Markov, fractal, diffusion, and related models of ion channel gating. A comparison with experimental data from two ion channels

M. S P Sansom, F. G. Ball, C. J. Kerry, R. McGee, R. L. Ramsey, P. N R Usherwood

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87 Scopus citations

Abstract

The gating kinetics of single-ion channels are generally modeled in terms of Markov processes with relatively small numbers of channel states. More recently, fractal (Liebovitch et al. 1987. Math. Biosci. 84:37–68) and diffusion (Millhauser et al. 1988. Proc. Natl. Acad. Sci. USA. 85:1502–1507) models of channel gating have been proposed. These models propose the existence of many similar conformational substrates of the channel protein, all of which contribute to the observed gating kinetics. It is important to determine whether or not Markov models provide the most accurate description of channel kinetics if progress is to be made in understanding the molecular events of channel gating. In this study six alternative classes of gating model are tested against experimental single-channel data. The single-channel data employed are from (a) delayed rectifier K+ channels of NG 108–15 cells and (b) locust muscle glutamate receptor channels. The models tested are (a) Markov, (b) fractal, (c) one-dimensional diffusion, (d) three-dimensional diffusion, (e) stretched exponential, and (f) expo-exponential. The models are compared by fitting the predicted distributions of channel open and closed times to those observed experimentally. The models are ranked in order of goodness-of-fit using a boot-strap resampling procedure. The results suggest that Markov models provide a markedly better description of the observed open and closed time distributions for both types of channel. This provides justification for the continued use of Markov models to explore channel gating mechanisms.

Original languageEnglish (US)
Pages (from-to)1229-1243
Number of pages15
JournalBiophysical Journal
Volume56
Issue number6
DOIs
StatePublished - 1989

Funding

The corresponding PDF is then generated by the standard methods. This work was supported by grants from the UK SERC (to Drs. Sansom, Ramsey, and Usherwood) and the Wellcome Trust (to Dr. Sansom).

ASJC Scopus subject areas

  • Biophysics

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