Optimization Strategy for Chemical Database Screening to Discover New Histone
Jakyung Yoo, Young Hoon Jung, Ok Pyo Zee, and Hyun-Ju Park
College of Pharmacy, Sungkyunkwan University, Suwon 440-746, Korea
Histone deacetylase (HDAC) inhibitor is an emerging target for the treatment of cancer,
and the discovery of new HDAC inhibitors as a potential anticancer appears highly desirable.
As part of our efforts to find novel small molecule HDAC inhibitors, a computational screening
of more than 100,000 organic compounds contained in commercially available databases was
Initially, we setup a reliable method to analyze the binding energy scores obtained
from the FlexX docking of known HDAC inhibitors. As a filtering tool, a 3D-QSAR/CoMSIA
model was built, based on HDAC inhibitory activities of synthetic derivatives of clinically
Flexible dockings, using DOCK and FlexX program, were performed on 2503 entries
satisfying the pharmacophore query in 3D search by UNITY. In subsequent steps, 315 best-
ranked hits were filtered by optimized scoring method, and then reranked by predicted activities
obtained from CoMSIA analysis to select final candidate compounds for experimental testing.
Through this study, we suggest a fast and reliable in-silico screening strategy using
optimized scoring and filtering methods.