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Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective.
de Jesus, João Paulo Almirão; Assis, Letícia Cristina; de Castro, Alexandre Alves; da Cunha, Elaine Fontes Ferreira; Nepovimova, Eugenie; Kuca, Kamil; de Castro Ramalho, Teodorico; de Almeida La Porta, Felipe.
  • de Jesus JPA; Laboratory of Nanotechnology and Computational Chemistry, Federal Technological University of Paraná, Avenida dos Pioneiros 3131, Londrina, Paraná, CEP 86036-370, Brazil.
  • Assis LC; Department of Chemistry, Federal University of Lavras, Lavras, Minas Gerais, CEP 37200-000, Brazil.
  • de Castro AA; Department of Chemistry, Federal University of Lavras, Lavras, Minas Gerais, CEP 37200-000, Brazil.
  • da Cunha EFF; Department of Chemistry, Federal University of Lavras, Lavras, Minas Gerais, CEP 37200-000, Brazil.
  • Nepovimova E; Department of Chemistry, Faculty of Science, University of Hradec Kralove, Rokitanskeho 62, 500 03, Hradec Králové, Czech Republic.
  • Kuca K; Department of Chemistry, Faculty of Science, University of Hradec Kralove, Rokitanskeho 62, 500 03, Hradec Králové, Czech Republic. kamil.kuca@uhk.cz.
  • de Castro Ramalho T; Department of Chemistry, Federal University of Lavras, Lavras, Minas Gerais, CEP 37200-000, Brazil.
  • de Almeida La Porta F; Department of Chemistry, Faculty of Science, University of Hradec Kralove, Rokitanskeho 62, 500 03, Hradec Králové, Czech Republic.
Sci Rep ; 11(1): 19998, 2021 10 07.
Article in English | MEDLINE | ID: covidwho-1462031
ABSTRACT
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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Drug Discovery / SARS-CoV-2 / COVID-19 Type of study: Prognostic study Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-99451-1

Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Drug Discovery / SARS-CoV-2 / COVID-19 Type of study: Prognostic study Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-99451-1