Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Anais da Academia Brasileira de Ciências (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000700703 |
Resumo: | Abstract Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are the latest class of drugs approved to treat type 2 DM (T2DM). Although adverse effects are often caused by a metabolite rather than the drug itself, only the safety assessment of disproportionate drug metabolites is usually performed, which is of particular concern for drugs of chronic use, such as SGLT2i. Bearing this in mind, in silico tools are efficient strategies to reveal the risk assessment of metabolites, being endorsed by many regulatory agencies. Thereby, the goal of this study was to apply in silico methods to provide the metabolites toxicity assessment of the SGLT2i. Toxicological assessment from SGLT2i metabolites retrieved from the literature was estimated using the structure and/or statistical-based alert implemented in DataWarrior and ADMET predictorTM softwares. The drugs and their metabolites displayed no mutagenic, tumorigenic or cardiotoxic risks. Still, M1-2 and M3-1 were recognized as potential hepatotoxic compounds and M1-2, M1-3, M3-1, M3-2, M3-3 and M4-3, were estimated to have very toxic LD50 values in rats. All SGLT2i and the metabolites M3-4, M4-1 and M4-2, were predicted to have reproductive toxicity. These results support the awareness that metabolites may be potential mediators of drug-induced toxicities of the therapeutic agents. |
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Anais da Academia Brasileira de Ciências (Online) |
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Toxicological assessment of SGLT2 inhibitors metabolites using in silico approachdiabetesin silico toxicologymetabolismSGLT2 inhibitorsSGLT2i metabolitesAbstract Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are the latest class of drugs approved to treat type 2 DM (T2DM). Although adverse effects are often caused by a metabolite rather than the drug itself, only the safety assessment of disproportionate drug metabolites is usually performed, which is of particular concern for drugs of chronic use, such as SGLT2i. Bearing this in mind, in silico tools are efficient strategies to reveal the risk assessment of metabolites, being endorsed by many regulatory agencies. Thereby, the goal of this study was to apply in silico methods to provide the metabolites toxicity assessment of the SGLT2i. Toxicological assessment from SGLT2i metabolites retrieved from the literature was estimated using the structure and/or statistical-based alert implemented in DataWarrior and ADMET predictorTM softwares. The drugs and their metabolites displayed no mutagenic, tumorigenic or cardiotoxic risks. Still, M1-2 and M3-1 were recognized as potential hepatotoxic compounds and M1-2, M1-3, M3-1, M3-2, M3-3 and M4-3, were estimated to have very toxic LD50 values in rats. All SGLT2i and the metabolites M3-4, M4-1 and M4-2, were predicted to have reproductive toxicity. These results support the awareness that metabolites may be potential mediators of drug-induced toxicities of the therapeutic agents.Academia Brasileira de Ciências2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000700703Anais da Academia Brasileira de Ciências v.94 suppl.3 2022reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202220211287info:eu-repo/semantics/openAccessJESUS,JÉSSICA B. DECONCEIÇÃO,RAISSA A. DAMACHADO,THAYNÁ R.BARBOSA,MARIA L.C.DOMINGOS,THAISA F.S.CABRAL,LUCIO M.RODRIGUES,CARLOS R.ABRAHIM-VIEIRA,BÁRBARASOUZA,ALESSANDRA M.T. DEeng2022-09-28T00:00:00Zoai:scielo:S0001-37652022000700703Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2022-09-28T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach |
title |
Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach |
spellingShingle |
Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach JESUS,JÉSSICA B. DE diabetes in silico toxicology metabolism SGLT2 inhibitors SGLT2i metabolites |
title_short |
Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach |
title_full |
Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach |
title_fullStr |
Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach |
title_full_unstemmed |
Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach |
title_sort |
Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach |
author |
JESUS,JÉSSICA B. DE |
author_facet |
JESUS,JÉSSICA B. DE CONCEIÇÃO,RAISSA A. DA MACHADO,THAYNÁ R. BARBOSA,MARIA L.C. DOMINGOS,THAISA F.S. CABRAL,LUCIO M. RODRIGUES,CARLOS R. ABRAHIM-VIEIRA,BÁRBARA SOUZA,ALESSANDRA M.T. DE |
author_role |
author |
author2 |
CONCEIÇÃO,RAISSA A. DA MACHADO,THAYNÁ R. BARBOSA,MARIA L.C. DOMINGOS,THAISA F.S. CABRAL,LUCIO M. RODRIGUES,CARLOS R. ABRAHIM-VIEIRA,BÁRBARA SOUZA,ALESSANDRA M.T. DE |
author2_role |
author author author author author author author author |
dc.contributor.author.fl_str_mv |
JESUS,JÉSSICA B. DE CONCEIÇÃO,RAISSA A. DA MACHADO,THAYNÁ R. BARBOSA,MARIA L.C. DOMINGOS,THAISA F.S. CABRAL,LUCIO M. RODRIGUES,CARLOS R. ABRAHIM-VIEIRA,BÁRBARA SOUZA,ALESSANDRA M.T. DE |
dc.subject.por.fl_str_mv |
diabetes in silico toxicology metabolism SGLT2 inhibitors SGLT2i metabolites |
topic |
diabetes in silico toxicology metabolism SGLT2 inhibitors SGLT2i metabolites |
description |
Abstract Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are the latest class of drugs approved to treat type 2 DM (T2DM). Although adverse effects are often caused by a metabolite rather than the drug itself, only the safety assessment of disproportionate drug metabolites is usually performed, which is of particular concern for drugs of chronic use, such as SGLT2i. Bearing this in mind, in silico tools are efficient strategies to reveal the risk assessment of metabolites, being endorsed by many regulatory agencies. Thereby, the goal of this study was to apply in silico methods to provide the metabolites toxicity assessment of the SGLT2i. Toxicological assessment from SGLT2i metabolites retrieved from the literature was estimated using the structure and/or statistical-based alert implemented in DataWarrior and ADMET predictorTM softwares. The drugs and their metabolites displayed no mutagenic, tumorigenic or cardiotoxic risks. Still, M1-2 and M3-1 were recognized as potential hepatotoxic compounds and M1-2, M1-3, M3-1, M3-2, M3-3 and M4-3, were estimated to have very toxic LD50 values in rats. All SGLT2i and the metabolites M3-4, M4-1 and M4-2, were predicted to have reproductive toxicity. These results support the awareness that metabolites may be potential mediators of drug-induced toxicities of the therapeutic agents. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000700703 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000700703 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765202220211287 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
dc.source.none.fl_str_mv |
Anais da Academia Brasileira de Ciências v.94 suppl.3 2022 reponame:Anais da Academia Brasileira de Ciências (Online) instname:Academia Brasileira de Ciências (ABC) instacron:ABC |
instname_str |
Academia Brasileira de Ciências (ABC) |
instacron_str |
ABC |
institution |
ABC |
reponame_str |
Anais da Academia Brasileira de Ciências (Online) |
collection |
Anais da Academia Brasileira de Ciências (Online) |
repository.name.fl_str_mv |
Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC) |
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||aabc@abc.org.br |
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1754302872803082240 |