Ion-channel gating mechanisms: model identification and parameter estimation from single channel recordings

1989 ◽  
Vol 236 (1285) ◽  
pp. 385-416 ◽  
Keyword(s):  
Parameter Estimation ◽  
Single Channel ◽  
Channel Gating ◽  
Model Identification ◽  
Simulated Data ◽  
Process Models ◽  
Gating Mechanisms ◽  
Gating Mechanism ◽  
Incorrect Model ◽  
Schwarz Criterion

Patch-clamp data may be analysed in terms of Markov process models of channel gating mechanisms. We present a maximum likelihood algorithm for estimation of gating parameters from records where only a single channel is present. Computer simulated data for three different models of agonist receptor gated channels are used to demonstrate the performance of the procedure. Full details of the implementation of the algorithm are given for an example gating mechanism. The effects of omission of brief openings and closings from the single-channel data on parameter estimation are explored. A strategy for discriminating between alternative possible gating models, based upon use of the Schwarz criterion, is described. Omission of brief events is shown not to lead to incorrect model identification, except in extreme circumstances. Finally, the algorithm is extended to include channel gating models exhibiting multiple conductance levels.

scholarly journals Voltage-dependent Gating of Single Wild-Type and S4 Mutant KAT1 Inward Rectifier Potassium Channels

1998 ◽  
Vol 112 (6) ◽  
pp. 679-713 ◽  
Author(s):  
Paul C. Zei ◽  
Richard W. Aldrich
Keyword(s):  
Kinetic Model ◽  
Potassium Channels ◽  
Single Channel ◽  
Channel Gating ◽  
Inward Rectifier ◽  
Inward Rectification ◽  
Closed State ◽  
Inward Rectifier Potassium Channels ◽  
Gating Mechanism ◽  
Voltage Dependent

The voltage-dependent gating mechanism of KAT1 inward rectifier potassium channels was studied using single channel current recordings from Xenopus oocytes injected with KAT1 mRNA. The inward rectification properties of KAT1 result from an intrinsic gating mechanism in the KAT1 channel protein, not from pore block by an extrinsic cation species. KAT1 channels activate with hyperpolarizing potentials from −110 through −190 mV with a slow voltage-dependent time course. Transitions before first opening are voltage dependent and account for much of the voltage dependence of activation, while transitions after first opening are only slightly voltage dependent. Using burst analysis, transitions near the open state were analyzed in detail. A kinetic model with multiple closed states before first opening, a single open state, a single closed state after first opening, and a closed-state inactivation pathway accurately describes the single channel and macroscopic data. Two mutations neutralizing charged residues in the S4 region (R177Q and R176L) were introduced, and their effects on single channel gating properties were examined. Both mutations resulted in depolarizing shifts in the steady state conductance–voltage relationship, shortened first latencies to opening, decreased probability of terminating bursts, and increased burst durations. These effects on gating were well described by changes in the rate constants in the kinetic model describing KAT1 channel gating. All transitions before the open state were affected by the mutations, while the transitions after the open state were unaffected, implying that the S4 region contributes to the early steps in gating for KAT1 channels.

scholarly journals Spontaneous Channel Activity of the Inositol 1,4,5-Trisphosphate (InsP3) Receptor (InsP3R). Application of Allosteric Modeling to Calcium and InsP3 Regulation of InsP3R Single-channel Gating

2003 ◽  
Vol 122 (5) ◽  
pp. 583-603 ◽  
Author(s):  
Don-On Daniel Mak ◽  
Sean M.J. McBride ◽  
J. Kevin Foskett
Keyword(s):  
Binding Sites ◽  
Single Channel ◽  
Channel Gating ◽  
Quantitative Prediction ◽  
Open Probability ◽  
Release Channel ◽  
Gating Mechanism ◽  
Inhibitory Site ◽  
Type 3

The InsP3R Ca2+ release channel has a biphasic dependence on cytoplasmic free Ca2+ concentration ([Ca2+]i). InsP3 activates gating primarily by reducing the sensitivity of the channel to inhibition by high [Ca2+]i. To determine if relieving Ca2+ inhibition is sufficient for channel activation, we examined single-channel activities in low [Ca2+]i in the absence of InsP3, by patch clamping isolated Xenopus oocyte nuclei. For both endogenous Xenopus type 1 and recombinant rat type 3 InsP3R channels, spontaneous InsP3-independent channel activities with low open probability Po (∼0.03) were observed in [Ca2+]i < 5 nM with the same frequency as in the presence of InsP3, whereas no activities were observed in 25 nM Ca2+. These results establish the half-maximal inhibitory [Ca2+]i of the channel to be 1.2–4.0 nM in the absence of InsP3, and demonstrate that the channel can be active when all of its ligand-binding sites (including InsP3) are unoccupied. In the simplest allosteric model that fits all observations in nuclear patch-clamp studies of [Ca2+]i and InsP3 regulation of steady-state channel gating behavior of types 1 and 3 InsP3R isoforms, including spontaneous InsP3-independent channel activities, the tetrameric channel can adopt six different conformations, the equilibria among which are controlled by two inhibitory and one activating Ca2+-binding and one InsP3-binding sites in a manner outlined in the Monod-Wyman-Changeux model. InsP3 binding activates gating by affecting the Ca2+ affinities of the high-affinity inhibitory sites in different conformations, transforming it into an activating site. Ca2+ inhibition of InsP3-liganded channels is mediated by an InsP3-independent low-affinity inhibitory site. The model also suggests that besides the ligand-regulated gating mechanism, the channel has a ligand-independent gating mechanism responsible for maximum channel Po being less than unity. The validity of this model was established by its successful quantitative prediction of channel behavior after it had been exposed to ultra-low bath [Ca2+].

