In silico probing and biological evaluation of SETDB1/ESET-targeted novel compounds that reduce tri-methylated histone H3K9 (H3K9me3) level

Insun Park, Yu Jin Hwang, Tae Hun Kim, Ambily Nath Indu Viswanath, Ashwini M. Londhe, Seo Yun Jung, Kyoung Mi Sim, Sun Joon Min, Ji Eun Lee, Jihye Seong, Yun Kyung Kim, Kyoung Tai No, Hoon Ryu, Ae Nim Pae

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

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. Graphical Abstract: [Figure not available: see fulltext.].

Original languageEnglish
Pages (from-to)877-889
Number of pages13
JournalJournal of Computer-Aided Molecular Design
Volume31
Issue number10
DOIs
Publication statusPublished - 2017 Oct 1

Bibliographical note

Publisher Copyright:
© 2017, Springer International Publishing AG.

All Science Journal Classification (ASJC) codes

  • Drug Discovery
  • Computer Science Applications
  • Physical and Theoretical Chemistry

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