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Identification of I(Kr) Kinetics and Drug Binding in Native Myocytes
Determining the effect of a compound on I(Kr) is a standard screen for drug safety. Often the effect is described using a single IC(50) value, which is unable to capture complex effects of a drug. Using verapamil as an example, we present a method for using recordings from native myocytes at several...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Springer US
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2690829/ https://www.ncbi.nlm.nih.gov/pubmed/19353268 http://dx.doi.org/10.1007/s10439-009-9690-5 |
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author | Zhou, Qinlian Zygmunt, Andrew C. Cordeiro, Jonathan M. Siso-Nadal, Fernando Miller, Robert E. Buzzard, Gregery T. Fox, Jeffrey J. |
author_facet | Zhou, Qinlian Zygmunt, Andrew C. Cordeiro, Jonathan M. Siso-Nadal, Fernando Miller, Robert E. Buzzard, Gregery T. Fox, Jeffrey J. |
author_sort | Zhou, Qinlian |
collection | PubMed |
description | Determining the effect of a compound on I(Kr) is a standard screen for drug safety. Often the effect is described using a single IC(50) value, which is unable to capture complex effects of a drug. Using verapamil as an example, we present a method for using recordings from native myocytes at several drug doses along with qualitative features of I(Kr) from published studies of HERG current to estimate parameters in a mathematical model of the drug effect on I(Kr). I(Kr) was recorded from canine left ventricular myocytes using ruptured patch techniques. A voltage command protocol was used to record tail currents at voltages from −70 to −20 mV, following activating pulses over a wide range of voltages and pulse durations. Model equations were taken from a published I(Kr) Markov model and the drug was modeled as binding to the open state. Parameters were estimated using a combined global and local optimization algorithm based on collected data with two additional constraints on I(Kr)I–V relation and I(Kr) inactivation. The method produced models that quantitatively reproduce both the control I(Kr) kinetics and dose dependent changes in the current. In addition, the model exhibited use and rate dependence. The results suggest that: (1) the technique proposed here has the practical potential to develop data-driven models that quantitatively reproduce channel behavior in native myocytes; (2) the method can capture important drug effects that cannot be reproduced by the IC(50) method. Although the method was developed for I(Kr), the same strategy can be applied to other ion channels, once appropriate channel-specific voltage protocols and qualitative features are identified. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10439-009-9690-5) contains supplementary material, which is available to authorized users. |
format | Text |
id | pubmed-2690829 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-26908292009-06-05 Identification of I(Kr) Kinetics and Drug Binding in Native Myocytes Zhou, Qinlian Zygmunt, Andrew C. Cordeiro, Jonathan M. Siso-Nadal, Fernando Miller, Robert E. Buzzard, Gregery T. Fox, Jeffrey J. Ann Biomed Eng Article Determining the effect of a compound on I(Kr) is a standard screen for drug safety. Often the effect is described using a single IC(50) value, which is unable to capture complex effects of a drug. Using verapamil as an example, we present a method for using recordings from native myocytes at several drug doses along with qualitative features of I(Kr) from published studies of HERG current to estimate parameters in a mathematical model of the drug effect on I(Kr). I(Kr) was recorded from canine left ventricular myocytes using ruptured patch techniques. A voltage command protocol was used to record tail currents at voltages from −70 to −20 mV, following activating pulses over a wide range of voltages and pulse durations. Model equations were taken from a published I(Kr) Markov model and the drug was modeled as binding to the open state. Parameters were estimated using a combined global and local optimization algorithm based on collected data with two additional constraints on I(Kr)I–V relation and I(Kr) inactivation. The method produced models that quantitatively reproduce both the control I(Kr) kinetics and dose dependent changes in the current. In addition, the model exhibited use and rate dependence. The results suggest that: (1) the technique proposed here has the practical potential to develop data-driven models that quantitatively reproduce channel behavior in native myocytes; (2) the method can capture important drug effects that cannot be reproduced by the IC(50) method. Although the method was developed for I(Kr), the same strategy can be applied to other ion channels, once appropriate channel-specific voltage protocols and qualitative features are identified. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10439-009-9690-5) contains supplementary material, which is available to authorized users. Springer US 2009-04-08 2009-07 /pmc/articles/PMC2690829/ /pubmed/19353268 http://dx.doi.org/10.1007/s10439-009-9690-5 Text en © Biomedical Engineering Society 2009 |
spellingShingle | Article Zhou, Qinlian Zygmunt, Andrew C. Cordeiro, Jonathan M. Siso-Nadal, Fernando Miller, Robert E. Buzzard, Gregery T. Fox, Jeffrey J. Identification of I(Kr) Kinetics and Drug Binding in Native Myocytes |
title | Identification of I(Kr) Kinetics and Drug Binding in Native Myocytes |
title_full | Identification of I(Kr) Kinetics and Drug Binding in Native Myocytes |
title_fullStr | Identification of I(Kr) Kinetics and Drug Binding in Native Myocytes |
title_full_unstemmed | Identification of I(Kr) Kinetics and Drug Binding in Native Myocytes |
title_short | Identification of I(Kr) Kinetics and Drug Binding in Native Myocytes |
title_sort | identification of i(kr) kinetics and drug binding in native myocytes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2690829/ https://www.ncbi.nlm.nih.gov/pubmed/19353268 http://dx.doi.org/10.1007/s10439-009-9690-5 |
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