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Modeling effects of voltage dependent properties of the cardiac muscarinic receptor on human sinus node function

Moss, R. 1; Sachse, F. B.; Moreno-Galindo, E. G.; Navarro-Polanco, R. A.; Tristani-Firouzi, M.; Seemann, G. 1
1 Institut für Biomedizinische Technik (IBT), Karlsruher Institut für Technologie (KIT)


The cardiac muscarinic receptor (M2R) regulates heart rate, in part, by modulating the ace-tylcholine (ACh) activated K⁺ current I$_{K,ACh}$ through dissociation of G-proteins, that in turn activate K$_{ ACh}$ channels. Recently, M2Rs were noted to exhibit intrinsic voltage sensitivity, i.e. their affinity for ligands varies in a voltage dependent manner. The voltage sensitivity of M2R implies that the affinity for Ach (and thus the Ach effect) varies throughout the time course of a cardiac electrical cycle. The aim of this study was to investigate the contribution of M2R voltage sensitivity to the rate and shape of the human sinus node action potentials in physiological and pathophysiological conditions. We developed a Markovian model of the I$_{K,ACh}$ modulation by voltage and integrated it into a computational model of human sinus node. We performed simulations with the integrated model varying Ach concentration and voltage sensitivity. Low Ach exerted a larger effect on I$_{K,ACh}$ at hyperpolarized versus depolarized membrane voltages. This led to a slowing of the pacemaker rate due to an attenuated slope of phase 4 depolarization with only marginal effect on action potential duration and amplitude. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000087606
Veröffentlicht am 22.01.2019
DOI: 10.1371/journal.pcbi.1006438
Zitationen: 13
Web of Science
Zitationen: 11
Zitationen: 12
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Biomedizinische Technik (IBT)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2018
Sprache Englisch
Identifikator ISSN: 1553-734X, 1553-7358
KITopen-ID: 1000087606
Erschienen in PLoS Computational Biology
Verlag Public Library of Science (PLoS)
Band 14
Heft 10
Seiten Art. Nr.: e1006438
Vorab online veröffentlicht am 10.10.2018
Nachgewiesen in Dimensions
Web of Science
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