Computational biology in the study of cardiac ion channels and cell electrophysiology

Abstract

1. Prologue 582. The Hodgkin–Huxley formalism for computing the action potential 592.1 The axon action potential model 592.2 Cardiac action potential models 623. Ion-channel based formulation of the action potential 653.1 Ion-channel structure 653.2 Markov models of ion-channel kinetics 663.3 Role of selected ion channels in rate dependence of the cardiac action potential 713.4 Physiological implications of IKs subunit interaction 773.5 Mechanism of cardiac action potential rate-adaptation is species dependent 784. Simulating ion-channel mutations and their electrophysiological consequences 814.1 Mutations in SCN5A, the gene that encodes the cardiac sodium channel 824.1.1 The ΔKPQ mutation and LQT3 824.1.2 SCN5A mutation that underlies a dual phenotype 874.2 Mutations in HERG, the gene that encodes IKr: re-examination of the ‘gain of function/loss of function’ concept 944.3 Role of IKs as ‘repolarization reserve’ 1005. Modeling cell signaling in electrophysiology 1025.1 CaMKII regulation of the Ca2+ transient 1025.2 The β-adrenergic signaling cascade 1056. Epilogue 1077. Acknowledgments 1088. References 109The cardiac cell is a complex biological system where various processes interact to generate electrical excitation (the action potential, AP) and contraction. During AP generation, membrane ion channels interact nonlinearly with dynamically changing ionic concentrations and varying transmembrane voltage, and are subject to regulatory processes. In recent years, a large body of knowledge has accumulated on the molecular structure of cardiac ion channels, their function, and their modification by genetic mutations that are associated with cardiac arrhythmias and sudden death. However, ion channels are typically studied in isolation (in expression systems or isolated membrane patches), away from the physiological environment of the cell where they interact to generate the AP. A major challenge remains the integration of ion-channel properties into the functioning, complex and highly interactive cell system, with the objective to relate molecular-level processes and their modification by disease to whole-cell function and clinical phenotype. In this article we describe how computational biology can be used to achieve such integration. We explain how mathematical (Markov) models of ion-channel kinetics are incorporated into integrated models of cardiac cells to compute the AP. We provide examples of mathematical (computer) simulations of physiological and pathological phenomena, including AP adaptation to changes in heart rate, genetic mutations in SCN5A and HERG genes that are associated with fatal cardiac arrhythmias, and effects of the CaMKII regulatory pathway and β-adrenergic cascade on the cell electrophysiological function.