In Silico Prediction of Cytochrome P450-Drug Interaction: QSARs for CYP3A4 and CYP2C9

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.

In vitro and in silico Approaches to Study Cytochrome P450-Mediated Interactions

“…'Descriptors' are terms for the various calculated or measured properties and can be of many types (e.g., spatial, electronic, thermodynamic, conformational, topological and structural). These descriptors are 'linked-up' to generate equations or formulae to delineate structure-function activities in the CYP(s) under investigation [27][28][29].…”

Mapping of Activity through Dichotomic Scores (MADS): A new chemoinformatic approach to detect activity‐rich structural regions

“…The string length can vary depending on the amount of structural information to be encoded. Despite fingerprint‐like representations of chemicals were initially designed to enhance the efficiency of chemical database searching, they have become a reliable tool in numerous virtual screening and modelling campaigns …”

A new concept of higher-order similarity and the role of distance/similarity measures in local classification methods

“…Because of their ability to quantitatively grasp the analogy between entities, distance/similarity metrics have been playing a crucial role in many fields, such as Quantitative Structure-Activity Relationship (QSAR) [4]- [6], food authentication [7]- [9], outlier detection [10]- [13] and drug discovery [14]- [16]. This underscores the potential of introducing and studying new metrics.…”