Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics...

Area of Science:

• Biochemistry
• Computational Chemistry
• Medicinal Chemistry

Background:

• Histone deacetylases (HDACs) are crucial metal-dependent enzymes regulating gene expression.
• Overexpression of Class I HDACs is linked to multiple malignancies, disrupting normal cell processes.
• Current epigenetic cancer therapies targeting HDACs have shown limited success.

Purpose of the Study:

• To identify novel inhibitors for Class I HDAC isoforms using computational approaches.
• To develop validated pharmacophore and QSAR models for targeting HDACs.
• To screen compound libraries and discover potential lead compounds for cancer therapy.

Main Methods:

• Ligand-based pharmacophore modeling and 2D quantitative structure-activity relationship (QSAR) modeling.
• Extensive validation of pharmacophore models using IC50 values and experimental energy scores.
• Virtual screening of compound libraries using a validated QSAR model (external R2 = 0.93).
• Molecular dynamics simulations to explore binding modes of lead compounds with HDAC2 and HDAC8.

Main Results:

• Developed and validated pharmacophore and QSAR models for targeting Class I HDACs.
• Short-listed 10 potential lead compounds (C1-C10) with strong binding affinities.
• Identified two compounds (C8 and C9) capable of interacting with all Class I HDAC isoforms.
• Molecular dynamics simulations provided insights into the binding interactions of compound C8 with HDAC2 and HDAC8.

Conclusions:

• The study successfully identified potential novel inhibitors for Class I HDACs using computational methods.
• Compounds C8 and C9 demonstrate significant potential as effective inhibitors for epigenetic cancer therapy.
• The developed models and identified lead compounds warrant further investigation for drug development.