lecture 7 - aau
TRANSCRIPT
Lecture 7
Data processing in SPRData processing in SPRSurface Reaction Kinetics on a
Bi hiBiochip
Surface plasmon sensor• Principle of affinity SP biosensor
Data processing
• Processing steps:ocess g s eps– zero response to the base line before analyte
injectioninjection– align all responses so that injection starts at the
same pointsame point– subtract the reference cell response – subtract the averaged response to buffer injection
Data processingmeasured response:measured response: receptorreceptor
receptor and reference aligned base
receptor and reference aligned basereferencereference aligned, base line subtractedaligned, base line subtracted
referencereference 4 injections4 injectionsreference subtractedreference subtracted
4 injections averaged + buffer injection
4 injections averaged + buffer injection
data, ready to be analyzeddata, ready to be analyzed
buffer injection subtractedbuffer injection subtracted
Data processing• Software:
– Scrubber2, (Biosensor Tools http://www.cores.utah.edu/Interaction/scrubber.html)ttp // co es uta edu/ te act o /sc ubbe t )
– BiaEvaluation (Biacore AB, Sweden)
General biosensor modelKinetics
Reaction Mass Reactionkinetics
Mass transport
Rates of chemical reactions
Consider reaction:A+2B -> 3C+DTh tThe rates are:
dtBd
dtAd
dtCd
dtDd ][
21][][
31][
−=−==
We can define rate of reaction: ξνξ ddndt
dv jj == ,][
0 -> 3C+D-A-2Bdt
jν
Rate laws
• Rate of reaction is often proportional to the p pconcentration raised to some power, e.g.
ba BAkv ][][=
• Overall order of the reaction: a+b+...order of the reaction with respect to A: a
BAkv ][][
order of the reaction with respect to A: a• Reactions of zero order
kv =
First order reaction close to equilibrium
• Consider reactions:
BA→ABBA
→→
• At equilibrium forward and reverse rates are the same
BdAd ,][][=
eqBkKBkAk
dtdt][
][][
,
' ===eq
eqeq AkKBkAk
][,][][ ' ===
Equilibrium constant
Modeling Molecular Interaction in SPR• The aim: design a model kinetic equation that
describes how amount of ligand-analyte depends on time concentration of anal te and amo nt of freetime, concentration of analyte and amount of free binding sites left.
The signal is proportional to the mass (per unit area) of bound analyte:
mass of the analyte
surface concentration of a complex
Aconst Mξ γ= ⋅ ⋅ 1:1 binding
The maximal signal:
S Aconst Mξ β= ⋅ ⋅
/ /S A
S
ξ βξ ξ γ β=
surface concentration of a ligand
Pseudo-first order Kinetics• For an analyte A (in solution) and a receptor R (immobilized)
ka
d
k
kA R AR⎯⎯→+ ←⎯⎯
• Association rate:
( ) [ ] [ ]0[ ]; ;a
ad k A R RAdγ α β γ α β γ= − = = =( ) [ ] [ ]0
[ ]adtβ γ β γ
• Dissociation rate:
ad
d kdtγ γ= −
• Summing:
( )a dd k kdtγ α β γ γ= − −
• Summing:
( )dt
Pseudo-first order Kinetics• Let’s consider a situation when a concentration of analyte a0 is injected into
the volume V with the surface S.
