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A single unified model for fitting simple to complex receptor response data
The fitting of complex receptor-response data where fractional response and occupancy do not match is challenging. They encompass important cases including (a) the presence of “receptor reserve” and/or partial agonism, (b) multiple responses assessed at different vantage points along a pathway, (c)...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7414914/ https://www.ncbi.nlm.nih.gov/pubmed/32770075 http://dx.doi.org/10.1038/s41598-020-70220-w |
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author | Buchwald, Peter |
author_facet | Buchwald, Peter |
author_sort | Buchwald, Peter |
collection | PubMed |
description | The fitting of complex receptor-response data where fractional response and occupancy do not match is challenging. They encompass important cases including (a) the presence of “receptor reserve” and/or partial agonism, (b) multiple responses assessed at different vantage points along a pathway, (c) responses that are different along diverging downstream pathways (biased agonism), and (d) constitutive activity. For these, simple models such as the well-known Clark or Hill equations cannot be used. Those that can, such as the operational (Black&Leff) model, do not provide a unified approach, have multiple nonintuitive parameters that are challenging to fit in well-defined manner, have difficulties incorporating binding data, and cannot be reduced or connected to simpler forms. We have recently introduced a quantitative receptor model (SABRE) that includes parameters for Signal Amplification (γ), Binding affinity (K(d)), Receptor activation Efficacy (ε), and constitutive activity (ε(R0)). It provides a single equation to fit complex cases within a full two-state framework with the possibility of incorporating receptor occupancy data (i.e., experimental K(d)s). Simpler cases can be fit by using consecutively reduced forms obtained by constraining parameters to specific values, e.g., ε(R0) = 0: no constitutive activity, γ = 1: no amplification (E(max)-type fitting), and ε = 1: no partial agonism (Clark equation). Here, a Hill-type extension is introduced (n ≠ 1), and simulated and experimental receptor-response data from simple to increasingly complex cases are fitted within the unified framework of SABRE with differently constrained parameters. |
format | Online Article Text |
id | pubmed-7414914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-74149142020-08-11 A single unified model for fitting simple to complex receptor response data Buchwald, Peter Sci Rep Article The fitting of complex receptor-response data where fractional response and occupancy do not match is challenging. They encompass important cases including (a) the presence of “receptor reserve” and/or partial agonism, (b) multiple responses assessed at different vantage points along a pathway, (c) responses that are different along diverging downstream pathways (biased agonism), and (d) constitutive activity. For these, simple models such as the well-known Clark or Hill equations cannot be used. Those that can, such as the operational (Black&Leff) model, do not provide a unified approach, have multiple nonintuitive parameters that are challenging to fit in well-defined manner, have difficulties incorporating binding data, and cannot be reduced or connected to simpler forms. We have recently introduced a quantitative receptor model (SABRE) that includes parameters for Signal Amplification (γ), Binding affinity (K(d)), Receptor activation Efficacy (ε), and constitutive activity (ε(R0)). It provides a single equation to fit complex cases within a full two-state framework with the possibility of incorporating receptor occupancy data (i.e., experimental K(d)s). Simpler cases can be fit by using consecutively reduced forms obtained by constraining parameters to specific values, e.g., ε(R0) = 0: no constitutive activity, γ = 1: no amplification (E(max)-type fitting), and ε = 1: no partial agonism (Clark equation). Here, a Hill-type extension is introduced (n ≠ 1), and simulated and experimental receptor-response data from simple to increasingly complex cases are fitted within the unified framework of SABRE with differently constrained parameters. Nature Publishing Group UK 2020-08-07 /pmc/articles/PMC7414914/ /pubmed/32770075 http://dx.doi.org/10.1038/s41598-020-70220-w Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Buchwald, Peter A single unified model for fitting simple to complex receptor response data |
title | A single unified model for fitting simple to complex receptor response data |
title_full | A single unified model for fitting simple to complex receptor response data |
title_fullStr | A single unified model for fitting simple to complex receptor response data |
title_full_unstemmed | A single unified model for fitting simple to complex receptor response data |
title_short | A single unified model for fitting simple to complex receptor response data |
title_sort | single unified model for fitting simple to complex receptor response data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7414914/ https://www.ncbi.nlm.nih.gov/pubmed/32770075 http://dx.doi.org/10.1038/s41598-020-70220-w |
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