Characterization of Protein Interactions by ITC, SPR and BLI Sangho - - PowerPoint PPT Presentation

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Characterization of Protein Interactions by ITC, SPR and BLI Sangho - - PowerPoint PPT Presentation

Characterization of Protein Interactions by ITC, SPR and BLI Sangho Lee Department of Biological Sciences Sungkyunkwan University Outline Protein interactions: why bother? Calorimetry Optical methods: SPR and BLI Real-life


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Characterization of Protein Interactions by ITC, SPR and BLI

Sangho Lee Department of Biological Sciences Sungkyunkwan University

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Outline

  • Protein interactions: why bother?
  • Calorimetry
  • Optical methods: SPR and BLI
  • Real-life example: hybrid approach
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SLIDE 3

Protein interactions – why bother?

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SLIDE 4

Protein interactions control the lives of cells

Escherichia coli drawn to molecular scale by David Goodsell

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SLIDE 5

Protein interaction network

[Nature (2000)]

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SLIDE 6

Protein interaction types

  • Homologous interactions:
  • The same proteins
  • Oligomers
  • Coiled-coil
  • Amyloids
  • Heterologous interactions:
  • Different proteins
  • Enzyme – inhibitors
  • Antibody – antigen
  • Protein complexes
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SLIDE 7

Protein interactions: qualitative vs. quantitative

Immunoprecipitation (IP) Pulldown Qualitative or semi-quantitative ITC, SPR, BLI Fluorescence anisotropy Quantitative

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SLIDE 8

Low Affinity

Antigen:antibody Weak interactions such as ubiquitin:ubiquitin receptor Most protein interactions

Moderate Affinity High Affinity

Ka < 104 M-1 104 < Ka < 108 M-1 Ka > 109 M-1

Range of binding constants

103 M-1

104 M-1

108 M-1

>109M-1

Protein interactions: binding affinity range

Kd < 10-4 M (mM) 10-4 < Kd < 10-8 M (mM – nM) Kd > 10-9 M (nM)

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SLIDE 9

Dissociation constant: Kd

𝑄 + 𝑀

𝐿𝑏 𝑄𝑀

𝐿𝑏 = 𝑄𝑀 [𝑄] 𝑀 = 𝑙𝑝𝑜 𝑙𝑝𝑔𝑔 𝑄𝑀

𝐿𝑒 𝑄 + 𝑀

𝐿𝑒 = [𝑄] 𝑀 [𝑄𝑀] = 𝑙𝑝𝑔𝑔 𝑙𝑝𝑜

M-1 M

𝐿𝑏 = 1 𝐿𝑒

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SLIDE 10

Isothermal Titration Calorimetry

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SLIDE 11

Enthalpy (ΔH) Binding Affinity (Ka) Heat capacity (ΔCp) Gibbs energy (ΔG) Reaction Stoichiometry (n) Entropy (ΔS)

Thermodynamic Profile

Isothermal titration calorimetry (ITC): Measuring heat

  • Calor (Latin, heat) + metry

(Greek, measure)

  • Direct measurement of heat

q either released or absorbed in molecular binding during gradual titration

  • Label-free measurement
  • Microcalorimeters: as low as

100 μl

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SLIDE 12

ITC theory: Thermodynamics

  • Scenario: a ligand (L) binds to a protein (P) at

temperature T

  • Release of absorption of heat due to binding
  • ΔH0(T) and Ka (therefore Kd) can be determined by

titration

𝑟 = ∆𝐼0 𝑈 𝑜𝑄𝑀 = ∆𝐼0 𝑈 𝑊[𝑄𝑀] 𝑄 + 𝑀

𝐿𝑏 𝑄𝑀

𝑟 = ∆𝐼0 𝑈 𝑊[𝑄𝑈] 𝐿𝑏 𝑀 1 + 𝐿𝑏 𝑀

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ITC theory: Thermodynamics

  • Scenario: a ligand (L) binds to a protein (P) at

temperature T

  • Once you determine ΔH0(T) and Ka (therefore Kd),

ΔG0 and ΔS0 can be calculated.

