Isothermal Titration Calorimeter Introduction to iTC200 Content

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Isothermal Titration Calorimeter
Introduction to iTC200
Product Specialist 李宗樹
GE Healthcare Life Sciences
1/
GE /
Content
Basic understanding of ITC…….
• Theory and Principle
• What ITC Can Do
Applications
• Differences between
calorimeters
• Experimental Design
• Operation / Maintenance
Software Analysis
2/
GE /
1
Interactions everywhere
Basic and applied research in the fields of
• Cancer
• Neurobiology
• Immunology
• Infectious diseases
• Functional proteomics
• Cell signaling
• Vaccines
• Selection and characterization of binding reagents
• Drug discovery
and many more….
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Biophysics Increases Data Confidence
and Elucidates Mechanism of Action
1. Confirm stability
Understanding of stability crucial to ensure
suitable conditions for interaction analysis
2. Confirm interactions
Multiple techniques are very useful in
characterizing all aspects of an interaction
Stoichiometries
Interacting pairs or multimeric complexes (N)
Binding strengths
Affinities range from mM to below pM (KA, KD)
Interaction forces
Hydrogen bonds, electrostatic interactions,
hydrophobic effects
Reaction rates
Association rate constants 103 to 109 M-1s-1 (ka)
Dissociation rate constants 10-5 to >1 s-1 (kd)
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2
Workflow for Label-Free
Characterization of Biomolecules
Biomolecule stability -> Interaction analysis and kinetics -> Thermodynamics
MicroCal Isothermal Titration
Calorimetry (ITC) systems
MicroCal Differential Scanning
Calorimetry (DSC) systems
Biacore Surface Plasmon
Resonance (SPR) systems
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Measure and characterize
biomolecule structure, function and activity
Obtain a wide range of critical, binding and stability related data to make your
conclusions and discovery/development decisions with confidence
6 / GE /
3
About Us
Over 40 years on microcalorimetry technology innovator
Inventor for 1st commercial Microcal DSC and ITC
Almost 10000 publish papers (2009)
Acquired by GE in 2008
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History of MicroCal Instruments
1987
2001
VP-DSC
1985
OMEGA
2007
1996
CapDSC
MC-1
PPC
ITC200
MC-2
1975
1977
1985
1995
2005
2008
2000
VP-ITC
1992
MCS
Auto ITC I
1998
2004
Auto ITC 200
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4
Microcalorimetry in life sciences
Two major techniques
Differential scanning calorimetry (DSC)
Isothermal titration calorimetry (ITC)
MicroCal™ VP-DSC
MicroCal™ VP-ITC
MicroCal™ VP-Capillary DSC
MicroCal™ iTC200
MicroCal™ Auto-iTC200
9 / 29-0301-14 AA
Comparison of various ITCs
VPITC
iTC200
Auto-iTC200
Cell material
Hastelloy®
Alloy C 276
Hastelloy®
Alloy C 276
Hastelloy®
Alloy C 276
Operating temperature
range (℃)
2-80
2-80
2-80
Volume for sample cell (μl)
1400+400
200+80
200+80
Volume for syringe (μl)
425
40
40
Throughput (depend on
method, no. of injection…)
2-4 /8 hrs
8-12 /8 hrs
> 22 /day
10 / 29-0301-14 AA
5
Why microcalorimetry?
Label-free
• Direct
measurement of
heat change (ITC)
• Direct
measurement of
melting transition
temperature to
predict thermal
stability (DSC)
Broad dynamic
range
Information rich
• Native
molecules in
solution
(biological
relevance)
• Very sensitive to
accommodate
range of
affinities
• All
thermodynamic
parameters
(affinity,
stochiometry,
enthalphy and
entropy) in a
single ITC
experiment
Ease-of-use
• No labeling or
immobilzation
necessary
• Less assay
development
• Wide range of
solvent/buffer/
sample conditions
NDH, kcal/mole of inject ant
0
-3
-6
-9
-1 2
0
1
2
Xt/M t
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How does the ITC work?
