holzhutter

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Abstract
Cellular functions are ultimately linked to metabolic fluxes brought about by thousands of chemical reactions and transport processes. The synthesis of the underlying enzymes and membrane transporters causes the cell a certain 'effort' of energy and external resources. Considering that those cells should have had a selection advantage during natural evolution that enabled them to fulfil vital functions (such as growth, defence against toxic compounds, repair of DNA alterations, etc.) with minimal effort, one may postulate the principle of flux minimization, as follows: given the available external substrates and given a set of functionally important 'target' fluxes required to accomplish a specific pattern of cellular functions, the stationary metabolic fluxes have to become a minimum. To convert this principle into a mathematical method enabling the prediction of stationary metabolic fluxes, the total flux in the network is measured by a weighted linear combination of all individual fluxes whereby the thermodynamic equilibrium constants are used as weighting factors, i.e. the more the thermodynamic equilibrium lies on the right-hand side of the reaction, the larger the weighting factor for the backward reaction. A linear programming technique is applied to minimize the total flux at fixed values of the target fluxes and under the constraint of flux balance (= steady-state conditions) with respect to all metabolites. The theoretical concept is applied to two metabolic schemes: the energy and redox metabolism of erythrocytes, and the central metabolism of Methylobacterium extorquens AM1. The flux rates predicted by the flux-minimization method exhibit significant correlations with flux rates obtained by either kinetic modelling or direct experimental determination. Larger deviations occur for segments of the network composed of redundant branches where the flux-minimization method always attributes the total flux to the thermodynamically most favourable branch. Nevertheless, compared with existing methods of structural modelling, the principle of flux minimization appears to be a promising theoretical approach to assess stationary flux rates in metabolic systems in cases where a detailed kinetic model is not yet available.

Unit definitions have no effect on the numerical analysis of the model. It remains the responsibility of the modeler to ensure the internal numerical consistency of the model. If units are provided, however, the consistency of the model units will be checked.

Name Definition
Id Name Spatial dimensions Size
default_compartment 3.0 1.0
Id Name Initial quantity Compartment Fixed
ADPf 0.25 default_compartment
AMPf 0.0 default_compartment
ATPf 0.25 default_compartment
DHAP 0.1492 default_compartment
E4P 0.0063 default_compartment
Fru16P2 0.0097 default_compartment
Fru6P 0.0153 default_compartment
GSH 3.1136 default_compartment
GSSG 0.0004 default_compartment
Glc6P 0.0394 default_compartment
GlcA6P 0.025 default_compartment
Glcin 4.5663 default_compartment
Glcout 5.0 default_compartment
GraP 0.0061 default_compartment
Gri13P2 0.0005 default_compartment
Gri23P2f 2.0601 default_compartment
Gri2P 0.0084 default_compartment
Gri3P 0.0658 default_compartment
Lac 1.6803 default_compartment
Lacex 1.68 default_compartment
MgADP 0.1 default_compartment
MgAMP 0.0 default_compartment
MgATP 1.4 default_compartment
MgGri23P2 0.5 default_compartment
Mgf 0.8 default_compartment
NAD 0.0653 default_compartment
NADH 0.0002 default_compartment
NADPHf 0.004 default_compartment
NADPf 0.0 default_compartment
P1NADP 0.0 default_compartment
P1NADPH 0.024 default_compartment
P1f 0.0 default_compartment
P2NADP 0.0 default_compartment
P2NADPH 0.024 default_compartment
P2f 0.0 default_compartment
PEP 0.0109 default_compartment
PRPP 1.0 default_compartment
Phi 0.9992 default_compartment
Phiex 1.0 default_compartment
Pyr 0.084 default_compartment
Pyrex 0.084 default_compartment
Rib5P 0.014 default_compartment
Rul5P 0.0047 default_compartment
Sed7P 0.0154 default_compartment
Xul5P 0.0127 default_compartment

Initial assignments are expressions that are evaluated at time=0. It is not recommended to create initial assignments for all model entities. Restrict the use of initial assignments to cases where a value is expressed in terms of values or sizes of other model entities. Note that it is not permitted to have both an initial assignment and an assignment rule for a single model entity.

Definition
Id Name Objective coefficient Reaction Equation and Kinetic Law Flux bounds
v_1 Glcout = Glcin

Vmaxv0/KMoutv0*(Glcout-Glcin/Keqv0)/(1+Glcout/KMoutv0+Glcin/KMinv0+alfav0*Glcout*Glcin/KMoutv0/KMinv0)
v_10 v_10 Gri23P2f = Gri3P + Phi

Vmaxv9*((Gri23P2f + MgGri23P2) - Gri3P/Keqv9)/((Gri23P2f + MgGri23P2) + K23P2Gv9)
v_11 Gri3P = Gri2P

Vmaxv10*(Gri3P - Gri2P/Keqv10)/(Gri3P + K3PGv10*(1 + Gri2P/K2PGv10))
v_12 Gri2P = PEP

