In Silico Prediction of Cytochrome P450-Drug Interaction: QSARs for CYP3A4 and CYP2C9.
Int J Mol Sci
; 17(6)2016 Jun 09.
Article
em En
| MEDLINE
| ID: mdl-27294921
ABSTRACT
Cytochromes P450 (CYP) are the main actors in the oxidation of xenobiotics and play a crucial role in drug safety, persistence, bioactivation, and drug-drug/food-drug interaction. This work aims to develop Quantitative Structure-Activity Relationship (QSAR) models to predict the drug interaction with two of the most important CYP isoforms, namely 2C9 and 3A4. The presented models are calibrated on 9122 drug-like compounds, using three different modelling approaches and two types of molecular description (classical molecular descriptors and binary fingerprints). For each isoform, three classification models are presented, based on a different approach and with different advantages (1) a very simple and interpretable classification tree; (2) a local (k-Nearest Neighbor) model based classical descriptors and; (3) a model based on a recently proposed local classifier (N-Nearest Neighbor) on binary fingerprints. The salient features of the work are (1) the thorough model validation and the applicability domain assessment; (2) the descriptor interpretation, which highlighted the crucial aspects of P450-drug interaction; and (3) the consensus aggregation of models, which largely increased the prediction accuracy.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Relação Quantitativa Estrutura-Atividade
/
Citocromo P-450 CYP3A
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Citocromo P-450 CYP2C9
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Inibidores do Citocromo P-450 CYP2C9
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Inibidores do Citocromo P-450 CYP3A
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Int J Mol Sci
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Itália