In Silico Prediction of Cytochrome P450-Drug Interaction: QSARs for CYP3A4 and CYP2C9Reportar como inadecuado




In Silico Prediction of Cytochrome P450-Drug Interaction: QSARs for CYP3A4 and CYP2C9 - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

Department of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, 20126 Milano, Italy



These authors contributed equally to the work.





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Academic Editor: Jesus Vicente De Julián Ortiz

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. View Full-Text

Keywords: cytochrome P450; QSAR; CYP2C9; CYP3A4; in silico; ADMET cytochrome P450; QSAR; CYP2C9; CYP3A4; in silico; ADMET





Autor: Serena Nembri †, Francesca Grisoni †, Viviana Consonni and Roberto Todeschini *

Fuente: http://mdpi.com/



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