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6
Equilibration
Equilibration
Seeking
First
Titration
Temperature
Injection
without
with Stirring
Stirring
DP
T
Shield
Jacket
5
30
Jacket
Outer Shield
0
T
0
DP
13 /
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MicroCal™ ITC systems
Universal technique based on heat
G = H - TS
G = -R T lnK
Syringe
Reference cell Sample cell
Raw data
Reported data
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7
Microcalorimetry provides a total picture
of binding energetics
Overall binding affinity KD correlates with IC50 or EC50.
This is directly related to ∆G, the total free binding energy
• ∆H, enthalpy is indication of
changes in hydrogen and van
der Waals bonding
• -T∆S, entropy is indication of
changes in hydrophobic
interaction and conformational
changes
-T∆S
∆H
• n, stoichiometry indicates the
ratio of ligand-tomacromolecule binding
G = H -TS
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Spontaneity of binding
ΔH
-TΔS
ΔG = (ΔH)+(-TΔS)
-
-
The process is favored by both enthalpy and
entropy and is spontaneous at all temperatures.
-
+
The process is favored by enthalpy but opposed
by entropy. It is spontaneous only at
temperatures where TS < H.
+
-
The process is opposed by enthalpy but favored
by entropy. It is spontaneous only at
temperatures where TS > H.
+
+
The process is opposed by both enthalpy and
entropy and will not occur spontaneously.
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8
Affinity is just part of the picture
All three interactions have the same binding energy (∆G)
A. Good hydrogen
bonding with
unfavorable
conformational
change
B. Binding
dominated by
hydrophobic
interaction
C. Favorable
hydrogen and
hydrophobic
interaction
G = H –TS
Unfavorable
Favorable
∆G
17 / 29-0301-14 AA
With isothermal titration calorimetry
you can…
Confirm drug binding to target
Measure target activity
Measure enzyme kinetics
MicroCal VP-ITC
Use thermodynamics to guide lead optimization
MicroCal™ iTC200
Get quick KDs for secondary screening/hit validation
Characterize mechanism of action
Validate IC50 and EC50 values
Study quantitative structure–activity relationship (QSAR)
MicroCal Auto-iTC200
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Protein-protein interactions
C-terminal domain of nuclear RNA auxiliary factor
(U2AF65-UHM) binding to spliceosomal component
mutant SF3b155-W7 (shown) or wild-type SF3b155
SF3b155-W7
Wild-type SF3b155
KD (mM)
2.50
2.83
G (kcal/mol)
-7.8
-7.7
H (kcal/mol)
-14.9
-9.4
S (cal/mole/oK)
-23.4
-5.6
Mutant has little impact on affinity but does
impact the interaction
Thickman et al, J. Mol. Biol. 356, 664-683 (2006)
RNA = Ribonucleic acids
∆G = Gibbs free energy
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Protein-DNA interactions
A
B
Energetics of telomere
complex assembly
A.
DNA binding to subunit a
B.
