Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective

Detalhes bibliográficos
Autor(a) principal: Jesus, João Paulo Almirão de
Data de Publicação: 2021
Outros Autores: Assis, Letícia Cristina, Castro, Alexandre Alves de, Cunha, Elaine Fontes Ferreira da, Nepovimova, Eugenie, Kuca, Kamil, Ramalho, Teodorico de Castro, La Porta, Felipe de Almeida
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/48827
Resumo: Understanding the effects of metabolism on the rational design of novel and more effective drugs is still a considerable challenge. To the best of our knowledge, there are no entirely computational strategies that make it possible to predict these effects. From this perspective, the development of such methodologies could contribute to significantly reduce the side effects of medicines, leading to the emergence of more effective and safer drugs. Thereby, in this study, our strategy is based on simulating the electron ionization mass spectrometry (EI-MS) fragmentation of the drug molecules and combined with molecular docking and ADMET models in two different situations. In the first model, the drug is docked without considering the possible metabolic effects. In the second model, each of the intermediates from the EI-MS results is docked, and metabolism occurs before the drug accesses the biological target. As a proof of concept, in this work, we investigate the main antiviral drugs used in clinical research to treat COVID-19. As a result, our strategy made it possible to assess the biological activity and toxicity of all potential by-products. We believed that our findings provide new chemical insights that can benefit the rational development of novel drugs in the future.
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spelling Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspectiveComputational chemistryViral infectionUnderstanding the effects of metabolism on the rational design of novel and more effective drugs is still a considerable challenge. To the best of our knowledge, there are no entirely computational strategies that make it possible to predict these effects. From this perspective, the development of such methodologies could contribute to significantly reduce the side effects of medicines, leading to the emergence of more effective and safer drugs. Thereby, in this study, our strategy is based on simulating the electron ionization mass spectrometry (EI-MS) fragmentation of the drug molecules and combined with molecular docking and ADMET models in two different situations. In the first model, the drug is docked without considering the possible metabolic effects. In the second model, each of the intermediates from the EI-MS results is docked, and metabolism occurs before the drug accesses the biological target. As a proof of concept, in this work, we investigate the main antiviral drugs used in clinical research to treat COVID-19. As a result, our strategy made it possible to assess the biological activity and toxicity of all potential by-products. We believed that our findings provide new chemical insights that can benefit the rational development of novel drugs in the future.Springer2022-01-13T02:00:13Z2022-01-13T02:00:13Z2021-10-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfJESUS, J. P. A. de et al. Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective. Scientific Reports, [S.l.], v. 11, Oct. 2021. DOI: 10.1038/s41598-021-99451-1.http://repositorio.ufla.br/jspui/handle/1/48827Scientific Reportsreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessJesus, João Paulo Almirão deAssis, Letícia CristinaCastro, Alexandre Alves deCunha, Elaine Fontes Ferreira daNepovimova, EugenieKuca, KamilRamalho, Teodorico de CastroLa Porta, Felipe de Almeidaeng2022-01-13T02:00:14Zoai:localhost:1/48827Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2022-01-13T02:00:14Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective
title Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective
spellingShingle Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective
Jesus, João Paulo Almirão de
Computational chemistry
Viral infection
title_short Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective
title_full Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective
title_fullStr Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective
title_full_unstemmed Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective
title_sort Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective
author Jesus, João Paulo Almirão de
author_facet Jesus, João Paulo Almirão de
Assis, Letícia Cristina
Castro, Alexandre Alves de
Cunha, Elaine Fontes Ferreira da
Nepovimova, Eugenie
Kuca, Kamil
Ramalho, Teodorico de Castro
La Porta, Felipe de Almeida
author_role author
author2 Assis, Letícia Cristina
Castro, Alexandre Alves de
Cunha, Elaine Fontes Ferreira da
Nepovimova, Eugenie
Kuca, Kamil
Ramalho, Teodorico de Castro
La Porta, Felipe de Almeida
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Jesus, João Paulo Almirão de
Assis, Letícia Cristina
Castro, Alexandre Alves de
Cunha, Elaine Fontes Ferreira da
Nepovimova, Eugenie
Kuca, Kamil
Ramalho, Teodorico de Castro
La Porta, Felipe de Almeida
dc.subject.por.fl_str_mv Computational chemistry
Viral infection
topic Computational chemistry
Viral infection
description Understanding the effects of metabolism on the rational design of novel and more effective drugs is still a considerable challenge. To the best of our knowledge, there are no entirely computational strategies that make it possible to predict these effects. From this perspective, the development of such methodologies could contribute to significantly reduce the side effects of medicines, leading to the emergence of more effective and safer drugs. Thereby, in this study, our strategy is based on simulating the electron ionization mass spectrometry (EI-MS) fragmentation of the drug molecules and combined with molecular docking and ADMET models in two different situations. In the first model, the drug is docked without considering the possible metabolic effects. In the second model, each of the intermediates from the EI-MS results is docked, and metabolism occurs before the drug accesses the biological target. As a proof of concept, in this work, we investigate the main antiviral drugs used in clinical research to treat COVID-19. As a result, our strategy made it possible to assess the biological activity and toxicity of all potential by-products. We believed that our findings provide new chemical insights that can benefit the rational development of novel drugs in the future.
publishDate 2021
dc.date.none.fl_str_mv 2021-10-07
2022-01-13T02:00:13Z
2022-01-13T02:00:13Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv JESUS, J. P. A. de et al. Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective. Scientific Reports, [S.l.], v. 11, Oct. 2021. DOI: 10.1038/s41598-021-99451-1.
http://repositorio.ufla.br/jspui/handle/1/48827
identifier_str_mv JESUS, J. P. A. de et al. Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective. Scientific Reports, [S.l.], v. 11, Oct. 2021. DOI: 10.1038/s41598-021-99451-1.
url http://repositorio.ufla.br/jspui/handle/1/48827
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv Scientific Reports
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
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reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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