Structural proteomics lecture 4: Biophysical dissection of protein complexes

1. Structural proteomics lecture 4:Biophysical dissection of protein complexes • “Protein complexes and their interactions are the basis of all biology” • True understanding of cellular processes requires understanding of the underlying molecular mechanisms • BUT… molecules should not be seen in isolation!

2. T cell Surface Composition T cell Surface Organisation

3. or One ab per complex Dimer of heterodimers e.g. a key complex: the T cell receptor What’s in the complex – how is it assembled? Need to understand this to know how it can signal. How does it bind its ligand – how is it so specific? What is the effective range of affinities? etc etc

4. Biophysical in vitro techniques to dissect protein complexes & their interactions • AUC • SPR • ITC • FRET / BRET • Single molecule microscopy (?)

5. 1. AUC (Analytical Ultracentrifugation)

6. What is Analytical Ultracentrifugation for? The measurement of properties of molecular species such as mass and shape constants and their alteration with concentration (e.g. during self-association or multi-component assembly) Why use Analytical Ultracentrifugation ? The possible mechanisms of protein complex function will often be limited by its organisation: AUC can assess complex size and degree of self-association as well as giving a measure of monodispersity of in vitro reagents.

7. Ultracentrifugation • Preparative • separate complex mixtures • fractionate cellular components • density gradients to separate by molecular mass • Analytical • sedimentation equilibration • Thermodynamic • Absolute MW • Shape independent • Aggregation • Protein-protein interactions • sedimentation velocity • Hydrodynamic • Relative MW • Molecular shape • Aggregation behavior

8. Theory: The Svedberg equation • Consider a particle m in a centrifuge tube filled with a liquid. • The particle (m) is acted on by three forces: • FC: the centrifugal force • FB: the buoyant force (Archimedes principle) • Ff: the frictional force between the particle and the liquid • Will reach constant velocity where forces balance:

9. Theory: The Svedberg equation • Define s, the sedimentation coefficient: s = • s is a constant for a given particle/solvent, has units of seconds, but use Svedberg (S) units (10–13 s). • Cytochrome s=1S, ribosome s=70S, composed of 50S and 30S subunits (sdoes not vary linearly with Mr) • Values for most biomolecules betwwen 1 and 10000 S

10. Theory: The Svedberg equation S = D = diffusion coefficient, N = Avogadro’s number or (Because Mr = Nm0) • Therefore can directly determine Mr in solution by measuring physical properties of the particle (s and v) under known experimental conditions (D, T and r), • c.f. PAGE, chromatography – comparative & non-native

11. Equipment • E.g. Beckman XL-A (or XL-I) analytical ultracentrifuge • Samples loaded into special centrifuge cells with transparent windows for optical measurements. • The distribution of solute molecules during the experiment is monitored by an optical system. The cells are scanned across their entire radius and data automatically collected for subsequent analysis

12. 1A. Equilibrium sedimentation • Moderate centrifuge speed • After sufficient time, an equilibrium is reached between sedimentation & diffusion, resulting in a montonic solute distribution across the cell Meniscus Cell bottom • Non-linear curve fitting can rigorously determine: • the solution molecular weight • association state • equilibrium constant for complex formation

13. Equilibrium sedimentation – monomer-dimer equilibrium • Data for transferrin at three loading concentrations. All three datasets were fit simultaneously to a monomer-dimer equilibrium model. The fit returned a Kd of about 100 mM for the dimerization.  • The relatively small and randomly distributed residuals indicate that the model provided a good fit to the data.

14. Experimental considerations • Wavelength for detection (280nm – 230nm) • Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl • Tris buffer can be used at 280 nm. (interferes at 230 nm) • If a reducing agent is needed, b-mercaptoethanol is better than dithiothreitol as it doesn’t absorb at 280 nm. • Protein concentration • Ensure detection at wavelength chosen • Sufficient range to detect association • Temperature • Equilibrium time – typically 18-24 hours • depends on length of cell, viscoity etc. • Rotor Speed

15. Rotor speed selection chart

16. 12 mm 3 mm Data collection • Sample preparation: Dialyze against buffer, scan from 350 to 200 nm to test for contaminants & test for aggregation by micro-centrifugation. • Sample loading: Reference cell side by side with sample, with slightly more volume (105ul c.f. 100ul). If using multiple chambers, place most concentrated sample closest to the center of rotation. • Calibration: radial & wavelength calibration on first use or rotor change • Experiment: set vacuum, temperature & speed and read every 2-3 hours, two identical readings = equilibrium, repeat at further speeds. • Stability test: check equilibrium again after an additional 10-12 hour spin • Baseline: Repeat reading at very high speeds when all solute at base.

