Parameter Optimization for Ion Channel Models: Integrating New Data with Known Channel Properties

• Published in: Methods in molecular biology (Clifton, N.J.) Vol. 2385; p. 353
• Main Authors: Navarro, Marco A, Amirshenava, Marzie, Salari, Autoosa, Milescu, Mirela, Milescu, Lorin S
• Format: Journal Article
• Language: English
• Published: United States 2022
• Subjects: Ion Channels - metabolism; Kinetics; Models, Biological; Software; Prior knowledge; Kinetic mechanism; Markov model; Model constraints; Kinetic parameters; Ion channel
• ISSN: 1940-6029
• DOI: 10.1007/978-1-0716-1767-0_17

Ion channels play a central role in membrane physiology, but to fully understand how they operate, one must have accurate kinetic mechanisms. Estimating kinetics is not trivial when the mechanism is complex, and a large number of parameters must be extracted from data. Furthermore, the information contained in the data is often limited, and the model may not be fully determined. The solution is to reduce the number of parameters and to estimate them in such a way that they not only describe well the new data but also agree with the existing knowledge. In a previous study, we presented a comprehensive formalism for estimating kinetic parameters subject to a variety of explicit and implicit constraints that define quantitative relationships between parameters and describe specific mechanism properties. Here, we introduce the reader to the QuB software, which implements this constraining formalism. QuB features a powerful visual interface and a high-level scripting language that can be used to formulate kinetic models and constraints of arbitrary complexity, and to efficiently estimate the parameters from a variety of experimental data.