Predicting Hepatotoxicity of Drug-like compounds based on Bayesian model

Abstract

Predicting hepatotoxicity is an important component of safety-related evaluations of drug-like compounds. Hepatotoxicity is related to the physicochemical properties of drug-like compounds, especially their structural alerts. In this study, we developed a Bayesian model to predict the hepatotoxicities of 498 drug-like compounds based on their quantitative structure-toxicity relationships (QSAR). The devised model predicted the hepatotoxicity of these compounds using 25 structural descriptors (such as the ECFP6 fingerprint) and provided a sensitivity, specificity