Selective structure-based virtual screening for full and partial agonists of the beta2 adrenergic receptor

Area of Science:

• Pharmacology
• Structural Biology
• Computational Chemistry

Background:

• The beta2 adrenergic receptor's high-resolution X-ray structure has limitations in differentiating ligands with varying functional effects.
• Distinguishing between inverse agonists/antagonists and partial/full agonists is critical for drug development.

Purpose of the Study:

• To develop a computational model capable of discriminating between different classes of beta2 adrenergic receptor ligands.
• To improve structure-based virtual screening for identifying agonists with specific functional activities.

Main Methods:

• Modification of the ground-state beta2 adrenergic receptor X-ray structure to incorporate early activation events.
• Structure-based virtual screening employing a topological scoring function based on molecular interaction fingerprints.

Main Results:

• The modified receptor model successfully distinguished between ligands with different functional effects.
• Virtual screening enriched for partial and full agonists, demonstrating the model's selectivity.
• Molecular interaction fingerprints were essential for accurate pose ranking and enrichment.

Conclusions:

• A refined receptor model reflecting activation dynamics is superior for discriminating ligand efficacy.
• Structure-based virtual screening with appropriate scoring functions can effectively identify agonists with specific functional profiles.
• This methodology advances the design and discovery of targeted beta2 adrenergic receptor modulators.