Dataset Information

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

ABSTRACT:

Background and purpose

Functional selectivity describes the ability of ligands to differentially regulate multiple signalling pathways when coupled to a single receptor, and the operational model is commonly used to analyse these data. Here, we assess the mathematical properties of the operational model and evaluate the outcomes of fixing parameters on model performance.

Experimental approach

The operational model was evaluated using both a mathematical identifiability analysis and simulation.

Key results

Mathematical analysis revealed that the parameters R₀ and K_E were not independently identifiable which can be solved by considering their ratio, ?. The ratio parameter, ?, was often imprecisely estimated when only functional assay data were available and generally only the transduction coefficient R ( ?KA) could be estimated precisely. The general operational model (that includes baseline and the Hill coefficient) required either the parameters E_m or K_A to be fixed. The normalization process largely cancelled out the mean error of the calculated ?log (R) caused by fixing these parameters. From this analysis, it was determined that we can avoid the need for a full agonist ligand to be included in an experiment to determine ?log (R).

Conclusion and implications

This analysis has provided a ready-to-use understanding of current methods for quantifying functional selectivity. It showed that current methods are generally tolerant to fixing parameters. A new method was proposed that removes the need for including a high efficacy ligand in any given experiment, which allows application to large-scale screening to identify compounds with desirable features of functional selectivity.

SUBMITTER: Zhu X

PROVIDER: S-EPMC5913411 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Publications

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

Zhu Xiao X Finlay David B DB Glass Michelle M Duffull Stephen B SB

British journal of pharmacology 20180330 10

<h4>Background and purpose</h4>Functional selectivity describes the ability of ligands to differentially regulate multiple signalling pathways when coupled to a single receptor, and the operational model is commonly used to analyse these data. Here, we assess the mathematical properties of the operational model and evaluate the outcomes of fixing parameters on model performance.<h4>Experimental approach</h4>The operational model was evaluated using both a mathematical identifiability analysis an ...[more]

PMID: 29457969

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Dataset Information

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

Background and purpose

Experimental approach

Key results

Conclusion and implications

Publications

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

Similar Datasets

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