A Complementary Scale of Biased Agonism for Agonists with Differing Maximal Responses.

Area of Science:

• Pharmacology
• Molecular Biology
• Biochemistry

Background:

• G protein-coupled receptors (GPCRs) exhibit multidimensional signaling.
• Functional selectivity, or biased agonism, describes ligands activating distinct signaling pathways with varying efficacies.
• Current bias quantification using transduction coefficients (log(τ/K_A)) can obscure nuanced compound profiles.

Purpose of the Study:

• To introduce a novel efficacy-driven scale, log(τ), for quantifying GPCR ligand bias.
• To complement existing affinity and efficacy-driven scales (log(τ/K_A)).
• To improve the classification and characterization of biased agonists, particularly in cases of partial agonism.

Main Methods:

• Development of a theoretical framework for the log(τ) scale.
• Application of the log(τ) scale to analyze μ-opioid receptor agonists.
• Comparison of the log(τ) scale with the traditional log(τ/K_A) scale.

Main Results:

• The proposed log(τ) scale provides additional resolution for classifying biased agonists.
• This efficacy-driven parameter offers a complementary view to affinity-driven metrics.
• Demonstrated utility in characterizing partial agonists at the μ-opioid receptor.

Conclusions:

• The log(τ) scale enhances the quantitative assessment of functional selectivity.
• It serves as a valuable adjunct to existing models for understanding biased agonism.
• This approach facilitates a more precise characterization of ligand-biased GPCR signaling.