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8&q=von+willebrands+factor+clotting&um=1&ie=UTF- 8&source=og&sa=N&hl=en&tab=wi&biw=987&bih=503 Von.

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Presentation on theme: "8&q=von+willebrands+factor+clotting&um=1&ie=UTF- 8&source=og&sa=N&hl=en&tab=wi&biw=987&bih=503 Von."— Presentation transcript:

1 8&q=von+willebrands+factor+clotting&um=1&ie=UTF- 8&source=og&sa=N&hl=en&tab=wi&biw=987&bih=503 Von Willebrands Factor = protein involved in blood clotting, forms large multimers, binds platelets and vessel wall, subject to large shear forces. How does force affect its interactions?

2 Novel experimental set-up to study effect of force on interaction between A1 and GPIb 

3 Experimental readout of force at which domains separate Note they are watching individual molecules they can repeatedly test the same molecule unbinding and rebinding forces are stochastic

4 Some technical details How long is linker? 43 amino acids,  16nm fully extended Has to be long enough to see rupture Why use DNA “handles”? To keep proteins off surfaces, separate laser trapped bead from rest of assembly, apply force at single point How to attach proteins to DNA? via S-S bonds with extra unique cys in protein and SH in synthetic DNA

5 How does the laser trap work? Idea: refraction changes direction (momentum) of light Since momentum is conserved, bead’s momentum changes by –  p F = -d  p/dt, mainly directed toward most intense part of beam pp for more detailed explanation of trap set-up used here Watch videos at orhttp://tweezerslab.unipr.it

6 Optics – counterpropagating laser traps beam position force Infer bead position from force, knowing stiffness, x=F/k

7 Relation between force and  extension  x = length of “open” A1-linker-GPIb  + DNA - length of A1-GPIb  complex + DNA DNA length should be constant at given F If A1 and GPIb  domains don’t stretch,  x due to extension of flexible aa linker and rot. of A1, GPIb  Bin data by force, show mean and variance of  x at rupture or rebinding Results c/w expected stretch in linker w/force, hence, c/w single tether

8 How does loading rate, F(t), affect d n of unbinding forces? E pulling direction x EE Rate of escape at F=0  e -  E/kT For constant pulling force F, energy barrier decreases by F  x, so rate  e -(  E-F  x)/kT => av. lifetime = e -F(  x/kT) = e -F  xx analysis to determine relationship between probability of unbinding at force f for a given F(t) and the average lifetime at constant force,  (F), which should depend exp’lly on F If F changes with time, F(t), d n of unbinding forces changes, and need careful

9 Dudko-Hummer-Szabo provide this analysis (PNAS 105:15755 (2008)) Relation between p(f) given F(t) and  (F) is: If data grouped into force bins of size  F; h i = p(rupture in i th force bin); in k th bin, F = F 0 +(k-1/2)  F evaluated at F=F 0 +(k-1/2)  F =

10 calculated Obs. p(f) Kim et al observe p(f) at different loading rates, find bimodal distributions at intermediate loading rates, then calculate for each peak according to D-H-S k 1(or2),off =    extrapolated to F=0

11 2 Note ln  (F)  F for each peak as in simple theory Their interpretation: 2 different bound states, each with its own exp’l dependence on F (slope  /kT) and predicted zero force unbinding rate k 1,off, k 2,off 1/k 2,off 1/k 1,off

12 Repeat expts at constant pulling F close to value at which bound/unbound states are equally likely, watch transitions back and forth B UB From these data calculate prob. of staying in bound state for time t

13 Two exponentials at intermediate forces, c/w 2 bound states with different unbinding rates (that are fns of F) straight line => p survival  e -kt ; k = rate of unbinding exp’l survival prob. expected for process with single random event (like radioactive decay)

14 Their model: 2 bound states interconvert at (force- dependent) rates k 12 and k 21 estimated from data Note both bonds are weakened by force (  >0, “slip” rather than “catch”) but conversion to bond with lower k off and smaller  -> tighter binding at high shear (“flex” bond)

15 Ristocetin (antibiotic) and botrocetin (snake venom toxin) are drugs known to affect vWF They promoted conversion to state 2 and decreased response to force (  )

16 Main points Novel set-up to repeatedly measure interaction between 2 protein domains in single protein as function of force Nice “corroboration” of D-H-S theory that relates unbinding force distributions at different loading rates to lifetimes at constant force, with complication that… Their system had bimodal unbinding force distributions at some loading rates. This suggests protein complex exists in 2 different states, each state behaving as expected for simple model with ln(  F  )  F  /kT, but different sensitivities (  ’s) for the 2 states

17 The 2 bound-state model is biologically interesting since it leads to a more graded response to force loading for an interaction naturally subject to comparable forces Will it turn out that many protein interactions have alter- native binding states? Single-molecule pulling experiments reveal complexities of protein interactions that would be hard to see in bulk assays Compared to AFM, newer pulling methods allow study in lower force regime (pN vs nN), and away from surfaces which can -> artifacts

18 Relevance to nanotechnology in other areas methods to detect forces  10pN distance changes  10nm ways to relate rupture-force distributions at different pulling rates to lifetimes at constant force ? interest from ME point of view – combining 2 “slip” bonds with different force sensitivities can mimic “catch” bond (increase in F -> sudden increase in bond strength)


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