Identification of structures for ion channel kinetic models

PLoS Comput Biol. 2021 Aug 16;17(8):e1008932. doi: 10.1371/journal.pcbi.1008932. eCollection 2021 Aug.

Abstract

Markov models of ion channel dynamics have evolved as experimental advances have improved our understanding of channel function. Past studies have examined limited sets of 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 currents and human left ventricular fast transient outward potassium currents. Successful models identified with this approach have certain characteristics in common, suggesting that aspects of the model topology are determined by the experimental data. Incorporating these channel models into cell and tissue simulations to assess model performance within protocols that were not used for training provided validation and further narrowing of the number of acceptable models. The success of this approach suggests a channel model creation pipeline may be feasible where the structure of the model is not specified a priori.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials
  • Animals
  • Biophysical Phenomena
  • Computational Biology
  • Computer Simulation
  • Databases, Factual
  • HEK293 Cells
  • Heart Atria / metabolism
  • Heart Ventricles / metabolism
  • Humans
  • Ion Channels / chemistry
  • Ion Channels / metabolism*
  • Kinetics
  • Markov Chains
  • Mice
  • Models, Cardiovascular*
  • Myocardium / metabolism*
  • Patch-Clamp Techniques
  • Potassium Channels, Voltage-Gated / chemistry
  • Potassium Channels, Voltage-Gated / metabolism
  • Voltage-Gated Sodium Channels / chemistry
  • Voltage-Gated Sodium Channels / metabolism

Substances

  • Ion Channels
  • Potassium Channels, Voltage-Gated
  • Voltage-Gated Sodium Channels