Models of the cardiac L‐type calcium current: A quantitative review. Issue 1 (26th August 2022)

• Record Type: Journal Article
• Authors: Agrawal, Aditi; Wang, Ken; Polonchuk, Liudmila; Cooper, Jonathan; Hendrix, Maurice; Gavaghan, David J.; Mirams, Gary R.; Clerx, Michael
• Is Part Of: Wiley interdisciplinary reviews. Volume 15:Issue 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-26
• Subjects: calcium channel -- cellular electrophysiology -- computational model -- L‐type calcium current; Systems biology -- Periodicals; Medicine -- Periodicals; Diseases -- Periodicals; Medicine; Systems biology; Periodicals; 572
• DOI: 10.1002/wsbm.1581
• Languages: English
• ISSNs: 2692-9368

Abstract

Abstract: The L‐type calcium current ( I CaL ) plays a critical role in cardiac electrophysiology, and models of I CaL are vital tools to predict arrhythmogenicity of drugs and mutations. Five decades of measuring and modeling I CaL have resulted in several competing theories (encoded in mathematical equations). However, the introduction of new models has not typically been accompanied by a data‐driven critical comparison with previous work, so that it is unclear which model is best suited for any particular application. In this review, we describe and compare 73 published mammalian I CaL models and use simulated experiments to show that there is a large variability in their predictions, which is not substantially diminished when grouping by species or other categories. We provide model code for 60 models, list major data sources, and discuss experimental and modeling work that will be required to reduce this huge list of competing theories and ultimately develop a community consensus model of I CaL . This article is categorized under: Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Molecular and Cellular Physiology Abstract : We discuss 73 published models of mammalian ICaL and find differences in gating kinetics, electrochemical driving force, and sensitivity to internal calcium concentrations, leading to considerable variability in their predictions.