𝑄 + 𝑀

𝐿𝑏 𝑄𝑀

∆𝐻0 𝑈 = −𝑆𝑈𝑚𝑜𝐿𝑏 ∆𝐻0 𝑈 = ∆𝐼0 𝑈 − 𝑈∆𝑇0 𝑈

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SLIDE 14

Representative instruments

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ITC: Instrument components

  • Exothermic reaction
  • The sample cell becomes warmer than the reference cell.
  • Binding causes a downward peak in the signal.
  • Heat released is calculated by integration under each peak.

[www.Malvern.com]

10 μL 1.4 (or 0.2) mL

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SLIDE 16

ITC: Data analysis

1 𝐿𝑒 ΔH n

[www.Malvern.com]

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ITC: Limitations and competitive binding techniques

Can’t measure tight interactions Ka by direct measurement: 102 M-1 - 109 M-1 Kd (dissociation constant) = 1/Ka

Limits Work-around

[van Holde, Principles of Physical Biochemistry, 2nd Ed. (2006)]

(1) Weak ligand binds to protein (2) Strong ligand displaces weak ligand:protein complex 𝐿𝑏𝑞𝑞 = 𝐿𝑡𝑢𝑠𝑝𝑜𝑕 1 + 𝐿𝑥𝑓𝑏𝑙 𝑀𝑥𝑓𝑏𝑙 Can measure tight interactions Ka by competitive technique: 109 M-1 - 1012 M-1

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SLIDE 18

Protein:protein interaction

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SLIDE 19

Protein:DNA interaction

Mixed-lineage leukemia: A type

  • f

childhood leukemia in which a piece of chromosome 11 has been translocated (broken off and attached itself to another chromosome). Children with this type of leukemia have a particularly poor prognosis (outlook). They do not respond at all well to the standard therapies for ALL (acute lymphoblastic or lymphocytic leukemia) and often suffer from early relapse after chemotherapy. On both the clinical and laboratory levels, chromosome 11 childhood leukemia appears therefore to be a distinctive disease and not a subset

  • f ALL. Armstrong and coworkers (Nature, Jan 2002)

named it "mixed-lineage leukemia.“ [MedicineNet.com] Heat absorbed

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Protein:cofactor interaction

CAP: catabolite activator protein (dimer) cAMP: cyclic AMP

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Protein:protein interaction – HIV Gag p6:Human Alix

[Sangho Lee et al. Nat. Struct. Mol. Biol. (2007)]

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Protein:protein interaction – Rabex-5:Polyubiquitin

[Donghyuk Shin, Sangho Lee et al. (2012) Biochem. Biophys. Res. Commun.]

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Surface plasmon resonance

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Surface plasmon resonance (SPR): Assay objectives

[BiaCore]

ITC SPR BLI SPR BLI

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Surface plasmon resonance (SPR): Theory

[Patching, Biochim. Biophys. Acta (2014)]

  • To measure the refractive index near to a

sensor surface

  • Polarised light is directed through a prism to

the under surface of the gold film where surface plasmons are generated at a critical angle of the incident light.

  • This absorption of light is seen as a decrease

in intensity of the reflected light. Resonance

  • r response units (RU) are used to describe

the increase in the signal, where 1 RU is equal to a critical angle shift of 10

− 4 deg or

10

  • 12 g mm
  • 2.
  • When a steady-state is achieved (all binding

sites occupied), the maximum RU is determined (n: No. of binding sites in Ligand)

𝑆𝑉𝑛𝑏𝑦 = 𝑜𝑆𝑉𝑀 𝑁𝑋

𝐵

𝑁𝑋

𝑀

Ligands

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SLIDE 26

Surface plasmon resonance (SPR): Sensorgram

[BiaCore]

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SLIDE 27

Surface plasmon resonance (SPR): Components

Microfluidics Sensor Chip Detection System

[BiaCore]

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SLIDE 28

Surface plasmon resonance (SPR): Sensor chips

Sensor Chip

CM5

Sensor Chip

CM4

Sensor Chip

C1

Sensor Chip

HPA

Sensor Chip

L1

CM dextran + Lipophilic Tail

Sensor Chip NTA Sensor Chip CM3 Sensor Chip SA Sensor Chip AU

[BiaCore]

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SLIDE 29

Kinetic analysis: Why important?

