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Comparing enzyme activity modifier equations through the development of global data fitting templates in Excel

The classical way of defining enzyme inhibition has obscured the distinction between inhibitory effect and the inhibitor binding constant. This article examines the relationship between the simple binding curve used to define biomolecular interactions and the standard inhibitory term (1 + ([I]∕K(i))...

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Detalles Bibliográficos
Autor principal: Walsh, Ryan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6296338/
https://www.ncbi.nlm.nih.gov/pubmed/30581673
http://dx.doi.org/10.7717/peerj.6082
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author Walsh, Ryan
author_facet Walsh, Ryan
author_sort Walsh, Ryan
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description The classical way of defining enzyme inhibition has obscured the distinction between inhibitory effect and the inhibitor binding constant. This article examines the relationship between the simple binding curve used to define biomolecular interactions and the standard inhibitory term (1 + ([I]∕K(i))). By understanding how this term relates to binding curves which are ubiquitously used to describe biological processes, a modifier equation which distinguishes between inhibitor binding and the inhibitory effect, is examined. This modifier equation which can describe both activation and inhibition is compared to standard inhibitory equations with the development of global data fitting templates in Excel and via the global fitting of these equations to simulated and previously published datasets. In both cases, this modifier equation was able to match or outperform the other equations by providing superior fits to the datasets. The ability of this single equation to outperform the other equations suggests an over-complication of the field. This equation and the template developed in this article should prove to be useful tools in the study of enzyme inhibition and activation.
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spelling pubmed-62963382018-12-21 Comparing enzyme activity modifier equations through the development of global data fitting templates in Excel Walsh, Ryan PeerJ Biochemistry The classical way of defining enzyme inhibition has obscured the distinction between inhibitory effect and the inhibitor binding constant. This article examines the relationship between the simple binding curve used to define biomolecular interactions and the standard inhibitory term (1 + ([I]∕K(i))). By understanding how this term relates to binding curves which are ubiquitously used to describe biological processes, a modifier equation which distinguishes between inhibitor binding and the inhibitory effect, is examined. This modifier equation which can describe both activation and inhibition is compared to standard inhibitory equations with the development of global data fitting templates in Excel and via the global fitting of these equations to simulated and previously published datasets. In both cases, this modifier equation was able to match or outperform the other equations by providing superior fits to the datasets. The ability of this single equation to outperform the other equations suggests an over-complication of the field. This equation and the template developed in this article should prove to be useful tools in the study of enzyme inhibition and activation. PeerJ Inc. 2018-12-14 /pmc/articles/PMC6296338/ /pubmed/30581673 http://dx.doi.org/10.7717/peerj.6082 Text en ©2018 Walsh http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Biochemistry
Walsh, Ryan
Comparing enzyme activity modifier equations through the development of global data fitting templates in Excel
title Comparing enzyme activity modifier equations through the development of global data fitting templates in Excel
title_full Comparing enzyme activity modifier equations through the development of global data fitting templates in Excel
title_fullStr Comparing enzyme activity modifier equations through the development of global data fitting templates in Excel
title_full_unstemmed Comparing enzyme activity modifier equations through the development of global data fitting templates in Excel
title_short Comparing enzyme activity modifier equations through the development of global data fitting templates in Excel
title_sort comparing enzyme activity modifier equations through the development of global data fitting templates in excel
topic Biochemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6296338/
https://www.ncbi.nlm.nih.gov/pubmed/30581673
http://dx.doi.org/10.7717/peerj.6082
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