Single Molecule Dynamics & Crossing Membranes Flashcards
Single Molecule Dynamics
Overview
- diffusion of single molecules is a key process in biological materials
- thermal energy, kb*T, is effective at keeping the objects in motion and in randomising their direction
How can there be well-ordered structures and controlled processes in this random environment?
- strong interactions, interactions»_space; kb*T, but this would then require a mechanism to break the strong bonds in order for rearrangment to occur
- non-equilibrium processes, system is maintained out of equilibrium via external fields or chemical energy (ATP) which allows them to avoid reaching thermal equilibrium
- statistical physics, each particle moves randomly and is subject to unpredictable randomisation by kb*T, BUT the collective statistical behaviour is entirely predictable
Why is diffusion important in cells?
- diffusion allows molecules to move without doing work
- it allows molecules to find each other e.g. enzymes-substrates, proteins-proteins, communication through ions/signalling molecules/proteins, drug-target sites
Single Molecule Diffusion
- molecules move because other molecules keep bumping into them
- individual molecules follow a random walk due to these collisions
- Brownian motion
- diffusion is the collective motion of many molecules, many random walks by many molecules
Random Walks
Definition
-at each time step, randomly pick a direction and move one unit in that direction
Random Walks
Mean Displacement
E[x(N)] = 0
Random Walks
Mean Square Displacement
E[x(N)²] = NL²
- where L is the step distance
- as becomes large, the distribution approaches Gaussian with mean 0 and variance NL²
Diffusion as a Function of Time
N = t/Δt
-where N is the number of steps, t is the total time and Δt is the time step
=>
E[x(N)²] = NL² = t/Δt * L²
Diffusion in Cells
-extend random walk to 2D and 3D = 2mDt -where is the mean square displacement -and D is the diffusion constant -and m is the spatial dimension (1D,2D,3D)
Diffusion Examples for Different Dimensions
1D - proteins along DNA
2D - lipids / proteins in membranes
3D - ions / proteins within and outside cells
Stokes-Einstein Equation
D = kb*T / [6π η(T) rH]
- where η(T) is the viscosity
- and rH is the hydrodynamic radius of the molecule
Diffusion Inside Cells vs in Water
- diffusion is slower inside cells
- the viscosity of the cytoplasm is non-uniform
- cells are highly crowded meaning there is a large excluded volume
Composition of Cells
-in weight: 70% water 15% proteins 6% RNA 4% small molecules 2% phospholipids 2% polysaccarides 1% DNA
Mean Separation Between Proteins in a Crowded Environment
= [N/V]^(-1/3)
- N is the number of molecules
- V is the total cell volume
Typical Protein Size
3nm-20nm
Factors Affecting Protein Diffusion
- collisions with crowders
- hydrodynamic interactions
- attractive interactions
- immobile barriers (membranes)
- sieving effects
- spatial heterogeneity (different areas of the cell with differnet densities of different proteins)
Molecular Crowding - Excluded Volume
- excluded volume is the space that the centre of the probe molecule can’t reach
- this depends on the radius of the probe molecule, Rp, and the radius of background molecules, Rb
How do we measure the diffusion constant?
- track proteins tagged with fluorescent molecules or track fluorescent molecules directly
- three main techniques:
- -fluorescence correlation spectroscopy (FCS)
- -fluorescence recovery after photobleaching (FRAP)
- -single particle tracking
Fluorescence Correlation Spectroscopy (FCS)
- excites volume of space with laser
- as molecule enters this region it is excited and fluoresces
- molecules move in and out of the region by diffusion, this can be measured by measuring the intensity of the fluorescing molecules
- apply autocorreltation
- use τD = r²/4D to find D