1 nM 100 pM 10 nM 10 pM 100 nM 1 M 1 mM 100 M 10 M

Kd

kon (M-1s-1)

104 107 106 105 102 103

koff(s-1)

0.0001 0.001 0.01 0.1 1

kon (M-1s-1) koff(s-1)

Kd = A B C

[BiaCore]

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SLIDE 30

Kinetic analysis: Same affinity, different kinetics

Compare sensorgrams for three different interactions

  • Same 1 nM affinity

(Kd)

  • Different kinetics

2 100 4 6 8 h

% blocked target

[BiaCore]

𝐿𝑒 = 𝑙𝑒 𝑙𝑏

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SLIDE 31

Things to consider: Analyte concentration

  • Run analyses over a wide range of analyte concentrations,

ideally 100-fold or more: The range should span 10x below the Kd to 10x above the Kd.

  • Accurate analyte concentration is critical!
  • Include a zero-concentration sample in the analyses.

[BiaCore]

Too high concentration Too low concentration Optimized

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SLIDE 32

Things to consider: Mass transfer

  • If the diffusion rate is slower than the association rate,

mass transfer effects can be observed

  • Low RUL reduces analyte consumption in “no-flow zone”
  • Apparent rate constants are smaller when mass transport

limited binding occurs (inaccurate kinetic data)

  • Work-arounds: higher flow rates, lowest ligand density

Mass transfer limitation No limitation

[BiaCore]

At different flow rates

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SLIDE 33

Things to consider: Conformational changes

  • Conformational changes during interaction may

cause kinetic parameters to change

  • Inject analyte at a fixed concentration
  • Vary contact times
  • Overlay the sensorgrams

Do relative dissociation rates change? If so, a conformational change is occurring. Confirm with other techniques.

[BiaCore]

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Data analysis: Curve fitting in kinetic analysis

kon, koff, and RUmax are calculated by global curve fitting

kon

A + B AB

koff

[BiaCore]

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Data analysis: Steady-state affinity determination

  • Kinetic determinations give an independent value
  • Steady-state response levels give one value for affinity

constants

  • Steady-state can be used for fast interactions where kinetics

are not available

  • ff
  • n

a

k k K 

  • n
  • ff

d

k k K 

Kinetics and affinity Affinity only

[BiaCore]

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SLIDE 36

Data analysis: Steady-state affinity determination

  • Response at equilibrium can be plotted against

the concentration to determine the affinity

  • Response should be at or close to equilibrium

at all concentrations for a reliable measurement

20 20 60 100 140 180 220 260 300 100 200 300 400 500 600 700 800 900 1000 s RU

[BiaCore]

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SLIDE 37

[Sangho Lee et al. (2006) Nat. Struct. Mol. Biol.]

Qualitative and quantitative interaction analysis: Rabex-5 and ubiquitin

A20_ZF MIU

  • Rabex-5: guanine exchange factor (GEF)

for Rab5 in intracellular trafficking

  • Two ubiquitin binding domains: A20_ZF,

MIU

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Biolayer interferometry

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Biolayer interferometry (BLI): Theory

Ligand Analyte Ligand:Analyte

Optical thickness change at the sensor tip due to binding causes wavelength shift Δλ

[ForteBio; Citartan et al. Analyst (2013)]

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BLI: Experimental platforms

[ForteBio]

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BLI: Practical considerations

  • pH Scouting is done for optimal ligand

immobilization on a sensor.

  • Molecular weight of the analyte matters.
  • Choice of data analysis method (kinetic or steady

state) depends on the nature of protein interactions.

