Evaluation of Cx43 Gap Junction Inhibitors Using a Quantitative Structure-Activity Relationship Model

Area of Science:

• Cardiovascular Pharmacology
• Molecular Biology
• Computational Chemistry

Background:

• Connexin-43 (Cx43) gap junctions (GJs) are crucial for cardiac electrical impulse conduction.
• Modulating Cx43 GJ activity offers therapeutic potential for cardiac arrhythmias.
• Molecular docking's predictive accuracy for GJ inhibitor potency is limited.

Purpose of the Study:

• To demonstrate the utility of Quantitative Structure-Activity Relationship (QSAR) models for identifying potent Cx43 GJ inhibitors.
• To compare the predictive performance of QSAR and molecular docking for Cx43 GJ inhibitors.

Main Methods:

• Evaluated 16 known Cx43 GJ inhibitors using molecular docking, QSAR, and 3D-QSAR.
• Suggested and experimentally tested d-limonene as a putative Cx43 inhibitor in HeLa cells.
• Compared predicted inhibitory concentrations (pIC50) with experimental values (eIC50).

Main Results:

• QSAR and 3D-QSAR models showed strong correlation (R=0.88, R=0.90) between predicted and experimental potencies.
• Molecular docking showed a weaker correlation (R=0.78) with experimental potencies.
• d-limonene was identified as a putative Cx43 GJ inhibitor.

Conclusions:

• QSAR modeling provides a more precise method for identifying potent Cx43 GJ inhibitors than molecular docking alone.
• The study proposes QSAR for primary screening of novel GJ channel inhibitors, followed by patch-clamp validation.