Lise Arleth, Professor BioNano-Science Group, University of - - PowerPoint PPT Presentation

EMBO course in Beijing, April-May, 2011 Dias 1

Calorimetry and its applications to Biological Molecules

Lise Arleth, Professor

BioNano-Science Group, University of Copenhagen, Faculty of Life Sciences Denmark

Thanks to Prof. Peter Westh, RUC, for several of the slides in this talk

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Calorimetry is (probably) one of the oldest analytical techniques??

Antoine de Lavoisier’s equipment ~1780

Life processes are a type of combustion

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Measuring principles

Detect temperature - calculate heat, Q (=ΔΕ+PΔV=ΔH) For constant pressure, P: heat=enthalpy change (ΔH). For constant volume, V: heat=internal energy change (ΔE).

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Measuring nano-J heats !

All biocalorimeters are “coffe cup” instruments (i.e. measure ΔH rather than ΔE) – (So we allow the sample volume to change slightly) Two (simple) principles:

Insulator

Insulato r

Heat conductor

Thermo- electric element

HEAT SINK HEAT SINK

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Two types of calorimeters dominate biochemical applications

Differential Scanning Calorimetry (DSC) Isothermal Titration Calorimetry (ITC) DSC ITC

Measures the heat that is required to linearly increase temperature, T Measures heat of mixing (titrand into titrate) Constant composition – temperature perturbed Constant Temperature – composition perturbed Applications: Protein denaturation phase transitions Applications: Ligand binding, Critical micellar concentrations Protein-surfactant interactions

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Experimental setups: DSC and ITC

ITC DSC Shoe-box sized instruments

200 µL Sample 500 µL Sample

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Scanning and Isothermal calorimetry

DSC:

Measures energy required to maintain a constant heating rate (=Cp)

ITC:

Measures energy change of mixing (reaction at constant temperature)

P + L ↔ PL

2’ CMP and 3’CMP binding to RNase

Campoy & Freire 2005

State 1 ↔ State 2

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Bio-calorimetry The pro’s and con’s of application

PRO Universally applicable No probe/no special sample preparation Quantitative Non specific CON No structure information Moderate sensitivity Low through-put Non specific

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Differential Scanning Calorimetry

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Assumption: N  D K= [D]/[N] Tm: Temperature where K=1 ([D]=[N] ΔH: Enthalpy of transition (total area using “step” shaped baseline) ΔS°: At Tm: ΔG°=0 hence ΔS°=ΔH/T ΔCp : D-N difference in heat capacity. dΔH/dT=ΔCp

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Check your assumption: The Van´t Hoff analysis

Divide the peak area into T-partitioned slices Determine the equilibrium constant at each temperature E.g. At 50°C: fraction denatured = red area/total area Native fraction (total area-red area)/total area Hence: K(50°C)= red area/(total area – red area)

Van't Hoff equation dlnK d(1T) = − ΔH o R ⇒

Plot calculated ln(K) values against 1/T. The slope is -ΔH°/R

ln K2 K1 ⎛ ⎝ ⎜ ⎞ ⎠ ⎟ = − ΔHm



R 1 T2 − 1 T

1

⎡ ⎣ ⎢ ⎤ ⎦ ⎥

If the Van’t Hoff analysis does not give you this, then your assumptions must be wrong (two-state model, baseline or ?)

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The protein folding problem

Molecular interpretations of DSC thermograms

• Hydrophobic driving forces
• Cooperative units
• Quantitative interpretations of mutation-effects
• Docking and ”structural thermodynamics”
• Has led to an significant part of our current

(fragmentary) knowledge on the protein folding process

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Interactions of proteins and other molecules affects the thermogram

The binding of a ligand to the native state brings about stabilization – The dicplacement of the peak along with the change in transition enthalpy quantifies the binding strength

2’ CMP binding to RNase

Campoy & Freire 2005

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DSC and lipid phase diagrams

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Alcohols depress the main (Pβ – Lα) phase transition temperature

So does pressure – Le chateliers principle!

