dc.contributor.author |
Zhu, Xiao |
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dc.contributor.author |
Finlay, David |
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dc.contributor.author |
Glass, Michelle |
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dc.contributor.author |
Duffull, Stephen B |
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dc.date.accessioned |
2018-10-22T19:43:42Z |
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dc.date.issued |
2018-05 |
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dc.identifier.citation |
British journal of pharmacology 175(10):1654-1668 May 2018 |
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dc.identifier.issn |
0007-1188 |
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dc.identifier.uri |
http://hdl.handle.net/2292/43021 |
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dc.description.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 KE were not independently identifiable which can be solved by considering their ratio, τ. The ratio parameter, τ, was often imprecisely estimated when only functional assay data were available and generally only the transduction coefficient R ( τKA) could be estimated precisely. The general operational model (that includes baseline and the Hill coefficient) required either the parameters Em or KA to be fixed. The normalization process largely cancelled out the mean error of the calculated Δlog (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 Δlog (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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dc.format.medium |
Print-Electronic |
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dc.language |
eng |
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dc.relation.ispartofseries |
British journal of pharmacology |
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dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
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dc.rights |
This is the peer reviewed version of the following article: Zhu, X., Finlay, D. B., Glass, M., & Duffull, S. B. (2018). An evaluation of the operational model when applied to quantify functional selectivity.. British journal of pharmacology, 175(10), 1654-1668, which has been published in final form at http://dx.doi.org/10.1111/bph.14171. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. |
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dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
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dc.rights.uri |
https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html |
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dc.subject |
Ligands |
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dc.subject |
Stochastic Processes |
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dc.subject |
Models, Biological |
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dc.title |
An evaluation of the operational model when applied to quantify functional selectivity. |
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dc.type |
Journal Article |
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dc.identifier.doi |
10.1111/bph.14171 |
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pubs.issue |
10 |
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pubs.begin-page |
1654 |
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pubs.volume |
175 |
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dc.rights.holder |
Copyright: The British Pharmacological Society |
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dc.identifier.pmid |
29457969 |
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pubs.end-page |
1668 |
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pubs.publication-status |
Published |
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dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
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pubs.subtype |
Research Support, Non-U.S. Gov't |
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pubs.subtype |
research-article |
en |
pubs.subtype |
Journal Article |
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pubs.elements-id |
726481 |
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pubs.org-id |
Medical and Health Sciences |
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pubs.org-id |
Medical Sciences |
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dc.identifier.eissn |
1476-5381 |
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pubs.record-created-at-source-date |
2018-02-20 |
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pubs.dimensions-id |
29457969 |
en |