a-DNA complex binding
to subunit b
ITC results confirmed
complex formation
Buczek and Horvath JBC 281 40124-40134 (2006)
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Protein-metal ion interactions
Multiple Binding Sites
Time (min)
µcal/sec
4
-10 0 10 20 30 40 50 60 70 80 90 100
2
Binding of Mn++ to
T5 5’ Nuclease
Mn++ binding is required
prior to DNA binding
0
kcal/mole
2
-2
n = 1.3
Ka = 1.0 x 104 M-1
H = +1.6 kcal mol -1
0
n = 0.85
Ka = 3.0 x 105 M-1
H = -0.59 kcal mol -1
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
Molar Ratio
Feng, et al, Nat. Struct. Mol. Biol. 11, 450-456 (2004)
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Activity vs. Stochiometry
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Measuring Bioactivity with ITC: Affinity
and Stoichiometry
Kcal/mol injectant
0
Protein Quality
50%
“Fully Active”
Measure active
concentrations
-2
Partially
Active
-4
Anti-quinidine antibodies
batches compared
-6
Fully Active
Activity of antibodies
immobilized on metal
beads quantitatively
measured
-8
0.0
0.5
1.0
1.5
2.0
Molar Ratio
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Assessment of protein quality by
MicroCal™ iTC200 system
Peptide binding to protein Batch #1
100% of Batch 1 protein active
based on stoichiometry
Peptide binding to protein Batch #2
23% of Batch 2 protein active
based on stoichiometry
Presented by L.Gao (Hoffmann-La Roche), poster at SBS 2009
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Drug Discovery and Development
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MicroCal™ Auto-iTC200 for confirmation of
binding- eliminating false positives
-1
-1 -1
-1
Compound
N
KD (µM)
∆H (kcal mol )
∆S (cal mol K )
∆G (kcal mol )
GLU IC50 µM
Compound 3
-
-
-
-
-
9*
Compound 4
1
0.38
-8
2.7
-8.9
0.35
Pyrrolidine -1
1
0.29
-22
-44
-9.2
0.52
Pyrrophenone
1
0.15
-14
-16
-9.4
0.13
Bioassay
indicates a
9 µM affinity
ITC indicates a
false positive
Presented by M. Ramarao, at the 2007 Current Trends in Microcalorimetry Conference
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13
Using MicroCal™ Auto-iTC200 to examine
mechanism of interaction
kcal mol-1
of injectant
Inhibitors with similar binding
affinities but different enthalpy
Control titration
Similar KD
Ligand
BCA
n
(µM)
Furosemide
titrations
CBS
titrations
KD
ΔG
ΔH
-TΔS
(µM)
(kcal/mol)
(kcal/mol)
(kcal/mol)
1.28
Acetozolamide
10
0.98 ±.02
0.06
-9.87
-11.15 ±0.46
CBS
30
1.00 ±.04
0.96
-8.21
-10.19 ±0.12
1.98
Furosemide
30
0.98 ±.08
0.92
-8.23
-7.06 ±0.20
-1.17
Sulfanilimide
30
0.99 ±.05
4
-7.35
-7.93 ±0.39
0.58
TFMSA
30
1.03 ±.02
0.35
-8.8
-2.03 ±0.07
-6.77
Different
binding
mechanisms
Molar
ratio
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5000
G
Unfavorable
The Evolution of HIV-1 Protease Inhibitors
-TS
H
-5000
Favorable
12 YEARS
-10000
TMC-114
TMC-126
KNI-764
KNI-272
KNI-577
Atazanavir
Lopinavir
Amprenavir
Ritonavir
Nelfinavir
-20000
Saquinavir
-15000
Indinavir
cal/mol
0
Velazquez-Campoy et al (2003) Current Drug Targets Infectious Disorders, 3 311
Ohtaka et al (2004) Int. J. Biochem. Cell Biol. 36 1787
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Optimizing Diaminopyrimidine Renin
Inhibitors
The Starting Point – A “Weak” Binder
IC50
Kd
∆H
T∆S
= 6.6 μM
= 3.6 μM
= -9.50 kcal/M
= -2.00 kcal/M
Compound 1
The IC50 and Kd are not very exciting, but the ∆H is highly favorable.
Why is that? Can this information help us design a better molecule?
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The Binding Orientation for
Cmpd 1 to Renin was
Determined
by X-ray Crystallography
Compound 1
The favorable ∆H is consistent with the
strong network of H-bonds.
The low IC50 and Kd are consistent with
unoccupied S2 and S3 pockets.
So what do we do now?
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15
Dramatic Improvement in Enzyme
Activity, Binding Affinity and Enthalpy
Compound 1
Compound 2
IC50
= 6,560 nM
IC50
=
691 nM
Kd
= 3,571 nM
Kd
=
535 nM
∆H
= -9.50 kcal/M
∆H
= -14.50 kcal/M
T∆S
= -2.00 kcal/M
T∆S
= - 5.87 kcal/M
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What Was the Result?
