Application of parallel artificial membrane permeability assay technique and chemometric modeling for blood-brain barrier permeability prediction of protein kinase inhibitors.
Future Med Chem
; 16(9): 873-885, 2024.
Article
em En
| MEDLINE
| ID: mdl-38639375
ABSTRACT
Aim:
This study aims to investigate the passive diffusion of protein kinase inhibitors through the blood-brain barrier (BBB) and to develop a model for their permeability prediction. Materials &methods:
We used the parallel artificial membrane permeability assay to obtain logPe values of each of 34 compounds and calculated descriptors for these structures to perform quantitative structure-property relationship modeling, creating different regression models.Results:
The logPe values have been calculated for all 34 compounds. Support vector machine regression was considered the most reliable, and CATS2D_09_DA, CATS2D_04_AA, B04[N-S] and F07[C-N] descriptors were identified as the most influential to passive BBB permeability.Conclusion:
The quantitative structure-property relationship-support vector machine regression model that has been generated can serve as an efficient method for preliminary screening of BBB permeability of new analogs.
[Box see text].
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Barreira Hematoencefálica
/
Relação Quantitativa Estrutura-Atividade
/
Inibidores de Proteínas Quinases
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Máquina de Vetores de Suporte
/
Membranas Artificiais
Limite:
Humans
Idioma:
En
Revista:
Future Med Chem
Ano de publicação:
2024
Tipo de documento:
Article