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Histone Acetyltransferase and Deacetylase Inhibitors—New Aspects and Developments

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biology".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 1473

Special Issue Editors


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Guest Editor
Institute of Pharmacy, Martin-Luther University Halle-Wittenberg, Halle (Saale), Germany
Interests: PROTACs; HDACs; carbonic anhydrase; kinase; computational drug discovery
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Special Issue Information

Dear Colleagues,

Epigenetic processes modulate gene transcription and genomic stability, ensuring proper cell development and differentiation. Epigenetic processes are controlled, among other things, by post-translational modifications on histones, with acetylation being a highly abundant example of these modifications. Acetylation patterns on histones are regulated by the synergy between a group of epigenetic enzymes, histone acetyltransferase enzymes (HATs), which introduce the modification, and a group that removes the modification, named histone deacetylases (HDACs). Histone deacetylases, in particular, have come into focus for drug discovery in recent years, and the first five inhibitors have been approved for cancer therapy. Although these compounds are non-selective HDAC inhibitors, current research is focused on developing selective inhibitors of the 18 HDAC subtypes. In particular, the recently explored subtypes, such as HDAC10, HDAC11, or the sirtuins, represent new targets for putative drugs. The availability of crystal structures for most of the HDACs also enables the application of in silico and structure-based approaches to drug discovery. In the case of histone acetyltransferases, much fewer inhibitor discovery studies have been reported so far.

A completely new approach is the inhibition of physiological processes by protein degradation. This can be achieved with so-called proteolysis-targeting chimera (PROTACs) or molecular glues. PROTACs are heterobifunctional molecules that couple a target ligand with a ligand for an E3 ligase so that the enzyme is polyubiquitinated and degraded by the proteasome. For HDACs, the PROTAC field is still in its infancy, although the first compounds have recently been reported.

The aim of this Special Issue is to highlight the current efforts and new results in medicinal chemistry, in silico studies, and biological characterization of histone deacetylase and acetyltransferase inhibitors. Original research articles, review articles, and short communications in the research areas described (but not limited to) are welcome.

Prof. Dr. Wolfgang Sippl
Dr. Hany Ibrahim
Guest Editors

Manuscript Submission Information

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Keywords

  • histone acetyltransferase enzymes (HATs)
  • histone deacetylases (HDACs)
  • HDAC inhibitors
  • histone
  • deacetylase
  • acetyltransferase

Published Papers (1 paper)

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Research

30 pages, 8716 KiB  
Article
Comparative Structure-Based Virtual Screening Utilizing Optimized AlphaFold Model Identifies Selective HDAC11 Inhibitor
by Fady Baselious, Sebastian Hilscher, Dina Robaa, Cyril Barinka, Mike Schutkowski and Wolfgang Sippl
Int. J. Mol. Sci. 2024, 25(2), 1358; https://doi.org/10.3390/ijms25021358 - 22 Jan 2024
Viewed by 1200
Abstract
HDAC11 is a class IV histone deacylase with no crystal structure reported so far. The catalytic domain of HDAC11 shares low sequence identity with other HDAC isoforms, which makes conventional homology modeling less reliable. AlphaFold is a machine learning approach that can predict [...] Read more.
HDAC11 is a class IV histone deacylase with no crystal structure reported so far. The catalytic domain of HDAC11 shares low sequence identity with other HDAC isoforms, which makes conventional homology modeling less reliable. AlphaFold is a machine learning approach that can predict the 3D structure of proteins with high accuracy even in absence of similar structures. However, the fact that AlphaFold models are predicted in the absence of small molecules and ions/cofactors complicates their utilization for drug design. Previously, we optimized an HDAC11 AlphaFold model by adding the catalytic zinc ion and minimization in the presence of reported HDAC11 inhibitors. In the current study, we implement a comparative structure-based virtual screening approach utilizing the previously optimized HDAC11 AlphaFold model to identify novel and selective HDAC11 inhibitors. The stepwise virtual screening approach was successful in identifying a hit that was subsequently tested using an in vitro enzymatic assay. The hit compound showed an IC50 value of 3.5 µM for HDAC11 and could selectively inhibit HDAC11 over other HDAC subtypes at 10 µM concentration. In addition, we carried out molecular dynamics simulations to further confirm the binding hypothesis obtained by the docking study. These results reinforce the previously presented AlphaFold optimization approach and confirm the applicability of AlphaFold models in the search for novel inhibitors for drug discovery. Full article
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