Drug Development.

Area of Science:

• Epigenetics and Molecular Biology
• Medicinal Chemistry
• Computational Drug Discovery

Background:

• Histone deacetylases (HDACs) regulate gene expression and are implicated in various diseases.
• Class I HDACs, particularly HDAC3, are targets for therapeutic intervention, but non-selective inhibition causes side effects.
• Existing HDAC3 inhibitors often face challenges with potency, selectivity, and toxicity, necessitating novel approaches.

Purpose of the Study:

• To identify novel histone deacetylase 3 (HDAC3)-selective inhibitors with unique zinc-binding groups (ZBGs).
• To computationally screen diverse compound libraries for potential HDAC3 inhibitors.
• To establish a foundation for developing safer and more effective HDAC3-targeted therapies.

Main Methods:

• Utilized in silico tools (PROCHECK, VERIFY3D, Molecular Operating Environment, ProteinsPlus, Schrodinger Maestro) for protein structure validation, active site prediction, and molecular docking.
• Performed structure-based virtual screening of focused compound libraries.
• Benchmarked docking protocols using re-docking and active/decoy sets to ensure reliability.

Main Results:

• Screening identified 22 diverse compounds, with 11 exhibiting HDAC3 inhibitory activity in vitro.
• Compound 'a' showed potent HDAC3 inhibition (IC50 0.99 µM) but lacked selectivity and had predicted toxicities.
• Compound 'b' demonstrated moderate HDAC3 inhibition (IC50 15.5 µM) with improved selectivity over HDAC1/2 and predicted toxicities, while both compounds were predicted to be non-blood-brain-barrier (BBB) permeant.

Conclusions:

• Successfully identified novel compounds with HDAC3 inhibitory potential.
• Highlighted the critical need for structural optimization to improve inhibitory activity and selectivity.
• Emphasized the importance of enhancing blood-brain-barrier (BBB) permeability and mitigating predicted toxicities for future drug development.