17. Data analysis • Editing the raw data • Baseline correction • Test mass recovery • Data modeling

18. Editing raw data • Remove the meniscus • Remove the bottom of the cell • Remove the bumps and spikes

19. Baseline correction • Deplete all macromolecular components using v. high speeds • Record baseline absorbance • Subtract this from observed absorbances Test mass recovery Initial absorbance x volume of the sample = total mass • Integration of experimental plot of absorbance vs squared radial position is used to monitor recovery of total mass • Large loss of mass after an increase in the speed suggests occurrence of aggregation/precipitation • An increase in recovery at higher speed is suggestive of breakdown of the molecules

20. d ln(c) 2RT d r2w2 Mp(1- ) = Data modeling • A plot of ln(c) vs r2 should be a straight line with a slope proportional to molecular weight Single ideal homogeneous species

21. Curvature in log plots • Indicates heterogeneity of the system • Arises from self-association of protein • Slope at any radial position is proportional to the weight average molecular weight Residuals • Start of with a single component model and execute a fit • Ideally you should have a residuals like in panel (a). • If residuals systematically vary, try another model!

22. 19K 26K 31K 40K Lymphotactin 40 ºC, 100 mM NaCl 10 ºC, 200 mM NaCl little or no curvature obvious curvature – mass also lost after spin

23. Direct fitting:Self association at 10 ºC & 200 mM NaCl

24. Effect of salt & temperature on aggregation 10 ºC, 200 mM NaCl 40 ºC, 100 mM NaCl

25. Affinity/avidity and function in costimulation Bivalency: stabilizes complexes ~100-fold But are B7-1 and B7-2 really different (proposed from crystals) ?

26. Importance of valency: Dimerization of sB7-1 6 5 Mw,app(Da/104) 4 3 sB7-1 2 0 1.0 2.0 Protein concentration (mg/ml)

27. 80 80 60 60 40 40 20 20 0 0 0 0 1 1 2 2 3 3 4 4 Importance of valency: sB7-2 & LICOS are monomers sLICOS sB7-2 Mw(kDa) Mw(kDa) Concentration (mg/ml) Concentration (mg/ml)

28. 1B. Velocity sedimentation • High centrifuge speed • Forms a sharp boundary between solute depleted region (at top) and a region of uniform solute concn(at bottom) • The concentration gradient (dc/dr) defines the boundary position • Non-linear curve fitting can rigorously determine: • number of mass species • molecular weight • shape information for a molecule of known mass

29. sedimentation coefficient (s) is the rate at which the sedimentation boundary moves • depends on the molecular weight & shape • globular (more spherical) protein has the largest sedimentation coefficient for a given molecular weight • unfolded or elongated proteins experience more friction -- smaller sedimentation coefficients • diffusion coefficient is related to minimum width of the sedimentation boundary, multiple species broaden the boundary beyond effects of diffusion alone Velocity sedimentation - data analysis

30. Velocity sedimentation - data analysis g(s*) distribution

31. Velocity sedimentation - data analysis • This antibody gives only one distinct peak, centered at s ~ 6.5 S, which corresponds to the native antibody 'monomer‘. This is low for a 150 kDa species due to its highly asymmetric 'Y' shape. • However, a more detailed analysis quickly reveals that this sample is not homogeneous. The red curve is a fit of these data as a single species. It does not match the data in the region from 8-12 S, indicating the presence of some multimer. • From the width of the main peak we can calculate the apparent diffusion coefficient (D) of the monomer. From the ratio of s to D we can calculate a mass of 151 kDa for this species, which matches the known value well within 3-5% error expected for masses determined in this fashion.

32. The example of SLAM (CD150) • Claimed to self-associate with nM Kd raising serious problems for all known models of cell surface protein interactions. • Equilibrium data couldn’t be fitted – concentrations too high! • Velocity data confirmed shape of complex and approximate strength of association

33. 2. SPR / BIAcore (Surface Plasmon Resonance)

34. What is Surface Plasmon Resonance for? The accurate measurement of the properties of inter-molecular interactions without a wash step. (Contrast with interaction screens and crude measurements of bond strength e.g. AUC or washed systems like ELISA) Why use Surface Plasmon Resonance? A full understanding of the function of proteins requires accurate knowledge of the nature of their interactions.

