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Single Channel Analysis

Single Channel Analysis. Curso FeSBE - 2019. Bibliografia. Membranes, Channels, and Noise. Eisenberg, R.S.,Frank , M., Stevens, C.F. Introduction. Fluctuation Theory for description of ionic events at the membrane.

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Single Channel Analysis

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  1. Single Channel Analysis CursoFeSBE - 2019

  2. Bibliografia • Membranes, Channels, and Noise. Eisenberg, R.S.,Frank, M., Stevens, C.F.

  3. Introduction • Fluctuation Theory for description of ionic events at the membrane. • Fluctuation Theory was originally developed for statistical fluctuation of ordinary physical quantities: random collisions between gas molecules and walls. Fluctuation theory and noise measurement (natural fluctuations of trnapsort system and those which are the response to an applied stochastic signal)

  4. StevensL Inference about molecular mechanism through Fluctuation Analysis • Worlf at molecular level is chaotic. Random fluctuations in membrane conductance. Channel noise reflects reflects underlying molecular mechanisms

  5. Topics • Fluctuation Analysis • Analysis of single channel behavior • VGl Channels

  6. Characterization of Noise – Spectral Analysis and Covariance FunctionWhole-Cell Current. Hypothesis: Noise is related to channel stochastic gating Spectral Density Function: Fourier Analysis >>> Spectral Density Covariance Function For Simple Molecular Mechanism

  7. Spectral Analysis

  8. Fourier Analysis • Fourier Theorem: Any usual function of time can be decomposed into a sum of sine and cosine waves with various amplitudes T=Noise sample duration y(t)= ampliotude Noise has 0 mean and no frequency above 500

  9. Spectral Density – Sf – For frequency.

  10. f0 : corner or cutoff frequency Σ2 : noise variance Lorentzian function??

  11. Covariance function L: legth of time over which tima average is calculated. For Single molecular mechanism. Τ : characteristic time

  12. Ion-Channel Mechanism: Stochastic Interpretation Shut Open • Ion-Channel mechanism: Reversible transition between states in which tha protein can exist. From experimental observation insight about reaction mechanism – numerical values for the rate constant, for example – can be obtained. Two States α β Ligant Bound Vacant Bound Open K1 K-1 α β

  13. Molecular Mechanism – Hypothesis Differential Equations (probability to find the channels in on of the several states, From the equation covariance is calculated. The Fourier transform of covariance is the Spectrum. The Spectrum derived is compared with experimental data. Shut Open α β

  14. In Stationary Conditions (Two State channel Shut Open f Ξopen steady state probabilitu α β

  15. Covariance Shut Open α β Corner frequency Variance

  16. Covariance/Correlation [C(t) R(t)Power Spectral Density Function (S(f)) • C(t) – Relationship between probabilities of events occurring at a certains time and those occurring before and after that time. Information of data on a time domain. • S(f): Information on data in the frequency domain.

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