Exploration of histone deacetylase 8 inhibitors through classification QSAR study: Part II

Abstract

Identification of important structural features for histone deacetylase 8 (HDAC8) inhibitions is very challenging. Design of selective HDAC8 inhibitor may lead to accelerate anticancer drug discovery efforts. Our laboratory has continuously trying to find new leads against HDAC8. In this current study, a statistically significant, robust recursive partitioning (RP) model was constructed on 588 diverse compounds to develop a decision tree after performing the Bayesian classification study on the same dataset. The statistical quality of the developed RP model was validated externally on 264 compounds like the earlier reported Bayesian classification modeling. The results of this model were compared with previously developed Naive Bayes classifier. In a nutshell, this study is an attempt of acquiring knowledge about the structural features required for selective HDAC8 inhibitors and may help to design new molecules in future.