title: Maximum likelihood estimation of biophysical parameters of synaptic receptors from macroscopic currents.
abstract: Dendritic integration and neuronal firing patterns strongly depend on biophysical properties of synaptic ligand-gated channels. However, precise estimation of biophysical parameters of these channels in their intrinsic environment is complicated and still unresolved problem. Here we describe a novel method based on a maximum likelihood approach that allows to estimate not only the unitary current of synaptic receptor channels but also their multiple conductance levels, kinetic constants, the number of receptors bound with a neurotransmitter, and the peak open probability from experimentally feasible number of postsynaptic currents. The new method also improves the accuracy of evaluation of unitary current as compared to the peak-scaled non-stationary fluctuation analysis, leading to a possibility to precisely estimate this important parameter from a few postsynaptic currents recorded in steady-state conditions. Estimation of unitary current with this method is robust even if postsynaptic currents are generated by receptors having different kinetic parameters, the case when peak-scaled non-stationary fluctuation analysis is not applicable. Thus, with the new method, routinely recorded postsynaptic currents could be used to study the properties of synaptic receptors in their native biochemical environment.
authors.affiliation: Laboratory of Molecular Biophysics, Bogomoletz Institute of Physiology Kiev, Ukraine ; State Key Laboratory of Molecular and Cellular Biology, Bogomoletz Institute of Physiology Kiev, Ukraine.
authors.forename: Andrey
authors.initials: A
authors.lastname: Stepanyuk
authors.affiliation: Laboratory of Molecular Biophysics, Bogomoletz Institute of Physiology Kiev, Ukraine ; State Key Laboratory of Molecular and Cellular Biology, Bogomoletz Institute of Physiology Kiev, Ukraine.
authors.forename: Anya
authors.initials: A
authors.lastname: Borisyuk
authors.affiliation: Laboratory of Molecular Biophysics, Bogomoletz Institute of Physiology Kiev, Ukraine ; State Key Laboratory of Molecular and Cellular Biology, Bogomoletz Institute of Physiology Kiev, Ukraine.
authors.forename: Pavel
authors.initials: P
authors.lastname: Belan
keywords: Markov chain Monte Carlo; kinetic model; maximum likelihood; peak-scaled non-stationary fluctuation analysis; semiseparable matrix; synaptic currents; unitary current