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An evaluation of the operational model when applied to quantify functional selectivity.

Xiao Zhu1, David B Finlay2, Michelle Glass2

  • 1Otago Pharmacometrics Group, National School of Pharmacy, University of Otago, Dunedin, New Zealand.

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Summary

This study analyzes the operational model for functional selectivity, finding that fixing parameters is generally acceptable. A new method eliminates the need for high-efficacy ligands, enabling large-scale screening for selective compounds.

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Area of Science:

  • Pharmacology
  • Biochemistry
  • Mathematical Biology

Background:

  • Functional selectivity describes how ligands differentially regulate signaling pathways via a single receptor.
  • The operational model is a common tool for analyzing functional selectivity data.
  • Understanding the mathematical properties of this model is crucial for accurate analysis.

Purpose of the Study:

  • To mathematically assess the properties of the operational model for analyzing functional selectivity.
  • To evaluate the impact of fixing model parameters on analysis outcomes.
  • To develop a more efficient method for quantifying functional selectivity.

Main Methods:

  • Mathematical identifiability analysis of the operational model.
  • Simulations to evaluate model performance with fixed parameters.
  • Analysis of parameter estimation precision and error propagation.

Main Results:

  • Identified that parameters R0 and KE are not independently identifiable, but their ratio (τ) can be used.
  • Found that the transduction coefficient R (τKA) is often precisely estimated.
  • Demonstrated that fixing parameters like Em or KA is generally well-tolerated due to normalization, allowing Δlog(R) determination without a full agonist.

Conclusions:

  • Current methods for quantifying functional selectivity are generally robust to parameter fixing.
  • A novel method is proposed that removes the requirement for high-efficacy ligands in experiments.
  • This facilitates large-scale screening for compounds exhibiting desired functional selectivity profiles.