A computational study of ion conductance in the KcsA K(+) channel using a Nernst-Planck model with explicit resident ions

• Published in: The Journal of chemical physics Vol. 131; no. 21; p. 215101
• Main Authors: Jung, Yong-Woon, Lu, Benzhuo, Mascagni, Michael
• Format: Journal Article
• Language: English
• Published: United States 07.12.2009
• Subjects: Bacterial Proteins - metabolism; Computer Simulation; Electric Conductivity; Ions - metabolism; Models, Biological; Potassium - metabolism; Potassium Channels - metabolism; Streptomyces lividans - metabolism
• ISSN: 1089-7690
• DOI: 10.1063/1.3268774

The biophysical mechanisms underlying the relationship between the structure and function of the KcsA K(+) channel are described. Because of the conciseness of electrodiffusion theory and the computational advantages of a continuum approach, the Nernst-Planck (NP) type models, such as the Goldman-Hodgkin-Katz and Poisson-NP (PNP) models, have been used to describe currents in ion channels. However, the standard PNP (SPNP) model is known to be inapplicable to narrow ion channels because it cannot handle discrete ion properties. To overcome this weakness, the explicit resident ions NP (ERINP) model was formulated, which applies a local explicit model where the continuum model fails. Then, the effects of the ERI Coulomb potential, the ERI induced potential, and the ERI dielectric constant for ion conductance were tested in the ERINP model. The current-voltage (I-V) and current-concentration (I-C) relationships determined in the ERINP model provided biologically significant information that the traditional continuum model could not, explicitly taking into account the effects of resident ions inside the KcsA K(+) channel. In addition, a mathematical analysis of the K(+) ion dynamics established a tight structure-function system with a shallow well, a deep well, and two K(+) ions resident in the selectivity filter. Furthermore, the ERINP model not only reproduced the experimental results with a realistic set of parameters, but it also reduced CPU costs.