Compound 2
Compound 3
IC50
=
691 nM
IC50
=
58 nM
Kd
=
535 nM
Kd
=
79 nM
∆H
= -14.50 kcal/M
∆H
= -10.00 kcal/M
T∆S
= - 5.87 kcal/M
T∆S
= - 0.23 kcal/M
Another 10-fold improvement!
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16
Dissecting the CTB-GM1 Interaction
Evaluate the contribution that each monosaccharide makes to the CTB—GM1
interaction in solution
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Displacement ITC
? Kd
apparent Kd
 Kd
accurate Kd
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17
CTB Displacement Titrations
110 mM
0 mM
25 mM
10 mM CTB
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Summary of ITC Results
Ligand
Kd
DG, kcal/mol
DH, kcal/mol
TDS, kcal/mol
GM1os
43 ± 1.4
nM
-10.04 ± 0.02
-17.45 ± 0.03
-7.4 ± 50.03
GalbOMe
14.8 ± 1.6
mM
-2.5 ± 0.07
-9.0 ± 0.48
-6.53 ± 0.48
GM2os
2.0 ± 0.2
mM
-3.67 ± 0.09
-4.35 ± 0.48
-0.69 ± 0.48
GalGalNAc
7.6 ± 0.8
mM
-2.89 ± 0.08
-10.15 ± 0.43
-7.27 ± 0.45
210 ± 100
mM
-0.92 ± 0.28
-10.7 ± 8.60
-9.77 ± 8.34
Neu5AcaOMe
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18
Novel ITC methods - SIM
Why SIM-Single Injection Method
Rapid data collection
Quick first result
Good for an ITC screen
19
Injection duration
0
The Rest (incl. MIM)
-2
9
-4
-6
720 secs
90 SIM
360 sec
kcal/mole of injectant
甥 al/sec
8
7
180 sec
6
-10
-12
-14
90 sec
5
-8
-16
0.00
3.33
6.67
10.00
13.33
16.67
20.00
23.33
Time (min)
-18
-20
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
Molar Ratio
All systems had 36 mls injected over 90, 180,360 and 720 seconds
RNase Plus 2’CMP (0.57 mM,0.057mM)
Injection duration
c = KA · [M]tot · n
18
17
16
K as % MIM
15
lnK
14
13
12
11
10
9
90
600
C=89
C=241
C=1000
180
400
injection time
c=76
360
200
c=14
720
0
C=4
MIM
8
130
120
110
100
90
80
70
60
50
40
30
20
10
0
injection time
The higher the C value the greater the impact on apparent affinity
20
Comparisons
0
-2
kcal/mole of injectant
-4
-6
-8
3H
AM BSA
BSA
2H
ACZA
-10
-12
-14
-16
-0.2 0.0
0.2 0.4 0.6 0.8
1.0
1.2
1.4
1.6
1.8 2.0
M olar Ratio
100 mM ligand and 10 mM BCAII
Conclusions-SIM
• At an injection rate of 0.1 ul/second (36 ul in 360
seconds) the data was of similar quality to MIM
(1:1 Binding)
• Data quality of SIM experiments was best when the
C value was below 200
• The experiments need a 60 second pre-injection
delay time and about 30 seconds of baseline after
the injection is complete. The total experiment time
is therefore 60+360+30=450 seconds (7.5 minutes).
