Abstract
Histone deacetylase 8 (HDAC8) expressions are correlated with a variety of cancer and tumor conditions. For the pathophysiological contributions of HDAC8, it is classified as an important target for cancer research. The hydroxamate derivatives are identified as more efficient HDAC8 inhibitors. However, strong chelating properties of hydroxamate group with the catalytic zinc ion of HDAC8 resulted in some demerits. Hence, in this current study, classification based chemoinformatic approaches including Bayesian modeling and recursive partitioning studies were conducted on a large and diverse set of 607 hydroxamates having less, very poor to high HDAC8 inhibitory properties. The main motto of this study is to identify and analyze the pivotal structural features of the cap and linker moieties required to obtain better HDAC8 inhibition. Moreover, a scrutiny of the HDAC8 crystal structure bound inhibitors was performed to correlate enzyme-inhibitor interactions with important molecular features resulted from these two classification-based models. The approach may be used to design novel HDAC8 inhibitors.
Communicated by Ramaswamy Sarma
Disclosure statement
The authors have no conflict of interests.