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Identification of Structures for Ion Channel Kinetic Models

View ORCID ProfileKathryn E. Mangold, Wei Wang, Eric K. Johnson, View ORCID ProfileDruv Bhagavan, View ORCID ProfileJonathan D. Moreno, View ORCID ProfileJeanne M. Nerbonne, Jonathan R. Silva
doi: https://doi.org/10.1101/2021.04.06.438566
Kathryn E. Mangold
1Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
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Wei Wang
2Department of Medicine, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO 63110
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Eric K. Johnson
2Department of Medicine, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO 63110
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Druv Bhagavan
1Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
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Jonathan D. Moreno
1Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
2Department of Medicine, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO 63110
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Jeanne M. Nerbonne
2Department of Medicine, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO 63110
3Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63110
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Jonathan R. Silva
1Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
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  • For correspondence: jonsilva@wustl.edu
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Abstract

Markov models of ion channel dynamics have evolved as experimental advances have improved our understanding of channel function. Past studies have examined various topologies for Markov models of channel dynamics. We present a systematic method for identification of all possible Markov model topologies using experimental data for two types of native voltage-gated ion channel currents: mouse atrial sodium and human left ventricular fast transient outward potassium currents. In addition to optional biophysically inspired restrictions on the number of connections from a state and elimination of long-range connections, this study further suggests successful models have more than minimum number of connections for set number of states. When working with topologies with more than the minimum number of connections, the topologies with three and four connections to the open state tend to serve well as Markov models of ion channel dynamics.

Significance Statement Here, we present a computational routine to thoroughly search for Markov model topologies for simulating whole-cell currents given an experimental dataset. We test this method on two distinct types of voltage-gated ion channels that function in the generation of cardiac action potentials. Particularly successful models have more than one connection between an open state and the rest of the model, and large models may benefit from having even more connections between the open state and the rest of the other states.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted April 06, 2021.
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Identification of Structures for Ion Channel Kinetic Models
Kathryn E. Mangold, Wei Wang, Eric K. Johnson, Druv Bhagavan, Jonathan D. Moreno, Jeanne M. Nerbonne, Jonathan R. Silva
bioRxiv 2021.04.06.438566; doi: https://doi.org/10.1101/2021.04.06.438566
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Identification of Structures for Ion Channel Kinetic Models
Kathryn E. Mangold, Wei Wang, Eric K. Johnson, Druv Bhagavan, Jonathan D. Moreno, Jeanne M. Nerbonne, Jonathan R. Silva
bioRxiv 2021.04.06.438566; doi: https://doi.org/10.1101/2021.04.06.438566

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