Discovery of Potent and Isoform‐Selective Histone Deacetylase Inhibitors Using Structure‐Based Virtual Screening and Biological Evaluation

The Histone Deacetylase Family: Structural Features and Application of Combined Computational Methods

Histone deacetylases (HDACs) are crucial in gene transcription, removing acetyl groups from histones. They also influence the deacetylation of non-histone proteins, contributing to the regulation of various biological processes. Thus, HDACs play pivotal roles in various diseases, including cancer, neurodegenerative disorders, and inflammatory conditions, highlighting their potential as therapeutic targets. This paper reviews the structure and function of the four classes of human HDACs. While four HDAC inhibitors are currently available for treating hematological malignancies, numerous others are undergoing clinical trials. However, their non-selective toxicity necessitates ongoing research into safer and more efficient class-selective or isoform-selective inhibitors. Computational techniques have greatly facilitated the discovery of HDAC inhibitors that achieve the desired potency and selectivity. These techniques encompass ligand-based strategies such as scaffold hopping, pharmacophore modeling, three-dimensional quantitative structure–activity relationships (3D-QSAR), and structure-based virtual screening (molecular docking). Additionally, advancements in molecular dynamics simulations, along with Poisson–Boltzmann/molecular mechanics generalized Born surface area (PB/MM-GBSA) methods, have enhanced the accuracy of predicting ligand binding affinity. In this review, we delve into the ways in which these methods have contributed to designing and identifying HDAC inhibitors.

In the quest for histone deacetylase inhibitors: current trends in the application of multilayered computational methods

Histone deacetylase (HDAC) inhibitors have gained attention over the past three decades because of their potential in the treatment of different diseases including various forms of cancers, neurodegenerative disorders, autoimmune, inflammatory diseases, and other metabolic disorders. To date, 5 HDAC inhibitor drugs are marketed for the treatment of hematological malignancies and several drug-candidate HDAC inhibitors are at different stages of clinical trials. However, due to the toxic side effects of these drugs resulting from the lack of target selectivity, active studies are ongoing to design and develop either class-selective or isoform-selective inhibitors. Computational methods have aided the discovery of HDAC inhibitors with the desired potency and/or selectivity. These methods include ligand-based approaches such as scaffold hopping, pharmacophore modeling, three-dimensional quantitative structure-activity relationships (3D-QSAR); and structure-based virtual screening (molecular docking). The current trends involve the application of the combination of these methods and incorporating molecular dynamics simulations coupled with Poisson-Boltzmann/molecular mechanics generalized Born surface area (MM-PBSA/MM-GBSA) to improve the prediction of ligand binding affinity. This review aimed at understanding the current trends in applying these multilayered strategies and their contribution to the design/identification of HDAC inhibitors.

Discovery of first novel sigma/HDACi dual-ligands with a potent in vitro antiproliferative activity

Designing and discovering compounds for dual-target inhibitors is challenging to synthesize new, safer, and more efficient drugs than single-target drugs, especially to treat multifactorial diseases such as cancer. The simultaneous regulation of multiple targets might represent an alternative synthetic approach to optimize patient compliance and tolerance, minimizing the risk of target-based drug resistance due to the modulation of a few targets. To this end, we conceived for the first time the design and synthesis of dual-ligands σR/HDACi to evaluate possible employment as innovative candidates to address this complex disease. Among all synthesized compounds screened for several tumoral cell lines, compound 6 (Kiσ1R = 38 ± 3.7; Kiσ2R = 2917 ± 769 and HDACs IC50 = 0.59 µM) is the most promising candidate as an antiproliferative agent with an IC50 of 0.9 µM on the HCT116 cell line and no significant toxicity to normal cells. Studies of molecular docking, which confirmed the affinity over σ1R and a pan-HDACs inhibitory behavior, support a possible balanced affinity and activity between both targets.

Design of Fluorogenic Probe Based on Intramolecular Condensation for Specific Detection of HDAC3

It is crucial to develop fluorogenic probes for selective targeting of HDACs to explore the roles of HDACs in the tumor onset and progression as well as HDAC-related drug development. However, considerable non-specific signals were produced by spontaneous hydrolysis and undesirable intermolecular attack of the unstable caging moiety in the detection of HDACs with previous probes. To improve the detection specificity, we proposed an intramolecular condensation strategy by the replacement of the traditional acetamide moiety with a trans-enamide unit. Upon deacetylation by HDACs, rapid intramolecular condensation reaction between newly formed terminal aldehyde and hydrazine moiety would occur to afford highly fluorescent hydrazone product. Systematic studies demonstrated that the probe exhibited an extraordinary selectivity for HDAC3 over other HDAC isoforms and interfering substances. The stability and specificity of the indicator make it a powerful tool for HDAC3 activity detection and HDAC3-related drug development.