AMPA and Kainate Receptors

2020 ◽  
Author(s):  
G. Brent Dawe ◽  
Patricia M. G. E. Brown ◽  
Derek Bowie
Keyword(s):  
Ion Channel ◽  
Glutamate Receptor ◽  
Single Channel ◽  
Channel Gating ◽  
Regulatory Proteins ◽  
Kainate Receptors ◽  
Mammalian Brain ◽  
Receptor Field ◽  
Neuronal Excitation ◽  
Ion Channel Proteins

α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and kainate-type glutamate receptors (AMPARs and KARs) are dynamic ion channel proteins that govern neuronal excitation and signal transduction in the mammalian brain. The four AMPAR and five KAR subunits can heteromerize with other subfamily members to create several combinations of tetrameric channels with unique physiological and pharmacological properties. While both receptor classes are noted for their rapid, millisecond-scale channel gating in response to agonist binding, the intricate structural rearrangements underlying their function have only recently been elucidated. This chapter begins with a review of AMPAR and KAR nomenclature, topology, and rules of assembly. Subsequently, receptor gating properties are outlined for both single-channel and synaptic contexts. The structural biology of AMPAR and KAR proteins is also discussed at length, with particular focus on the ligand-binding domain, where allosteric regulation and alternative splicing work together to dictate gating behavior. Toward the end of the chapter there is an overview of several classes of auxiliary subunits, notably transmembrane AMPAR regulatory proteins and Neto proteins, which enhance native AMPAR and KAR expression and channel gating, respectively. Whether bringing an ion channel novice up to speed with glutamate receptor theory and terminology or providing a refresher for more seasoned biophysicists, there is much to appreciate in this summation of work from the glutamate receptor field.

A new imputation-based incomplete data-driven fuzzy modeling for accuracy improvement in ubiquitous computing applications

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sonia Goel ◽  
Meena Tushir
Keyword(s):  
Parameter Estimation ◽  
Missing Data ◽  
Incomplete Data ◽  
Model Identification ◽  
Fuzzy Model ◽  
New Method ◽  
Content Type ◽  
Ubiquitous Environment ◽  
Sugeno Model ◽  
Takagi Sugeno

Purpose In real-world decision-making, high accuracy data analysis is essential in a ubiquitous environment. However, we encounter missing data while collecting user-related data information because of various privacy concerns on account of a user. This paper aims to deal with incomplete data for fuzzy model identification, a new method of parameter estimation of a Takagi–Sugeno model in the presence of missing features. Design/methodology/approach In this work, authors proposed a three-fold approach for fuzzy model identification in which imputation-based linear interpolation technique is used to estimate missing features of the data, and then fuzzy c-means clustering is used for determining optimal number of rules and for the determination of parameters of membership functions of the fuzzy model. Finally, the optimization of the all antecedent and consequent parameters along with the width of the antecedent (Gaussian) membership function is done by gradient descent algorithm based on the minimization of root mean square error. Findings The proposed method is tested on two well-known simulation examples as well as on a real data set, and the performance is compared with some traditional methods. The result analysis and statistical analysis show that the proposed model has achieved a considerable improvement in accuracy in the presence of varying degree of data incompleteness. Originality/value The proposed method works well for fuzzy model identification method, a new method of parameter estimation of a Takagi–Sugeno model in the presence of missing features with varying degree of missing data as compared to some well-known methods.

A New Integrated Algorithm of Structure Determination and Parameter Estimation for Nonlinear Systems Identification

1999 ◽  
Author(s):  
Wang Xiao Wang ◽  
Jianyin Xie
Keyword(s):  
Parameter Estimation ◽  
Nonlinear Systems ◽  
Structure Determination ◽  
Model Identification ◽  
Identification Algorithm ◽  
Householder Transformation ◽  
Systems Identification ◽  
Value Decomposition ◽  
Svd Method ◽  
Nonlinear Systems Identification

Abstract A new integrated algorithm of structure determination and parameter estimation is proposed for nonlinear systems identification in this paper, which is based on the Householder Transformation (HT), Givens and Modified Gram-Schmidt (MGS) algorithms. While being used for the polynomial and rational NARMAX model identification, it can select the model terms while deleting the unimportant ones from the assumed full model, avoiding the storage difficulty as the CGS identification algorithm does which is proposed by Billings et. al., and is numerically more stable. Combining the H algorithm with the modified bidiagonalization least squares (MBLS) algorithm and the singular value decomposition (SVD) method respectively, two algorithms referred to as the MBLSHT and SVDHT ones are proposed for the polynomial and rational NARMAX model identification. They are all numerically more stable than the HT or Givens or MGS algorithm given in this paper, and the MBLSHT algorithm has the best performance. A higher precision for the parameter estimation can thus be obtained by them, as supported b simulation results.

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