Predicting Drug-Induced Cholestasis with the Help of Hepatic Transporters-An in Silico Modeling Approach.

Eleni Kotsampasakou,Gerhard F Ecker

doi:10.1021/acs.jcim.6b00518

Eleni Kotsampasakou, Gerhard F Ecker

Open Access

https://doi.org/10.1021/acs.jcim.6b00518

Copy DOI

Abstract

Cholestasis represents one out of three types of drug induced liver injury (DILI), which comprises a major challenge in drug development. In this study we applied a two-class classification scheme based on k-nearest neighbors in order to predict cholestasis, using a set of 93 two-dimensional (2D) physicochemical descriptors and predictions of selected hepatic transporters’ inhibition (BSEP, BCRP, P-gp, OATP1B1, and OATP1B3). In order to assess the potential contribution of transporter inhibition, we compared whether the inclusion of the transporters’ inhibition predictions contributes to a significant increase in model performance in comparison to the plain use of the 93 2D physicochemical descriptors. Our findings were in agreement with literature findings, indicating a contribution not only from BSEP inhibition but a rather synergistic effect deriving from the whole set of transporters. The final optimal model was validated via both 10-fold cross validation and external validation. It performs quite satisfactorily resulting in 0.686 ± 0.013 for accuracy and 0.722 ± 0.014 for area under the receiver operating characteristic curve (AUC) for 10-fold cross-validation (mean ± standard deviation from 50 iterations).

Highlights

Drug induced liver injury (DILI) is a major issue worldwide, both for patients and health providers.[1,2] It is one of the primary causes for attrition during clinical and preclinical studies and the main reason for drug withdrawal from the market.[3−6] DILI is divided into types, (i) hepatocellular, (ii) cholestatic, or (iii) mixed, according to the type of liver damage and the clinical chemistry biomarker alterations.[7]
In order to assess the importance and significance of this additional information individually, we used them in different combinations: all transporters, only bile salt export pump (BSEP), all transporters excluding either BSEP, or P-gp, or breast cancer resistance protein (BCRP), or the OATPs
In this study we present a two-class classification model for the prediction of cholestasis based on a public data set of 578 compounds

Summary

Introduction

Drug induced liver injury (DILI) is a major issue worldwide, both for patients and health providers.[1,2] It is one of the primary causes for attrition during clinical and preclinical studies and the main reason for drug withdrawal from the market.[3−6] DILI is divided into types, (i) hepatocellular, (ii) cholestatic, or (iii) mixed (hepatocellular and cholestatic), according to the type of liver damage and the clinical chemistry biomarker alterations.[7] The cholestatic and mixed hepatocellular and cholestatic type are the two most severe manifestations of DILI and yield almost half of the recorded cases of DILI.[8,9]. While the mechanistic basis for hepatocellular DILI is still a mystery for the majority of the cases, more knowledge exists for cholestatic DILI. There is growing evidence for a vast amount of cholestasis cases pinpointing the important role of hepatic transporters.[10]

Methods

Results

Conclusion