Prediction of ADME properties, Part 1: Classification models to predict Caco-2 cell permeability using atom-based bilinear indices

Juan A. Castillo-Garit, Yudith Cañizares-Carmenate, Yovani Marrero-Ponce, Francisco Torrens, Concepción Abad

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

8 Citas (Scopus)

Resumen

The prediction of the permeability through cultured Caco-2 cells (an often-used in vitro model for drug absorption) is carried out using theoretical models. Atom-based bilinear indices and linear discriminant analysis (LDA) are used to obtain quantitative models, which discriminate between higher absorption and moderate-poorer absorption compounds, form a database of measured P caco.2from a large data set with 157 structurally diverse compounds. We d velop two LDA models with more than 90% of accuracy for training and test set; the best model presents accuracy of 91.79% and 91.30%, respectively. The results achieved in this work compare favourably with other approaches previously published In the technical literature. The percentage of good correlation was of 80%, In the virtual screening of 241 drugs with the reported values of the percentage of human intestinal absorption (HIA). Finally, we can say that, the present "in silico" method would be a valuable tool in the drug discovery process in order to select the molecules with the greatest chance before synthesis.

Idioma originalInglés
Páginas (desde-hasta)129-138
Número de páginas10
PublicaciónAfinidad
Volumen71
N.º566
EstadoPublicada - 2014
Publicado de forma externa

Huella

Profundice en los temas de investigación de 'Prediction of ADME properties, Part 1: Classification models to predict Caco-2 cell permeability using atom-based bilinear indices'. En conjunto forman una huella única.

Citar esto