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Isothermal Titration Calorimetry

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Isothermal titration calorimetry:

Qpeak,i = V⋅ ΔH⋅ ΔLi = the area under the i'th peak V : Sample volume ΔH : The characteristic binding enthalpy for the reaction ΔLi : The increase in number of saturated binding sites ΔLi = P

[ ] ×

Ka L

[ ]i

1+ Ka L

[ ]i

− Ka L

[ ]i−1

1+ Ka L

[ ]i−1

⎛ ⎝ ⎜ ⎞ ⎠ ⎟

Which allows for determining the binding constant, Ka

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Limitations of measurements

Window of binding strength typically 103-109 M-1 Use Competition-binding assays to get up to 1012 M-1 Too strong Perfect Difficult Too weak

Advantages of ITC measurements

High resolution Fast Several binding parameters in one trial

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Surfactants (=detergents)

• Amphiphilic
• Selforganize into micelles

when surfactant concention exeeds critical Monomer Concentration (cmc) Proteins

• Hierachical structure
• Folded / Unfolded

+ = ?

Elaborated ITC Example: Protein-surfactant interactions Collaboration with P. Westh, L. Lundby-Hansen

Practical relevance: Detergent Enzyme industry

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Air Water Surfactants and the critical micellar concentration (CMC) Ln (Concentration) Surface tension, γ (mJ/m2) Air Water Critical micellar concentration

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ITC – Typical data set: -As obtained in Prof. Peter Westh’s Lab., Denmark

HiC protein (an enzyme) titrated with the detergent SDS Raw data ITC data

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Critical micellar concentration

Demicellization versus temperature

ΔHdemic = 0 at 22ºC CMCSDS = 2.2 mM at 22ºC Buffer: 50 mM TRIS, 2 mM EDTA, pH=7

ΔHdemic is T-dependent => We can “contrast- match” it out at a given temperature

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ITC-scans of protein-surfactant interactions at 22 C SDS-HiC (Humicola insolens pisi cutinase) SDS-BSA (Bovine Serum Albumin)

Data suggest that there is more information than Tanfords ”Each g protein binds 1.4 g SDS”: ”Thermodynamic fingerprint”

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Complementarity between SANS/SAXS and ITC

SANS Very detailed structural information can be

• btained

Time consuming, requires large facility, 1 sample takes 2 hours at the SANS-II at PSI. Data analysis may be relatively complicated ITC Measures of enthalpy of surfactant-protein interactions. ”Thermodynamic fingerprint” Small laboratory based instrument, 1 full titration scan takes about 3-6 hours No structural information

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Focus: SDS:BSA system and its thermodynamic finger print. At the very beginning ….. A B C

A: Specific binding

E

B: ? C: ? D: ? E: Saturation

D

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SDS concentration Plot as a function of SDS-BSA Molar ratio Vary BSA concentration

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Concentration dependence of titration scans Identify characteristic points

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Intercept at [BSA]=0 gives free monomer concentration at given point, Slope gives binding number

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Realistic ?

Binding Isotherm determined from ITC

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Performed SANS measurements along the titration scan A B C

A: Specific binding

E

B: ? C: ? D: ? E: Saturation

D

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SANS data (pure sds, pure bsa and mixtures)

BSA SDS BSA:SDS MR=50

I(q) p(r):

Pair Distance Distribution function

Step 1: Use this for determining the forward Scattering I(0), (via IFT)

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Binding Isotherm determined from ITC and from SANS So our ITC point-plot-method gives the same binding isotherms as we obtain from SANS 

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Thermodynamic finger print and structure

• f surfactant protein complexes

A B C

A: Strong Specific binding

E

B: Strong increase of Cfree – Weak increase

• f binding number

C: 1st unfolding, Size of complex and Cfree increases D: 2nd unfolding Further elongation

• f complex, Cfree

increases weakly E: Saturated complexes, monomers and micelles

D

Nbinding at saturation: 210 SDS per BSA, =0.9 g SDS per g BSA

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Closing remarks

Practically any physical or chemical process absorbs or releases heat – hence it can be followed by calorimetry. If the qualitative# nature of the process is known, calorimetry is often effective and easy to use. If it is not, the method is

• ften useless.
• # E.g. a structural, general or molecular understanding of the

process ⇒ Structural and calorimetric methods are very strong in combination ! For example SANS and ITC can be used in combination to

• btain a very detailed quantitative understanding of the SDS-

Induced protein unfolding