Vmaxv11*(Gri2P - PEP /Keqv11)/(Gri2P + K2PGv11*(1+PEP/KPEPv11))
v_13 v_13 PEP + MgADP = Pyr + MgATP

Vmaxv12*(PEP*MgADP - Pyr*MgATP/Keqv12)/((PEP + KPEPv12)*(MgADP + KMgADPv12)*(1 + L0v12*((1 + (ATPf+MgATP)/KATPv12)^4)/(((1 + PEP/KPEPv12)^4)*((1 + Fru16P2/KFru16P2v12)^4))))
v_14 Pyr + NADH = Lac + NAD

Vmaxv13*(Pyr*NADH-Lac*NAD/Keqv13)
v_15 Pyr + NADPHf = Lac + NADPf

kLDHv14*(Pyr*NADPHf - Lac*NADPf/Keqv14)
v_16 MgATP = MgADP + Phi

kATPasev15*MgATP
v_17 MgATP + AMPf = MgADP + ADPf

(Vmaxv16/(KATPv16*KAMPv16))*(MgATP*AMPf - MgADP*ADPf/Keqv16)/((1+MgATP/KATPv16)*(1+AMPf/KAMPv16) + (MgADP+ADPf)/KADPv16 + (MgADP*ADPf)/((KADPv16)^2))
v_18 v_18 Glc6P + NADPf = GlcA6P + NADPHf

Vmaxv17/KG6Pv17/KNADPv17*(Glc6P*NADPf - GlcA6P*NADPHf/Keqv17)/(1 + NADPf*(1+Glc6P/KG6Pv17)/KNADPv17 + (ATPf+MgATP)/KATPv17 + NADPHf/KNADPHv17 + (Gri23P2f + MgGri23P2)/KPGA23v17)
v_19 v_19 GlcA6P + NADPf = Rul5P + NADPHf

Vmaxv18/K6PG1v18/KNADPv18*(GlcA6P*NADPf - Rul5P*NADPHf/Keqv18)/((1+NADPf/KNADPv18)*(1+GlcA6P/K6PG1v18+(Gri23P2f + MgGri23P2)/KPGA23v18) + (ATPf+MgATP)/KATPv18 + NADPHf*(1+GlcA6P/K6PG2v18)/KNADPHv18)
v_2 v_2 Glcin + MgATP = Glc6P + MgADP

Inhibv1*Glcin/(Glcin+KMGlcv1)*(Vmax1v1/KMgATPv1)*(MgATP + (Vmax2v1/Vmax1v1)*MgATP*Mgf/KMgATPMgv1 - Glc6P*MgADP/Keqv1)/(1 + (MgATP/KMgATPv1)*(1+Mgf/KMgATPMgv1) + Mgf/KMgv1 + (1.55+Glc6P/KGlc6Pv1)*(1+Mgf/KMgv1) + (Gri23P2f + MgGri23P2)/K23P2Gv1 + Mgf*(Gri23P2f + MgGri23P2)/(KMgv1*KMg23P2Gv1))
v_20 GSSG + NADPHf = {2.0}GSH + NADPf

Vmaxv19*(GSSG*NADPHf/(KGSSGv19*KNADPHv19) - (GSH^2/KGSHv19^2)*NADPf/(KNADPv19*Keqv19))/(1 + NADPHf*(1+GSSG/KGSSGv19)/KNADPHv19 + (NADPf/KNADPv19)*(1 + GSH*(1+GSH/KGSHv19)/KGSHv19))
v_21 {2.0}GSH = GSSG

Kv20*GSH
v_22 Rul5P = Xul5P

Vmaxv21*(Rul5P-Xul5P/Keqv21)/(Rul5P+KRu5Pv21*(1+Xul5P/KX5Pv21))
v_23 Rul5P = Rib5P

Vmaxv22*(Rul5P-Rib5P/Keqv22)/(Rul5P+KRu5Pv22*(1+Rib5P/KR5Pv22))
v_24 Rib5P + Xul5P = GraP + Sed7P

Vmaxv23*(Rib5P*Xul5P - GraP*Sed7P/Keqv23)/((K1v23 + Rib5P)*Xul5P + (K2v23+K6v23*Sed7P)*Rib5P + (K3v23+K5v23*Sed7P)*GraP + K4v23*Sed7P + K7v23*Xul5P*GraP)
v_25 Sed7P + GraP = E4P + Fru6P

Vmaxv24*(Sed7P*GraP - E4P*Fru6P/Keqv24)/((K1v24 + GraP)*Sed7P + (K2v24+K6v24*Fru6P)*GraP + (K3v24+K5v24*Fru6P)*E4P + K4v24*Fru6P + K7v24*Sed7P*E4P)
v_26 Rib5P + MgATP = PRPP + MgAMP

Vmaxv25*(Rib5P*MgATP - PRPP*MgAMP/Keqv25)/((KATPv25 + MgATP)*(KR5Pv25 + Rib5P))
v_27 E4P + Xul5P = GraP + Fru6P