35. The range of affinities seen for transient interactions at the cell surface Selectins Inactive LFA-1 fully active LFA-1 fully active Mac-1 SLAM CD28 CD8 TCR CD4 rCD2 hCD2 KIR CTLA-4 Ab:Ag 1000 100 10 1 0.1 3D Kd (mM)

36. BIAcore Why use Surface Plasmon Resonance? A full understanding of the function of proteins requires accurate knowledge of the nature of their interactions. Example: Costimulation vs. Inhibition (again!) B7.1 and B7.2 both bind to CD28 and CTLA-4. BUT B7.2 & CD28 are constitutively expressed, others on activation B7.1 is dimeric, B7.2 is not CD28, although dimeric, is monovalent CTLA-4 binds its ligands much more strongly than CD28 B7.1 binds its ligands more strongly than B7.2 RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times more stable than the costimulatory B7.2:CD28 complex.

37. Dip in light intensity Principle of Surface Plasmon Resonance Angle of ‘dip’ affected by: 1) Wavelength of light 2) Temperature 3) Refractive index n2

38. Surface Plasmon Resonance in the BIAcore

39. Basic Idea… • NB 4 channels (‘flow cells’) per ‘chip’ • 2 steps: • Immobilisation: • Stick something (or up to 3 things) to the chip(NB also stick a control down) • Inject analyte: • Inject something else and see if it binds, how much binds and how fast it binds

40. Direct: Indirect: Immobilisation • 2 Main options: • Direct: • Covalently bind your molecule to the chip • Indirect: • First immobilise something that binds your molecule • with high affinity e.g. streptavidin / antibodies

41. Immobilisation: Carboxymethyl binding CM5 Sensor Chip N.B. Carboxymethyl groups are on a dextran matrix: This is negatively charged => Need to do a “preconcentration” test to determine optimum pH for binding (molecule needs to be +ve)

42. SA NTA HPA Immobilisation: Other sensor chips

43. pH: 4.0 4.5 5.0 5.5 A B C D 15,400 RU Pre-concentration: An antibody was diluted in buffers of different pH and injected over an non-activated chip. Maximum electrostatic attraction occurs at pH 5 • Immobilisation: • Inject 70ml 1:1 EDC:NHS • Inject 7ml mAb in pH5 buffer (in this case @370mg/ml) • Inject 70ml Ethanolamine • Inject 30ml 10mM Glycine pH2.5 Sensorgrams (raw data)

44. Sensorgrams – ligand binding

45. Specific response in red flowcell Response in control / empty flowcell due to viscosity of protein solution injected – therefore ‘control’ response DOES increase with concentration (this is NOT binding!!) Measured response Is it specific? “Specific” Binding • Each chip has four ‘flow-cells’ • Immobilise different molecules in each flow-cell • Must have a ‘control’ flowcell • ‘Specific binding’ is the response in flow-cell of interest minus response in the control flowcell

46. Equilibrium Binding Analysis N.B. Measurement of affinities etc. should usually be done at physiological temperature (i.e. 37°C), although this is more difficult. Sometimes 25°C data can be used to compare fold differences in binding or to test for any binding at all (i.e. specificity studies).

47. Scatchard plot: rearrangement of binding isotherm to give a linear plot. Not so good for calculating Kd, as gives undue weight to least reliable points (low concentration) Plot Bound/Free against Bound Gradient = 1/Kd Equilibrium Binding Analysis - continued Binding curve can be fitted with a Langmuir binding isotherm (assuming a 1:1 binding with a single affinity)

48. Kinetics Harder Case: 2B4 binding CD48

49. Potential pitfalls • Protein Problems: Aggregates (common) Concentration errors Artefacts of construct • Importance of controls: Bulk refractive index issues Control analyte Different levels of immobilisation Use both orientations (if pos.) • Mass Transport: Rate of binding limited by rate of injection: kon will be underestimated • Rebinding: Analyte rebinds before leaving chip koff will be underestimated • Last two can be spotted if measured kon and koff vary with immobilisation level (hence importance of controls)

50. van’t Hoff analysis: Gradient Intercept Less common applications 1. Temperature dependence of binding