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The evolution of model cardiac ion electrophysiology

MAR 31, 2023
Computational models advance the understanding of cardiac health and disease.
The evolution of model cardiac ion electrophysiology internal name

The evolution of model cardiac ion electrophysiology lead image

The electrical conduction system of the heart allows for around 100,000 beats a day. While this system typically works as intended, small deviations in a single gene that encodes an ion channel can lead to deadly rhythm disturbances. Computational modeling of how these changes affect complex physiologies has increased the understanding of cardiac electrophysiology and arrhythmia therapy.

Jonathan Moreno and Jonathan Silvia reviewed recent cutting-edge methods to model ion channel electrophysiology and the application of these models to understand disease mechanisms and drug therapies.

“Even though the field has evolved over decades, starting in the 1950s, there have been some exciting new directions that have emerged in the last several years,” said Silvia.

The earliest computational models were based on a giant squid action potential and described the cellular flow of three ions represented with circuit diagrams. As these models gained detail over time, methods were developed to improve the efficiency of their integration on limited computational resources. As computational resources and methods have evolved, so have these electrophysiological models.

The authors also discuss the evolution of the Markov model and its connection to molecular dynamics methods used to study nanoscale movements of proteins. Today, many models are becoming fully automated, widely available, and can represent molecular movements with computational algorithms.

“The new developments that we have highlighted open up many new directions including how to allow computers to create cardiac models, automatically, improve how predictive models can be, and introduce nanoscale details,” said Silva.

Source: “Emerging methods to model cardiac ion channel and myocyte electrophysiology,” by Jonathan D. Moreno and Jonathan R. Silva, Biophysics Reviews (2023). The article can be accessed at https://doi.org/10.1063/5.0127713 .

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