CHANNELS, RECEPTORS, AND ELECTRICAL SIGNALING |
Estimation of Ion Channel Kinetics from Fluctuations of Macroscopic Currents
Luciano Moffatt 1*
1 INQUIMAE, CONICET
* To whom correspondence should be addressed. E-mail: lmoffatt{at}qi.fcen.uba.ar.
Submitted on November 15, 2006
Revised on December 11, 2006
Accepted on 1 February 2007
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Abstract |
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For single channel recordings, the Maximum Likelihood Estimation (MLE) of kinetic rates and conductance is well established. A direct extrapolation of this method to macroscopic currents is computationally prohibitive: it scales as a power of the number of channels. An approximated MLE that ignored the local time correlation of the data (Milescu et al 2005; Biophysical Journal 88:2494-2515) has been shown to provide estimates of the kinetic parameters. In this paper an improved approximated MLE that takes into account the local time correlation is proposed. This method estimates the channel kinetics using both the time course and the random fluctuations of the macroscopic current generated by a homogeneous population of ion channels under white noise. It allows arbitrary kinetic models and stimulation protocols. The application of the proposed algorithm to simulated data from a simple 3-state model on non-stationary conditions showed reliable estimates of all the kinetic constants, the conductance and the number of channels and also reliable values for the standard error of those estimates. Compared to the previous approximated MLE, it reduces by a factor of 10 the amount of data needed to secure a given accuracy and it can even determine the kinetic rates in macroscopic stationary conditions.
Key Words:
Hidden Markov Modelling, Kinetics, Markov Chain, Maximum Likelihood Estimation
