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Lecture 14 Membranes continued Diffusion Membrane transport.

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Presentation on theme: "Lecture 14 Membranes continued Diffusion Membrane transport."— Presentation transcript:

1 Lecture 14 Membranes continued Diffusion Membrane transport

2 From S. Feller Lipid Bilayers are dynamic distributions of phosphate and carbonyl groups and lateral pressure profiles

3 from S. White Distribution of groups along the z-axis

4 Electrostatic potential Electric Double Layer (EDL) Dipole Potential

5 surface pressure  = 70 dyne/cm compressed monolayer surface pressure of the crowding surfactant balances part of the surface tension, thus the apparent surface tension to the left of the barrier is smaller Lipids at air-water interface

6 Irving Langmuir  w -  surf =  surf  surf  w - surface tension of pure water  surf - surface tension in the presence of surfactant  surf  surf – surface pressure of the surfactant dipalmitoyl phosphatidylcholine (DPPC) monolayer-bilyer equivalence pressure 35-40 dyn/cm

7 Schematics for measuring surface potentials in lipid monolayers

8 what’s wrong?

9 Differential Scanning Calorimeter (DSC): Phase transition for DPPC (Dipalmitoyl phosphatidylcholine) http://employees.csbsju.edu/hjakubowski/classes/ch331/lipidstruct/oldynamicves.html For DOPC (oleyl)…-18°C For DPPC (palmytoyl)…+41°C  S =  H/T m

10 Mixtures of phospholipids Two phases www.mpikg-golm.mpg.de/th/people/jpencer/raftsposter.pdf

11 Increases short-range order Broadens phase transition Sizes are wrong?

12 Biochim Biophys Acta. 2005 Dec 30;1746(3):172-85. DOPC/DPPC POPC…palmitoyl, oleyl http://www.nature.com/emboj/journal/v24/n8/full/7600631a.html Phospholipid/ganglioside Lateral Phase Separation

13 Diffusion is a result of random motion which simply maximizes entropy Einstein treatment: c1c1 c2c2 ll but C distance negative slope therefore: but (Fick’s law) (one dimension)

14 y x z 1D 2D 3D l

15 Diffusion = random walk time X, distance Diffusion equation Fick’s law fluxgradient rate

16 Variance Normal distribution Random walk in one dimension D = diffusion coefficient t = time 0.060.040.020 0.040.06 0 20 40 60 80 100 p1x() p2x() p3x() x, cm t = 1 s t = 10 s t = 100 s D = 10 -5 cm 2 /s root-mean-square (standard) deviation x = deviation from the origin Replace: where

17 01234 0 0.5 x,  1.0 0.607 area inside 1  = 0.68 If we step 1 sigma (  ) away from the origin, what do we see? concentration observer

18 x = x 1, x 2, x 3 t = t 1, t 2, t 3 t, s 00.0050.010.0150.020.025 0 20 40 60 80 100 x, cm  = 0.0045 cm  = 0.014 cm  = 0.045 cm t 1 = 1 s t 2 = 10 s t 3 = 100 s An observer sees that the concentration first increases and then decreases 1  is a special point where the concentration of the diffusible substance reaches its maximum 020406080100 0 10 20 30 40 50 60 t = 1 s t = 10 s t = 100 s x = 0.0045 cm x = 0.014 cm x = 0.045 D = 10 -5 cm 2 /s

19 Diffusion across exchange epithelium Einstein eqn: - mean square distance (cm 2 ) D – diffusion coefficient (cm 2 /s) t – time interval (s) “random walk”


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