21
Enzyme Kinetics
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Enzyme Kinetics and ITC
ITC measures thermal power (dQ/dt)
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22
Enzyme kinetics
dQ/dt
ITC measures thermal power (dQ/dt)
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Enzyme Kinetics
Typical concentrations
•Enzyme 25-100 pM
•Substrate 10-100 μM
(2-20 μl per injection;
15-30 injections)
Todd and Gomez, Anal. Biochem. 296, 179-187 (2001)
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23
Continuous injection method
Trypsin catalysed hydrolysis of BAEE and inhibition by benzamidine
9
9 nM Trypsin
8
甥 al/sec
7
9 nM Trypsin
+ 95 mM benzamidine
6
5
4
Final concentration of BAEE = 164 mM
3
0
5
10
15
20
25
30
Tim e (min)
Continuous injection method
0.00035
Rate (millimoles/l/sec)
0.00030
9 nM trypsin + 164 mM BAEE
0.00025
0.00020
9 nM trypsin + 164 mM BAEE
+ 0.1 mM benzamidine
0.00015
0.00010
Km = 5.6 μM
kcat = 36.2 s-1
Ki = 16 μM
0.00005
0.00000
-0.00005
0.00
0.05
0.10
0.15
[S] (mM)
24
Comparison of calorimetric and other
assay data
Todd and Gomez, Anal. Biochem. 276, 179-187 (2001)
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ITC References –Over 3800 papers
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25
Achieving high quality data using
MicroCal™ ITC system
Sample
preparation
Experimental
optimization
The experiment
Data analysis
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Sample preparation
Sample preparation
Experimental
optimization
The experiment
Data analysis
• How much sample is required?
1. Dialyze or buffer exchange proteins
2. Accurately measure protein concentration using A280
3. Ensure that protein and small molecule solutions are
well matched
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26
How much sample is required?
The sample preparation
No  start with 20 µM
protein and 200 µM ligand
Do you know the KD?
Yes  follow the
column for estimated KDs
Estimated KD
µM
[Protein]
µM
[Ligand]
µM
[Protein]*N
/KD= C
<0.5
10
100
>20
0.5-2
20
200
10-40
2-10
50
500
5-25
10-100
30
40*KD
0.3-3
>100
30
20*KD
<0.3
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C value
The sample preparation
0
C = [Protein]*N/KD
-2
C = 5-500 Good
kcal/mole of injectant
-4
C = 10-100 Great
C = 0.05
C = 0.5
-6
-8
-10
C = 1-5 and 500-1000 OK
C=5
-12
C = < 1 and > 1000
-14
C = 50
-16
C = 500
competition or replacement ITC
0.0
0.5
1.0
1.5
2.0
Molar Ratio
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27
Step 1: Dialyze
Sample preparation
•Protein and ligand in identical buffer
•If the ligand is too small for dialysis then dialyze the
macromolecule and then dissolve the ligand in the dialyze
buffer.
2.5
The large peaks were due
to differences in the NaCl
concentration between buffers
2.0
1.5
甥 al/sec
The data shown here shows before
and after dialysis
1.0
0.5
without dialysis
0.0
with dialysis
-0.5
0
20
40
60
80
100
120
140
160
180
Time (min)
65 / 29-0301-14 AA
Step 2: Accurately measure protein and
ligand concentrations
Sample preparation
•Protein concentration should be determined using A280
•Be as accurate as you can weighing the ligand. UV absorption
is better if ligand has a chromophore.
•Some additives may also have absorbance
66 / 29-0301-14 AA
28
Step 3: Match buffers
Sample preparation
The ligand
Dilute an aliquot of the ligand stock solution containing
dimethylsulfoxide (DMSO) with the dialysate and then…
The protein
Add a corresponding amount of DMSO to the protein solution
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Ligand preparation from DMSO stock
Sample preparation
5 mM ligand
in 100% DMSO
50 µl
950 µl
Dialysate
buffer
250 µM ligand
in 5% DMSO
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29
Match DMSO in the protein solution
Sample preparation
25 µM dialyzed
protein
DMSO
50 µl
950 µl
1 ml of 23.75 µM
protein in 5% DMSO
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DMSO mismatch
20% DMSO into
20% DMSO-same stock
7
6
甥 al/sec
5
2% DMSO into
2% DMSO –from different stocks
2% DMSO into
0% DMSO
A: Matched solution: both cell & syringe have same solution (280 m l DMSO added to 14 ml buffer).