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BLI example system: Rabex-5 and polyubiquitin

[Donghyuk Shin, Sei Young Lee, Shuo Ren, Soyoun Kim, Yoshikatsu Aikawa, and Sangho Lee (2012) Biochem. Biophys. Res. Commun.]

Y25A/Y26A A58D GST-Rabex-59-73 N-

  • C
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Experimental design

Linear Ub4 K63-linked Ub4 K48-linked Ub4 GST-Rabex-59-73 N-

  • C

Rabex-59-73 GST

Ligands Analytes

(Ligands)

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Experimental design

Linear Ub4 K63-linked Ub4 K48-linked Ub4 GST-Rabex-59-73 N-

  • C

Rabex-59-73 GST

Ligands Analytes

(Ligands)

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Ligand immobilization: pH Scouting

[Thermo.com]

0.25 μM Linear Ub4

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Ligand immobilization: pH Scouting

0.25 μM Linear Ub4

[Thermo.com]

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Analyte selection: Size matters

GST-Rabex-59-73 N-

  • C

Rabex-59-73

0.25 1.05 Saturation No saturation

0.25 μM K63-linked Ub4

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SLIDE 48

Full sensorgram: Everything optimized

Baseline Activation Loading Quenching Baseline Association Dissociation 0.25 μM Linear Ub4 GST-Rabex-59-73 N-

  • C

GST 10 μM 5 μM 1 μM 0.5 μM 0.1 μM 10 μM

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Full sensorgram: Everything optimized

Baseline Activation Loading Quenching Baseline Association Dissociation 0.25 μM Linear Ub4 GST-Rabex-59-73 N-

  • C

GST 10 μM 5 μM 1 μM 0.5 μM 10 μM

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Data analysis: Kinetic vs. steady-state

Kinetic Steady-state

0.25 μM Linear Ub4 GST-Rabex-59-73 N-

  • C
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Qualitative and quantitative interaction analysis: Rabex-5 MIU domain and polyubiquitin

Y25A/Y26A A58D GST-Rabex-59-73 N-

  • C

[Donghyuk Shin, Sei Young Lee, Shuo Ren, Soyoun Kim, Yoshikatsu Aikawa, and Sangho Lee (2012) Biochem. Biophys. Res. Commun.]

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Qualitative and quantitative interaction analysis: Rabex-5 MIU domain and polyubiquitin

[Yoshikatsu Aikawa, Sangho Lee et al. (2012) J. Biol. Chem.]

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Real-life example: hybrid approach

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Regions between UBZ and LRM of Rad18 Are Involved in Polyubiquitin Recognition

[Notenboom et al. (2007) Nucleic Acids Res.]

DNA binding Ub binding E3 Ub ligase

[Trung Thanh Thach, Namsoo Lee, Donghyuk Shin, Seungsu Han, Gyuhee Kim, Hongtae Kim, and Sangho Lee (2015) Biochemistry]

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SAXS-based model for Rad18(201-240):Linear Ub2

[Trung Thanh Thach, Namsoo Lee, Donghyuk Shin, Seungsu Han, Gyuhee Kim, Hongtae Kim, and Sangho Lee (2015) Biochemistry]

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SLIDE 56

Validation of Rad18(201-240):Linear Ub2 Interaction

[Trung Thanh Thach, Namsoo Lee, Donghyuk Shin, Seungsu Han, Gyuhee Kim, Hongtae Kim, and Sangho Lee (2015) Biochemistry]

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SLIDE 57

Summary

ITC SPR, BLI Affinity range (Kd) nM to sub-mM (pM with competition) nM to low mM Pros

  • Thermodynamic

parameters (ΔG, ΔH, ΔS)

  • No immobilization
  • Kinetic parameters

(kon, koff)

  • “Dirty” samples

possible

  • “Less” sample required

High throughput Cons

  • “More” sample

required

  • Lows to medium

throughput

  • Mass transfer

limitation

  • Immobilization

artifacts