Lise Arleth, Professor - EMBL Hamburg · 2012-08-03 · EMBO course in Beijing, April-May, 2011 Dias 1 Calorimetry and its applications to Biological Molecules Lise Arleth, Professor

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

EMBO Course, Beijing, April-May, 2011 Dias 2

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

Antoine de Lavoisier’s equipment ~1780

Life processes are a type of combustion


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).


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 Insulator

Heat conductor

Thermo-electric element

HEAT S

INK

HEAT

SIN

K


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


Experimental setups: DSC and ITC ITC DSC

Shoe-box sized instruments

200 µL Sample 500 µL

Sample


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


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


Differential Scanning Calorimetry


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


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 equationd lnKd(1

T)= −

ΔHo

R⇒

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

€

ln K2

K1

⎛

⎝ ⎜

⎞

⎠ ⎟ = −

ΔHm

R1T2−1T1

⎡

⎣ ⎢

⎤

⎦ ⎥

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


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


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


DSC and lipid phase diagrams


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

So does pressure – Le chateliers principle!


Isothermal Titration Calorimetry


Isothermal titration calorimetry:

€

€

Qpeak,i =V ⋅ ΔH⋅ ΔLi = the area under the i' th peakV : Sample volumeΔH : The characteristic binding enthalpy for the reactionΔLi : 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


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


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


Air Water

Surfactants and the critical micellar concentration (CMC)

Ln (Concentration)

Sur

face

ten

sion

, γ

(mJ/

m2 )

Air Water

Critical micellar concentration


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


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


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”


Complementarity between SANS/SAXS and ITC

SANS Very detailed structural information can be obtained

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


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


SDS concentration

Plot as a function of

SDS-BSA Molar ratio

Vary BSA concentration


Concentration dependence of titration scans Identify characteristic points


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

Slope gives binding number

EMBO Course, Beijing, April-May, 2011 Dias 29 Realistic ?

Binding Isotherm determined from ITC


Performed SANS measurements along the titration scan

A B C

A: Specific binding

E

B: ?

C: ?

D: ?

E: Saturation

D


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)


Binding Isotherm determined from ITC and from SANS

So our ITC point-plot-method gives the same

binding isotherms as we obtain from SANS


Thermodynamic finger print and structure of surfactant protein complexes

A B C

A: Strong Specific binding

E

B: Strong increase of Cfree – Weak increase

of binding number

C: 1st unfolding,

Size of complex and

Cfree increases

D: 2nd unfolding Further elongation of 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


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 often 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 obtain a very detailed quantitative understanding of the SDS-Induced protein unfolding

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Lise Arleth, Professor - EMBL Hamburg · 2012-08-03 · EMBO course in Beijing, April-May, 2011 Dias 1 Calorimetry and its applications to Biological Molecules Lise Arleth, Professor