Title:Discovery of Novel Small Molecule HDAC1, 2, 3 Inhibitors -- Combined
Receptor-Based and Ligand-Based Virtual Screening Strategy
Volume: 19
Issue: 7
Author(s): Yi Wu, Bo Zhang, Xiaowu Dong, Shenglin Ma*Shengquan Hu*
Affiliation:
- Department of Oncology, Nanjing Medical University, Hangzhou First People’s Hospital, Hangzhou,
Zhejiang 310006, P.R. China
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou,
Zhejiang 310058, P.R. China
Keywords:
HDAC1, inhibitors, RBVS, LBVS, cancer, deacetylation.
Abstract:
Aims: This study aims to investigate and validate the potential drug target to HDAC1.
Background: Human histone deacetylase 1 (HDAC1) can catalyze the deacetylation of histones belonging
to the family of human histone deacetylases (HDACs). Amide hydrolase HDAC1 plays a key role in
the development of many serious cancers such as prostate cancer, gastric cancer, lung cancer, esophageal
cancer, colon cancer, and breast cancer. Therefore, HDAC1 inhibitors, promoting the transcription of a
series of key genes such as the p53 gene and inhibiting the development of cancer through various downstream
mechanisms, have great potential for the treatment of cancer.
Objective: The objective of this study is to discover new skeleton HDAC1 inhibitors efficiently and conveniently
with therapeutic potential for cancer.
Methods: Based on the crystal structure of HDAC1, through the combination of receptor-based and ligand-
based virtual screening from the commercial compound library, the top-ranked compounds are selected
for purchase through binding modes analysis, and their activities were verified through in vitro
HDAC1 inhibitory biological experiments.
Results: Based on LeDock, 5ICN showed good distinguishing ability and was used as the receptor. According
to the results of the LeDock docking scoring from receptor-based virtual screening, 69 compounds
with binding energy less than -7.5 kcal/mol were obtained and used for ligand-based virtual
screening. A total of 21 novel compounds with high potential HDAC1 inhibitory activity were collected
by combining the similarity searching (NN) and the multinomial Naive Bayes machine learning model
(NB) methods. Through binding modes analysis, 10 compounds with different structures with potential
HDAC1 inhibitory activity were selected and screened HDAC1 inhibitory in vitro. May267 showed moderate
HDAC1 inhibitory activity, and the inhibition rate was 48% at a concentration of 20 μM.
Conclusion: This study discovers novel small molecule HDAC1 inhibitors by combined receptor-based
and ligand-based virtual screening strategy, which provides an efficient method for the discovery of other
small molecule drugs. May267 shows moderate HDAC1 inhibitory activity, which can be further optimized
as a lead compound. However, it still has the problem of poor kinase selectivity to be solved.
