetic nitrogenous heterocyclic compounds with M(pro). Libraries L1 and L2 contain 52 synthetic derivatives of the natural compound 2-propylquinoline, whereas libraries L3 and L4 contain 65 compounds synthesized using the natural compound physostigmine as a precursor. Validation through redocking suggested that the rigid receptor and flexible receptor approaches used for docking were suitable to model the interaction of this type of compounds with the target protein, although the flexible approach seemed to provide a more realistic representation of interactions within the active site. Using empirical energy score thresholds, we selected 58 compounds from the four libraries with the most favorable energy estimates. Globally, favorable estimates were obtained for molecules with two or more substituents, putatively accommodating in three or more subsites within the M(pro) active site. Our results pave the way for further experimental evaluation of the selected compounds as potential antiviral agents against SARS-CoV-2.
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spelling pubmed-78245192021-01-24 A Computational Approach to Explore the Interaction of Semisynthetic Nitrogenous Heterocyclic Compounds with the SARS-CoV-2 Main Protease Llanes, Alejandro Cruz, Héctor Nguyen, Viet D. Larionov, Oleg V. Fernández, Patricia L. Biomolecules Article In the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic, numerous attempts have been made to discover new potential antiviral molecules against its causative agent, SARS-CoV-2, many of which focus on its main protease (M(pro)). We hereby used two approaches based on molecular docking simulation to explore the interaction of four libraries of semisynthetic nitrogenous heterocyclic compounds with M(pro). Libraries L1 and L2 contain 52 synthetic derivatives of the natural compound 2-propylquinoline, whereas libraries L3 and L4 contain 65 compounds synthesized using the natural compound physostigmine as a precursor. Validation through redocking suggested that the rigid receptor and flexible receptor approaches used for docking were suitable to model the interaction of this type of compounds with the target protein, although the flexible approach seemed to provide a more realistic representation of interactions within the active site. Using empirical energy score thresholds, we selected 58 compounds from the four libraries with the most favorable energy estimates. Globally, favorable estimates were obtained for molecules with two or more substituents, putatively accommodating in three or more subsites within the M(pro) active site. Our results pave the way for further experimental evaluation of the selected compounds as potential antiviral agents against SARS-CoV-2. MDPI 2020-12-27 /pmc/articles/PMC7824519/ /pubmed/33375460 http://dx.doi.org/10.3390/biom11010018 Text en © 2020 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
Llanes, Alejandro
Cruz, Héctor
Nguyen, Viet D.
Larionov, Oleg V.
Fernández, Patricia L.
A Computational Approach to Explore the Interaction of Semisynthetic Nitrogenous Heterocyclic Compounds with the SARS-CoV-2 Main Protease
title A Computational Approach to Explore the Interaction of Semisynthetic Nitrogenous Heterocyclic Compounds with the SARS-CoV-2 Main Protease
title_full A Computational Approach to Explore the Interaction of Semisynthetic Nitrogenous Heterocyclic Compounds with the SARS-CoV-2 Main Protease
title_fullStr A Computational Approach to Explore the Interaction of Semisynthetic Nitrogenous Heterocyclic Compounds with the SARS-CoV-2 Main Protease
title_full_unstemmed A Computational Approach to Explore the Interaction of Semisynthetic Nitrogenous Heterocyclic Compounds with the SARS-CoV-2 Main Protease
title_short A Computational Approach to Explore the Interaction of Semisynthetic Nitrogenous Heterocyclic Compounds with the SARS-CoV-2 Main Protease
title_sort computational approach to explore the interaction of semisynthetic nitrogenous heterocyclic compounds with the sars-cov-2 main protease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7824519/
https://www.ncbi.nlm.nih.gov/pubmed/33375460
http://dx.doi.org/10.3390/biom11010018
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