0V S V constα γ α+ = =
d Sγ ⎛ ⎞( )0a dd Sk kdt Vγ α γ β γ γ⎛ ⎞= − − −⎜ ⎟
⎝ ⎠
• At the equilibrium (when time passed)
kd γγ
( )0
0 eqa
deq eq
kd KSdt kV
γγ
α γ β γ= = =
⎛ ⎞− −⎜ ⎟⎝ ⎠V⎝ ⎠
ka2<ka1K tK=const
Pseudo-first order Kinetics( )0a d
d Sk kdt Vγ α γ β γ γ⎛ ⎞= − − −⎜ ⎟
⎝ ⎠• if the concentration of analyte is high:
( ) ( )0 ; eqaa d
kd k k Kγγ α β γ γ= − − = =( ) ( )0
0
;a dd eqdt k
β γ γα β γ−
Pseudo-first order Kinetics• Equilibrium analysis (not affected by mass transport)
0
(1 )EQ eq K
Kξ γ αξ β
= =+ 0(1 )S Kξ β α+
Other kinetic models• Zero-order reaction following initial binding (conformational
change in AR complex that blocks dissociation)
1 2 *a ak k
k kA R AR AR⎯⎯→ ⎯⎯→+ ←⎯⎯ ←⎯⎯
1 2d dk k← ←
22 1 2 2a d
d k kdtγ γ γ= −
11 0 1 2 1 1 2 1 2 2( )a d a d
dtd k k k kdtγ α β γ γ γ γ γ= − − − − +
• As the total mass is measured by the sensor
1 2/ ( ) /Sξ ξ γ γ β= +
Other kinetic models• Parallel pseudo first-order reactions (e.g. two different
receptors or two different analytes)
1
1 1ak
A R AR⎯⎯→+ ←⎯⎯1
2
2
1 1
2 2
d
a
d
k
k
kA R AR
←
⎯⎯→+ ←⎯⎯2d
[ ] [ ] (1 )R p R pβ β β β= = = = −1 1 2 2
21 0 1 1 1 1
[ ] [ ] (1 )
( )a d
R p R pd k kdt
β β β βγ α β γ γ
= = = =
= − −
12 0 2 2 2 2( )
/ ( ) /
a dd k kdtγ α β γ γ
ξ ξ β
= − −
1 2/ ( ) /Sξ ξ γ γ β= +
Other kinetic models• Multivalent receptor binding:
single receptor binds more than one molecule (e.g. streptavidin, ( g p ,antibodies, triplex formation)
1akA R AR→1
1
2
a
d
a
k
k
A R AR
AR A ARA
⎯⎯→+ ←⎯⎯
⎯⎯→+ ←2dk
AR A ARA+ ←⎯⎯
[ ] [ ] (1 )R Rβ β β β1 1 2 2
22 0 1 2 2
[ ] [ ] (1 )
a d
R p R pd k kdt
β β β βγ α γ γ
= = = = −
= −
11 0 1 2 1 1 2 0 1 2 2( )a d a d
dtd k k k kdtγ α β γ γ γ α γ γ= − − − − +
1 2/ ( 2 ) /Sξ ξ γ γ β= +
Thermodynamics in SPR• change in Gibbs energy can be found from equilibrium
constant:0 lnG RT KΔ = −
• Enthalpy and entropy of the reaction can be found fromEnthalpy and entropy of the reaction can be found from temperature dependence (van’t Hoff equation)
G H T SΔ = Δ − ΔG H T SΔ Δ Δ
• Activation energy for association and dissociation can be found from Arrhenius equation:found from Arrhenius equation:
exp( / )actk P E RT= −
Association/Dissociation in an experiment
Plateau + Span
Plateau
Dissociation:
Response = Span * e-kd* t + PlateauAssociation:
Response = Req * (1 - e -kobs * t)p q ( )
Mass transport effects• In a flow cell:
– flow is laminarvolume flow rate
Reh
ρηΦ
=Reynolds number:
2Re ( / ) 0.998 /h mm sη
= Φ ⋅For water at 20ºC:
flow is laminar for Re<2100.
