A topological substructural approach for the prediction of P-glycoprotein substrates.
J Pharm Sci
; 95(3): 589-606, 2006 Mar.
Article
em En
| MEDLINE
| ID: mdl-16432877
A topological substructural molecular design approach (TOPS-MODE) has been used to predict whether a given compound is a P-glycoprotein (P-gp) substrate or not. A linear discriminant model was developed to classify a data set of 163 compounds as substrates or nonsubstrates (91 substrates and 72 nonsubstrates). The final model fit the data with sensitivity of 82.42% and specificity of 79.17%, for a final accuracy of 80.98%. The model was validated through the use of an external validation set (40 compounds, 22 substrates and 18 nonsubstrates) with a 77.50% of prediction accuracy; fivefold full cross-validation (removing 40 compounds in each cycle, 80.50% of good prediction) and the prediction of an external test set of marketed drugs (35 compounds, 71.43% of good prediction). This methodology evidenced that the standard bond distance, the polarizability and the Gasteiger-Marsilli atomic charge affect the interaction with the P-gp; suggesting the capacity of the TOPS-MODE descriptors to estimate the P-gp substrates for new drug candidates. The potentiality of the TOPS-MODE approach was assessed with a family of compounds not covered by the original training set (6-fluoroquinolones), and the final prediction had a 77.7% of accuracy. Finally, the positive and negative substructural contributions to the classification of 6-fluoroquinolones, as P-gp substrates, were identified; evidencing the possibilities of the present approach in the lead generation and optimization processes.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Preparações Farmacêuticas
/
Membro 1 da Subfamília B de Cassetes de Ligação de ATP
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Modelos Biológicos
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Revista:
J Pharm Sci
Ano de publicação:
2006
Tipo de documento:
Article
País de afiliação:
Cuba
País de publicação:
Estados Unidos