B: Slightly mismatched solution: syringe: 20 ml DMSO added to 1.0 ml buffer;
cell: 280 ml DMSO added to 14 ml buffer.
C: 2 % mismatch in DMSO: syringe: 20 ml DMSO added to 1.0 ml buffer; cell: buffer only (no DMSO).
4
3
2
1
0
-5
0
5
10
15
20
25
30
35
40
45
50
55
Time (min)
30
pH mismatches
Sample preparation
• pH mismatches can arise when using high concentrations of
ligand i.e. mM concentrations and above
• Increase the buffer concentration until the ligand charge does
not change the pH
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Choice of buffer
Sample preparation
•ITC is robust, almost all buffers can be used e.g. HEPES, PBS,
glycine, acetate
•Use conditions in which your protein is “happy”
•If reducing agent is required, it is best to use
– Tris (2-carboxyethylphosphine) hydrochloride (TCEP)
(TCEP is not stable in phosphate buffer)
– β-mercaptoethanol (BME)
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31
The experiment
Sample preparation
Experimental
optimization
The experiment
Data analysis
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Clean the cell
The experiment
11.00
10.50
甥 al/sec
10.00
Rinse with 20% Contrad™
(14% Decon™) and water
9.50
9.00
8.50
8.00
0.00
10.00
20.00
30.00
40.00
50.00
Time (min)
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32
Typical run parameters for
MicroCal™ iTC200 system
Injection parameters
•Volume: typical 2 µl (range 0.1-38 µl)
– An initial injection of 0.5 µl is made followed by 19 * 2 µl injections
•Duration: 4 seconds
•Spacing: typical 150 seconds
•Filter period: 5 seconds, it’s the time span of data acquisition
for data averaging
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Typical run parameters for
MicroCal™ iTC200 system
•Reference power: 5 to 10 µcals/sec
•Stir speed: 1000 rpm
•Feedback: High
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33
The control experiment
The experiment
•Water-water, or buffer-buffer:
confirm cell and syringe are clean, injection system OK,
instrument functioning
•Ligand into buffer, and buffer into protein under the same
experimental conditions :
measure heat of dilution, check for buffer match – any other
sources of heat change?
Don’t forget the DMSO if that is used in the buffer or stock solution!
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Data analysis
Sample preparation
Experimental
optimization
The experiment
Data analysis
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34
Experimental optimization
Sample preparation
Experimental
optimization
The experiment
Data analysis
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Case study: Bovine carbonic anhydrase II
(BCAII) binding to 6 ligands
Experimental optimization
•Wide affinity range
– 5 nM to 10 µM
•Wide enthalpy range
– -5 to -14 kcals/mol
•All measurements performed in 50 mM HEPES buffer, pH 7.4
and 5% DMSO
80 / 29-0301-14 AA
35
Guidelines for high quality data
Experimental optimization
Heat of injection
• >2.5 µcals for the second (first full) peak is ideal
• ~1 µcals for second peak is minimum heat
C value
• >1 and <1000
– Best between 5 and 500
• If C < 5 then heat should be >2.5 µcals
81 / 29-0301-14 AA
Ethoxylamide and ACZA data
Experimental optimization
0.0
-2.0
~ 5 to 6 µcals
-1
kcal mol of injectant
-4.0
10.50
200 M ACZA into 20 M BCAII
10.40
10.30
ACZA
C ~ 250
-6.0
-8.0
-10.0
-12.0
10.20
-14.0
10.10
0.0
0.5
1.0
1.5
2.0
Molar Ratio
9.90
9.80
0.0
9.70
-2.0
9.60
9.50
kcal mol-1 of injectant
甥al/sec
-16.0
10.00
200 M Ethoxylamide into 20 M BCAII
9.40
0.00
10.00
20.00
30.00
40.00
Time (min)
Ethoxylamide
C ~ 1150
-4.0
-6.0
-8.0
-10.0
-12.0
-14.0
0.0
0.5
1.0
1.5
2.0
Molar Ratio
82 / 29-0301-14 AA
36
Ethoxylamide optimization
Experimental optimization
Time (min)
0
10
20
30
40
50
60
Ethoxylamide
70
0.00
• Heat of first full injection was
0.7 µcals. This is low, underestimate
the DH by ~10 % but rewarded by a
good C value.
