A Rational Approach for the Identification of Non-Hydroxamate HDAC6-Selective Inhibitors

Abstract

The human histone deacetylase isoform 6 (HDAC6) has been demonstrated to play a major role in cell motility and aggresome formation, being interesting for the treatment of multiple tumour types and neurodegenerative conditions. Currently, most HDAC inhibitors in preclinical or clinical evaluations are non-selective inhibitors, characterised by a hydroxamate zinc-binding group (ZBG) showing off-target effects and mutagenicity. The identification of selective HDAC6 inhibitors with novel chemical properties has not been successful yet, also because of the absence of crystallographic information that makes the rational design of HDAC6 selective inhibitors difficult. Using HDAC inhibitory data retrieved from the ChEMBL database and ligand-based computational strategies, we identified 8 original new non-hydroxamate HDAC6 inhibitors from the SPECS database, with activity in the low μM range. The most potent and selective compound, bearing a hydrazide ZBG, was shown to increase tubulin acetylation in human cells. No effects on histone H4 acetylation were observed. To the best of our knowledge, this is the first report of an HDAC6 selective inhibitor bearing a hydrazide ZBG. Its capability to passively cross the blood-brain barrier (BBB), as observed through PAMPA assays, and its low cytotoxicity in vitro, suggested its potential for drug development.

Figure 1. Prototypical pharmacophoric scheme for HDAC inhibition and the in-silico driven protocol adopted in this study.

(A) Chemical structure of the FDA-approved HDAC inhibitor Vorinostat (SAHA): the prototypical pharmacophoric scheme for HDAC inhibition is highlighted. (B) Protocol for pharmacophore-based virtual screening (PBVS) and ligand-based virtual screening (LBVS) adopted in this study.

Figure 2. Chemical structures of compounds selected for pharmacophore generation.

The structure of the most potent HDAC6 inhibitor (PMID_18642892_3) reported in the literature is also presented.

Figure 3. Pharmacophore model for selective HDAC6 inhibitors according to FLAPpharm.

(A) Alignment obtained for the three compounds. (B) Pharmacophore obtained upon alignment in terms of common pharmacophoric interaction fields (PIFs). The hydrogen-bond donor constraint used for screening is indicated by a red arrow. (C) Pharmacophore obtained upon alignment in terms of common pharmacophoric points at the centroid of pseudoPIFs. The most relevant common pharmacophoric points at the centroid of the pseudoPIFs are also highlighted. For both pharmacophore depictions (B, C), the green areas represent the hydrophobic moieties, the blue areas represent the H-bond donor regions, the red areas represent the H-bond acceptor regions, and the cyan wireframe surface defines the shape of the pharmacophore.

Figure 4. Chemical structure of the selected virtual screening hits from the SPECS database.

The approach used for retrieving each compound is highlighted. PBVS as pharmacophore-based virtual screening; LBVS as ligand-based virtual screening.

Figure 5. Relative α-tubulin acetylation in HeLa cells treated with AK-14 and Tubastatin A (*P < 0.05, two-sided t-test).

Results are presented as the mean of 3 independent experiments in triplicate with error bars representing the standard deviation (SD).

Figure 6. Western blot for Histone H4 acetylation levels in HeLa cells treated with AK-14 and Trichostatin A (TSA).