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Thermodynamic modeling of protein separation

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(1)

Thermodynamic modeling of protein separation

Ju Ho Lee Ph. D. Course

(2)

Scope

Roles of thermodynamics in biochemical engineering

Factors in protein purification

Purification of protein

Thermodynamic modeling of protein separation and precipitation.

(3)

Roles

For rational, efficient and rapid

process development and equipment design in bioprocesses.

L(light)=10L/min

H(Heavy)=100L/min

Xo=20g/L X4=0.1g/L

[ Multistage countercurrent liquid extraction of Penicillian-G ]

Organic solvent KD=YL/XH=50

1 stage 2 stage 3 stage 4 stage

(4)

Potential role of thermodynamics

Predictions of product behavior

(aggregation, degradation) given T,pH,I

Predictions of chromatographic behavior based on product properties

Prediction of solvent-product interactions

Prediction of two-phase aqueous extraction via equilibrium

(5)

Factors affecting protein properties

Ionic Strength

pH

Temperature

Solubility

Organic Solvents

Primary, Secondary, tertiary, quarternary structure

(6)

Purification process of protein

Precipitation

Solid-Liquid Equilibria Liquid-Liquid Equilibria

Aqueous two phase system

Polymer-Polymer-protein-Water

Polymer-Salts-protein-Water

(7)

Precipitations.

By adding Salts ((NH4)2SO4, Na2SO4)

log S/So = -Ks(I)

(So : solubility of protein at I=0)

By adding Polymers(PEG, DEX) - reducing the amount of water

acting on protein molecules

(8)

Aqueous two phase systems(I)

Polymer-Polymer-water-protein system

Phase : PEG(Dextran)

Dilute solution of protein i,j,k…, and salt

Phase : Dextran(PEG)

Dilute solution of protein i,j,k…, and salt

(9)

Aqueous two phase systems

Polymer-Salt-water-protein system

Phase : PEG

Dilute solution of protein i,j,k…, and salt

Phase : Phosphate salts

Dilute solution of protein i,j,k…, and salt

(10)

Modeling(I) : Salt-Induced Protein Precipitation

Potentials of mean force for aqueous protein-protein interactions

(C.J.Coen et al, 1995)

W(r) = Wdisp(r) + Wq-q(r) (DLVO)

+ Wq-(r) + W-(r)

+ WOA(r)

(11)

+

= 2 d 3A 10 2

0 1

2 2

dr 1}4π}

T)/kT]

, a W(r, {exp[

) 2 ,

(

hs NA

B T

a B

) (

1 2

2 2 2

,

2 B c By LALLS R M

Kc

w

+

=

θ

(12)

Modeling(I) : Salt-Induced Protein Precipitation

Approach using EOS ( Prausnitz et al, 1996)

Saturated liquid phase

Pure protein phase ( Precipitate)

Saturated liquid phase

Precipitate +

electrolyte + water Assume

LLE

(13)

RPA(Random-Phase Approximation) equation of state

=

+ +

= +

+

=

=

dr r

r W

U pp 2

3

3 2

ref

ref

) ( 4

η) (1

η η

η ) 1

ρkT ( P

2kT ) ρU

ρkT ( P

ρkT Z P

π

Equation of States approach

(14)

Protein-Protein Potential

Wij(r)=Welec(r)+Wdisp(r)+Wosmotic(r)+Wspecific(r)

δ)

0(r

))

r

ε (r)

W

16σ ] r

kT)[1 3r

3 πσ (r) 4

W

r )}

2ln(1 σ r

σ σ

- r { σ 12 (r) H

W

/2) κσ (1

ε 4ππ

)]

σ κ(r (1/r)exp[

e z (r) z

W

ij

ij ij

sp speific

3 s ij, 3 s

ij, s

2 s ij, osmotic

2 2 ij 2

2 ij 2

ij 2

2 ij ij

disp

2 ij r

o

ij 2

j i elec

+

>

=

+

<

<

=

+

=

+

+

=

+

=

δ

(15)

Correlation of experimental supernatant phase protein

a)Hen-egg-white lysozyme in ammonium sulfate

b)a-chymotrypsin in ammonium sulfate

(16)

Modeling(II) :

Protein-Electrolytes

Adsoprtion lattice model(Baskir, 1987)

+ Pitzer long-range electrostatic term

( Qunhua Peng et al,1995 )

1/2 3/2 x LR x

4

2 σ

2 1

σ 1

*

* 4

ρIx 1

I lnγ 2A

kT

) Δμ n

Δμ (n

kT ) ΔU

Ω ln( Ω kT

g lnγ g

= +

− + +

− =

=

(17)

Characteristics of Model

Assumptions

► Protein : neutral molecule

► No electrolyte in the

adsorption layers of protein

► No interaction between

proteins

(18)

Modeling(III) :

Protein-Polymer/electrolyte

Integral-Equation Theory

(C.A. Haynes et al, 1993)

ij ij

ij ij

ij

d r

r h

d r

kT r

u r

C

<

=

>

=

+

+

=

 

1 )

(

/ ) ( )

(

)dr (r'

|)h r' r

(|

C ρ

(r) C

h

k

r

0

ik kj

k ij

ij

(19)

Characteristics of Model

A`Ex = A`Ex,hs+ A`Ex,na+ A`Ex,ic+ A`Ex,cc+ A`Ex,ve

) B , B , m(B m

b, )

c R m(c

) c (c

K'

c M 2B

1 R

Kc

T) , V β

n n RTN

A'

jj ij

ii j

i q

j i

i ii θ w

i

0

i j 0

o

* ij j i Av

EX

i

= +

+ + =

+

=

=

 

(for Polymer and protein)

(Cross osmotic second virial coefficients for macromolecules)

(20)

Comparison between exp and calc

a) PEG3350-Dextran T70-potassium phosphate

b) PEG3350-Dextran T70-potassium chloride

(21)

Conclusion.

현재까지 실제 공정에 적용할 수 있는 정량적인 예측능력을 가진 모델은 없다.

단백질의 상평형을 모사하기 위해서는

계에 존재하는 힘들을 적절하게 묘사하는

항들이 포함되어야 한다.

Lattice fluid를 Bio-separation에 적용하기 위해서는 segment들의 크기를 고려한

항들이 추가되어야 한다.

참조

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