甥 al/sec
-0.02
-0.04
-0.06
kcal mol-1 of injectant
-0.08
0.0
• KD is 6 nM, C = 880.
Great, at least 2 data points in the
transition region.
-2.0
-4.0
-6.0
-8.0
-10.0
-12.0
0.0
0.5
1.0
1.5
2.0
Molar Ratio
37 * 1 µl injections of
50 µM Ethoxylamide
into 5 µM protein
Reduced concentrations and
injection volume
83 / 29-0301-14 AA
CBS and furosemide data
Experimental optimization
0.0
10.60
kcal mol-1 of injectant
-2.0
200 M CBS into 20 M BCAII
10.50
10.40
~ 5 µcals
CBS
C ~ 22
-6.0
-8.0
-10.0
-12.0
10.20
0.0
10.10
0.5
1.0
1.5
2.0
Molar Ratio
10.00
~ 3 µcals
9.90
0.0
200 M Furosemide into 20 M BCAII
9.80
0.00
10.00
20.00
30.00
40.00
50.00
-2.0
-1
Time (min)
kcal mol of injectant
甥 al/sec
10.30
-4.0
No need for optimization
Furosemide
C ~ 36
-4.0
-6.0
-8.0
0.0
0.5
1.0
1.5
2.0
Molar Ratio
84 / 29-0301-14 AA
37
Sulfanilimide and AMBSA data
Experimental optimization
-2.0
-1
kcal mol of injectant
-3.0
10.20
Sulfanilimide
C~2
-4.0
-5.0
-6.0
200 M sulfanilimide into 20 M BCAII
-7.0
~ 2.5 µcals
-8.0
0.0
0.5
1.0
1.5
2.0
Molar Ratio
10.00
-1.0
~ 1 µcals
kcal mol-1 of injectant
9.90
200 M AMBSA into 20 M BCAII
9.80
0.00
10.00
20.00
30.00
40.00
50.00
Time (min)
AMBSA
C~2
-2.0
-3.0
0.0
0.5
1.0
1.5
2.0
Molar Ratio
85 / 29-0301-14 AA
Sulfanilimide optimization
Experimental optimization
18 * 2 µl injections of
500 µM Sulfanilimide
into 50 µM protein
Sulfanilimide
•Heat is 7.4 µcals - good
•KD is 8 µM
•C = 6
-2.0
kcal mol-1 of injectant
甥 al/sec
10.10
-4.0
Increased concentrations
-6.0
0.0
0.5
1.0
1.5
2.0
Molar Ratio
86 / 29-0301-14 AA
38
AMBSA optimization
Experimental optimization
18 * 2 µl injections of
500 µM AMBSA into
50 µM protein
AMBSA
•Heat is 4.8 µcals - good
0.0
kcal mol-1 of injectant
•KD is 10 µM
•C = 5
-2.0
Increased concentrations
-4.0
0.0
0.5
1.0
1.5
2.0
Molar Ratio
87 / 29-0301-14 AA
Session summary
• Good sample preparation gives good data: ’Good in-Good out’
• Optimize sample concentration for the affinity
– Most experiments will work well with 20 µM protein and 200-250 µM
ligand
88 / 29-0301-14 AA
39
Experimental Tips
• Conc. in cell: 20~50 μM
• Conc. In syringe: [M]*n*10~20
• Buffer exchange, check pH-buffer match
• Fill cells without bubbles
• Clean cell and syringe thoroughly
• Do control experiment
108 /
GE /
Thank you for your attention
109 /
GE /
40
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