ArticleBritish journal of pharmacology2018
An evaluation of the operational model when applied to quantify functional selectivity.
Article in British journal of pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
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- Evaluating signaling bias for synthetic cannabinoid receptor agonists at the cannabinoid CBPharmacology research & perspectives · 2023Article
- Quantitative receptor model for responses that are left- or right-shifted versus occupancy (are more or less concentration sensitive): the SABRE approach.Frontiers in pharmacology · 2023Article
- A single unified model for fitting simple to complex receptor response data.Scientific reports · 2020Article
- Evaluation of the profiles of CBBritish journal of pharmacology · 2020Article
- 100 years of modelling ligand-receptor binding and response: A focus on GPCRs.British journal of pharmacology · 2020Review
- Do Toxic Synthetic Cannabinoid Receptor Agonists Have Signature in Vitro Activity Profiles? A Case Study of AMB-FUBINACA.ACS chemical neuroscience · 2019Article
- An intact model for quantifying functional selectivity.Scientific reports · 2019Article
- A Receptor Model With Binding Affinity, Activation Efficacy, and Signal Amplification Parameters for Complex Fractional Response Versus Occupancy Data.Frontiers in pharmacology · 2019Article
- An evaluation of the operational model when applied to quantify functional selectivity.British journal of pharmacology · 2018Article
- Cannabinoid Receptor 2 Signalling Bias Elicited by 2,4,6-Trisubstituted 1,3,5-Triazines.Frontiers in pharmacology · 2018Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeFunctional 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
resultsMathematical analysis revealed that the parameters 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.