| Literature DB >> 28879500 |
Insun Park1,2, Yu Jin Hwang1, TaeHun Kim1,3, Ambily Nath Indu Viswanath1,3, Ashwini M Londhe1,3, Seo Yun Jung1, Kyoung Mi Sim1,4, Sun-Joon Min5, Ji Eun Lee6, Jihye Seong1,3, Yun Kyung Kim1,3, Kyoung Tai No2, Hoon Ryu7,8, Ae Nim Pae9,10.
Abstract
ERG-associated protein with the SET domain (ESET/SET domain bifurcated 1/SETDB1/KMT1E) is a histone lysine methyltransferase (HKMT) and it preferentially tri-methylates lysine 9 of histone H3 (H3K9me3). SETDB1/ESET leads to heterochromatin condensation and epigenetic gene silencing. These functional changes are reported to correlate with Huntington's disease (HD) progression and mood-related disorders which make SETDB1/ESET a viable drug target. In this context, the present investigation was performed to identify novel peptide-competitive small molecule inhibitors of the SETDB1/ESET by a combined in silico-in vitro approach. A ligand-based pharmacophore model was built and employed for the virtual screening of ChemDiv and Asinex database. Also, a human SETDB1/ESET homology model was constructed to supplement the data further. Biological evaluation of the selected 21 candidates singled out 5 compounds exhibiting a notable reduction of the H3K9me3 level via inhibitory potential of SETDB1/ESET activity in SETDB1/ESET-inducible cell line and HD striatal cells. Later on, we identified two compounds as final hits that appear to have neuronal effects without cytotoxicity based on the result from MTT assay. These compounds hold the calibre to become the future lead compounds and can provide structural insights into more SETDB1/ESET-focused drug discovery research. Moreover, these SETDB1/ESET inhibitors may be applicable for the preclinical study to ameliorate neurodegenerative disorders via epigenetic regulation.Entities:
Keywords: Homology modeling; Huntington’s disease; Peptide-competitive small molecule inhibitors; Pharmacophore; SETDB1/ESET; Trimethylated H3K9 (H3K9me3); Virtual screening
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Year: 2017 PMID: 28879500 DOI: 10.1007/s10822-017-0052-3
Source DB: PubMed Journal: J Comput Aided Mol Des ISSN: 0920-654X Impact factor: 3.686