– velocity profile is parabolic
max32
vhwΦ
=
in a case of no diffusion the transport
( ) ( )x y t y y x y tα α∂ ∂⎛ ⎞
– in a case of no diffusion the transport is by convection
max( , , ) ( , , )4 1x y t y y x y tv
t h h xα α∂ ∂⎛ ⎞= − −⎜ ⎟∂ ∂⎝ ⎠
Mass transport effects• Let’s take into account diffusion
( , , )x y tα∂
2 2
( , , )
( ) ( )
x y tt
x y t x y t
α
α α
∂=
∂⎛ ⎞∂ ∂
2 2
( , , ) ( , , )
( )
x y t x y tDx y
y y x y t
α α
α
⎛ ⎞∂ ∂= + −⎜ ⎟∂ ∂⎝ ⎠
∂⎛ ⎞max
( , , )4 1y y x y tvh h x
α∂⎛ ⎞− −⎜ ⎟ ∂⎝ ⎠
Mass transport effects• Complete model can be solved numerically like
followingg– Navier-Stokes and Convection-Diffusion in the volume, e.g.
2 2( ) ( ) ( ) ( )x y t x y t x y t y y x y tα α α α⎛ ⎞∂ ∂ ∂ ∂⎛ ⎞max2 2
( , , ) ( , , ) ( , , ) ( , , )4 1x y t x y t x y t y y x y tD vt x y h h x
α α α α⎛ ⎞∂ ∂ ∂ ∂⎛ ⎞= + − −⎜ ⎟ ⎜ ⎟∂ ∂ ∂ ∂⎝ ⎠⎝ ⎠
– Reaction kinetics on a biochip
[ ]( , ) ( 0 ) ( ) ( )d x t k t t k tγ β[ ]( , ) ( ,0, ) ( , ) ( , )a dk x t x t k x tdtγ α β γ γ= − −
Boundary condition at the biochip– Boundary condition at the biochip( ,0, ) ( , )x t x tD
tα γ∂ ∂
=∂ ∂y t∂ ∂
SPR case: Mass transfer+Reaction
Simplified model of mass transport A i• Assumptions:– analyte transport in x direction is convective (no diffusion)
2max 1v hPeDl
= >
l it d d ( ) id d li ( l
2( ) ( ) ( )x y t x y t y x y tα α α⎛ ⎞∂ ∂ ∂
– velocity dependence v(y) considered linear (as only area near surface is important)
max2
( , , ) ( , , ) ( , , )4x y t x y t y x y tD vt y h x
α α α⎛ ⎞∂ ∂ ∂= −⎜ ⎟∂ ∂ ∂⎝ ⎠
“two compartment model”: bulk of the channel with– two compartment model : bulk of the channel with convection transport and constant α and layer of thickness hlnext to the sensornext to the sensor.
( )01
Md dkdt h dtα γα α⎡ ⎤= − −⎢ ⎥⎣ ⎦
1/32max1.282M
v Dkhl
⎛ ⎞≈ ⎜ ⎟
⎝ ⎠ldt h dt⎢ ⎥⎣ ⎦ hl⎝ ⎠
Data processing• Software:
– Scrubber2, (Biosensor Tools http://www.cores.utah.edu/Interaction/scrubber.html)ttp // co es uta edu/ te act o /sc ubbe t )
– BiaEvaluation (Biacore AB, Sweden)
Data processing
• Global analysis:Ak
A B AB→
All responses within the data set are fitted to the same
A
DkA B AB⎯⎯→+ ←⎯⎯
– All responses within the data set are fitted to the same values of kA and kD.
– Chi-squared is calculated for all curvesChi squared is calculated for all curves
m A
m D
k k
k kA A B AB⎯⎯→ ⎯⎯→+←⎯⎯ ←⎯⎯mass transfer limited
– conditions to reduce mass transfer effect: low ligand density, high flow rate.
Data processing• Protein-antibody interaction
Best fit usingBest fit using bimolecular model
Best fit using mass-transport model
Thermodynamics for drug discovery
even contribution
entropy driven
enthalpy driven
G H T SΔ = Δ − Δ
large entropy: affinity increases w. temperature
Shuman et al, J.Biomol.Rec.17, p.106 (2004)
Problem
• Derive equations for parallel pseudo first-order e e equa o s o pa a e pseudo s o dereaction kinetics with a single receptor and two different analytesdifferent analytes.