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Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19
Teicoplanin is a glycopeptide antibiotic effective against several bacterial infections, has exhibited promising therapeutic efficiency against COVID-19 in vitro, and the rationale for its use in COVID-19 is yet to be recognized. Hence, in this study a number of molecular modeling techniques were em...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300629/ https://www.ncbi.nlm.nih.gov/pubmed/34356777 http://dx.doi.org/10.3390/antibiotics10070856 |
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author | Azam, Faizul |
author_facet | Azam, Faizul |
author_sort | Azam, Faizul |
collection | PubMed |
description | Teicoplanin is a glycopeptide antibiotic effective against several bacterial infections, has exhibited promising therapeutic efficiency against COVID-19 in vitro, and the rationale for its use in COVID-19 is yet to be recognized. Hence, in this study a number of molecular modeling techniques were employed to decrypt the mechanistic insight of teicoplanin interaction with several COVID-19 drug targets. Initially, molecular docking was employed to study the teicoplanin interaction with twenty-five SARS-CoV-2 structural and non-structural proteins which was followed by molecular mechanics/generalized Born surface area (MM/GBSA) computation for binding energy predictions of top ten models from each target. Amongst all macromolecular targets, the N-terminal domain of the nucleocapsid protein displayed the strongest affinity with teicoplanin showing binding energies of −7.4 and −102.13 kcal/mol, in docking and Prime MM/GBSA, respectively. Thermodynamic stability of the teicoplanin-nucleocapsid protein was further probed by molecular dynamics simulations of protein–ligand complex as well as unbounded protein in 100 ns trajectories. Post-simulation MM-GBSA computation of 50 frames extracted from simulated trajectories estimated an average binding energy of −62.52 ± 12.22 kcal/mol. In addition, conformational state of protein in complex with docked teicoplanin displayed stable root-mean-square deviation/fluctuation. In conclusion, computational investigation of the potential targets of COVID-19 and their interaction mechanism with teicoplanin can guide the design of novel therapeutic armamentarium for the treatment of SARS-CoV-2 infection. However, additional studies are warranted to establish the clinical use or relapses, if any, of teicoplanin in the therapeutic management of COVID-19 patients. |
format | Online Article Text |
id | pubmed-8300629 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83006292021-07-24 Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 Azam, Faizul Antibiotics (Basel) Article Teicoplanin is a glycopeptide antibiotic effective against several bacterial infections, has exhibited promising therapeutic efficiency against COVID-19 in vitro, and the rationale for its use in COVID-19 is yet to be recognized. Hence, in this study a number of molecular modeling techniques were employed to decrypt the mechanistic insight of teicoplanin interaction with several COVID-19 drug targets. Initially, molecular docking was employed to study the teicoplanin interaction with twenty-five SARS-CoV-2 structural and non-structural proteins which was followed by molecular mechanics/generalized Born surface area (MM/GBSA) computation for binding energy predictions of top ten models from each target. Amongst all macromolecular targets, the N-terminal domain of the nucleocapsid protein displayed the strongest affinity with teicoplanin showing binding energies of −7.4 and −102.13 kcal/mol, in docking and Prime MM/GBSA, respectively. Thermodynamic stability of the teicoplanin-nucleocapsid protein was further probed by molecular dynamics simulations of protein–ligand complex as well as unbounded protein in 100 ns trajectories. Post-simulation MM-GBSA computation of 50 frames extracted from simulated trajectories estimated an average binding energy of −62.52 ± 12.22 kcal/mol. In addition, conformational state of protein in complex with docked teicoplanin displayed stable root-mean-square deviation/fluctuation. In conclusion, computational investigation of the potential targets of COVID-19 and their interaction mechanism with teicoplanin can guide the design of novel therapeutic armamentarium for the treatment of SARS-CoV-2 infection. However, additional studies are warranted to establish the clinical use or relapses, if any, of teicoplanin in the therapeutic management of COVID-19 patients. MDPI 2021-07-15 /pmc/articles/PMC8300629/ /pubmed/34356777 http://dx.doi.org/10.3390/antibiotics10070856 Text en © 2021 by the author. 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 Azam, Faizul Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
title | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
title_full | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
title_fullStr | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
title_full_unstemmed | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
title_short | Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19 |
title_sort | elucidation of teicoplanin interactions with drug targets related to covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300629/ https://www.ncbi.nlm.nih.gov/pubmed/34356777 http://dx.doi.org/10.3390/antibiotics10070856 |
work_keys_str_mv | AT azamfaizul elucidationofteicoplanininteractionswithdrugtargetsrelatedtocovid19 |