RT Journal Article
SR Electronic
T1 Ion channel model reduction using manifold boundaries
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.03.11.483794
DO 10.1101/2022.03.11.483794
A1 Dominic G. Whittaker
A1 Jiahui Wang
A1 Joseph G. Shuttleworth
A1 Ravichandra Venkateshappa
A1 Jacob M. Kemp
A1 Thomas W. Claydon
A1 Gary R. Mirams
YR 2022
UL http://biorxiv.org/content/early/2022/05/16/2022.03.11.483794.abstract
AB Mathematical models of voltage-gated ion channels are used in basic research, industrial and clinical settings. These models range in complexity, but typically contain numerous variables representing the proportion of channels in a given state, and parameters describing the voltage-dependent rates of transition between states. An open problem is selecting the appropriate degree of complexity and structure for an ion channel model given data availability. Here, we simplify a model of the cardiac human Ether-à-go-go Related Gene (hERG) potassium ion channel, which carries cardiac IKr, using the manifold boundary approximation method (MBAM). The MBAM approximates high-dimensional model-output manifolds by reduced models describing their boundaries, resulting in models with fewer parameters (and often variables). We produced a series of models of reducing complexity starting from an established 5-state hERG model with 15 parameters. Models with up to 3 fewer states and 8 fewer parameters were shown to retain much of the predictive capability of the full model and were validated using experimental hERG1a data collected in HEK293 cells at 37°C. The method provides a way to simplify complex models of ion channels that improves parameter identifiability and will aid in future model development.Competing Interest StatementThe authors have declared no competing interest.