Double focus in the MIA-QSAR modeling of anti-influenza properties of 2-iminobenzimidazolines: pharmacology and toxicology

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorPereira, I. V.-
Autor(es): dc.creatorFreitas, M. P. de-
Data de aceite: dc.date.accessioned2026-02-09T11:48:07Z-
Data de disponibilização: dc.date.available2026-02-09T11:48:07Z-
Data de envio: dc.date.issued2022-01-05-
Data de envio: dc.date.issued2022-01-05-
Data de envio: dc.date.issued2020-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/48797-
Fonte completa do material: dc.identifierhttps://www.tandfonline.com/doi/full/10.1080/1062936X.2021.1950832-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1147767-
Descrição: dc.descriptionInfluenza affects millions of people globally and the appearance of drug-resistant strains is an ongoing problem. Therefore, this work reports the development of quantitative structure-activity relationship (QSAR) models to predict some biological properties of new 2-iminobenzimidazoline candidates for the treatment of the flu. A series of 2-iminobenzimidazoline derivatives with experimentally available values for cytotoxicity (pCC50) and anti-influenza activity (pIC50) was used for multivariate image analysis applied to QSAR (MIA-QSAR). The models were vigorously validated according to the best practices in QSAR and the chemical features responsible for the response variables were analysed based on MIA-plots, which assess the PLS regression coefficients and variable importance in projection scores. MIA descriptors encoding atomic properties (van der Waals radius and electronegativity) were capable of properly modelling the pCC50 and pIC50 data. The internally and externally validated models were used to predict the selectivity indexes (SI = pCC50/pIC50) of unprecedented analogues, which were designed upon analysis of the MIA-plots that show the substituent groups most affecting the biological data and by the combination of substructures of selected molecules. At least three promising anti-influenza candidates could be proposed from the predictive MIA-QSAR models.-
Idioma: dc.languageen-
Publicador: dc.publisherTaylor & Francis-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceSAR and QSAR in Environmental Research-
Palavras-chave: dc.subjectMIA-QSAR-
Palavras-chave: dc.subjectInfluenza-
Palavras-chave: dc.subject2-iminobenzimidazolines-
Palavras-chave: dc.subjectAntiviral activity-
Palavras-chave: dc.subjectCytotoxicity-
Título: dc.titleDouble focus in the MIA-QSAR modeling of anti-influenza properties of 2-iminobenzimidazolines: pharmacology and toxicology-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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