Vmaxv26*(E4P*Xul5P - GraP*Fru6P/Keqv26)/((K1v26 + E4P)*Xul5P + (K2v26+K6v26*Fru6P)*E4P + (K3v26+K5v26*Fru6P)*GraP + K4v26*Fru6P + K7v26*Xul5P*GraP)
v_28 Phiex = Phi

Vmaxv27*(Phiex-Phi/Keqv27)
v_29 Lacex = Lac

Vmaxv28*(Lacex-Lac/Keqv28)
v_3 Glc6P = Fru6P

Vmaxv2*(Glc6P-Fru6P/Keqv2)/(Glc6P+KGlc6Pv2*(1+Fru6P/KFru6Pv2))
v_30 Pyrex = Pyr

Vmaxv29*(Pyrex-Pyr/Keqv29)
v_31 MgATP = ATPf + Mgf

EqMult*(MgATP - Mgf*ATPf/KdATP)
v_32 MgADP = ADPf + Mgf

EqMult*(MgADP - Mgf*ADPf/KdADP)
v_33 MgAMP = AMPf + Mgf

EqMult*(MgAMP - Mgf*AMPf/KdAMP)
v_34 MgGri23P2 = Gri23P2f + Mgf

EqMult*(MgGri23P2 - Mgf*Gri23P2f/Kd23P2G)
v_35 P1NADP = P1f + NADPf

EqMult*(P1NADP - P1f*NADPf/Kd1)
v_36 P1NADPH = P1f + NADPHf

EqMult*(P1NADPH - P1f*NADPHf/Kd3)
v_37 P2NADP = P2f + NADPf

EqMult*(P2NADP - P2f*NADPf/Kd2)
v_38 P2NADPH = P2f + NADPHf

EqMult*(P2NADPH - P2f*NADPHf/Kd4)
v_4 v_4 Fru6P + MgATP = Fru16P2 + MgADP

Vmaxv3*(Fru6P*MgATP - Fru16P2*MgADP/Keqv3)/((Fru6P + KFru6Pv3)*(MgATP + KMgATPv3)*(1+L0v3*((1+ATPf/KATPv3)*(1+Mgf/KMgv3)/ ((1+(AMPf+MgAMP)/KAMPv3)*(1+Fru6P/KFru6Pv3)))^4))
v_5 Fru16P2 = GraP + DHAP

(Vmaxv4/KFru16P2v4)*(Fru16P2 - GraP*DHAP/Keqv4)/(1 + Fru16P2/KFru16P2v4 + GraP/KiGraPv4 + DHAP*(GraP+KGraPv4)/(KDHAPv4*KiGraPv4)+ Fru16P2*GraP/(KFru16P2v4*KiiGraPv4))
v_6 DHAP = GraP

Vmaxv5*(DHAP-GraP/Keqv5)/(DHAP+KDHAPv5*(1+GraP/KGraPv5))
v_7 GraP + Phi + NAD = Gri13P2 + NADH

Vmaxv6/(KNADv6*KGraPv6*KPv6)*(NAD*GraP*Phi - Gri13P2*NADH/Keqv6)/((1+NAD/KNADv6)*(1+GraP/KGraPv6)*(1+Phi/KPv6) + (1+NADH/KNADHv6)*(1+ Gri13P2/K13P2Gv6) - 1)
v_8 Gri13P2 + MgADP = Gri3P + MgATP

Vmaxv7/(KMgADPv7*K13P2Gv7)*(MgADP*Gri13P2 - MgATP*Gri3P/Keqv7)/((1+MgADP/KMgADPv7)*(1+Gri13P2/K13P2Gv7) + (1+MgATP/KMgATPv7)*(1+Gri3P/K3PGv7) - 1)
v_9 v_9 Gri13P2 = Gri23P2f

kDPGMv8*(Gri13P2 - (Gri23P2f + MgGri23P2)/Keqv8)/(1 + (Gri23P2f + MgGri23P2)/K23P2Gv8)

Global parameters

Id Value
Atot 2.0
EqMult 1000.0
GStotal 3.114
Inhibv1 1.0
K13P2Gv6 0.0035
K13P2Gv7 0.002
K1v23 0.4177
K1v24 0.00823
K1v26 0.00184
K23P2Gv1 2.7
K23P2Gv8 0.04
K23P2Gv9 0.2
K2PGv10 1.0
K2PGv11 1.0
K2v23 0.3055
K2v24 0.04765
K2v26 0.3055
K3PGv10 5.0
K3PGv7 1.2
K3v23 12.432
K3v24 0.1733
K3v26 0.0548
K4v23 0.00496
K4v24 0.006095
K4v26 0.0003
K5v23 0.41139
K5v24 0.8683
K5v26 0.0287
K6PG1v18 0.01
K6PG2v18 0.058
K6v23 0.00774
K6v24 0.4653
K6v26 0.122
K7v23 48.8
K7v24 2.524
K7v26 0.215
KADPv16 0.11
KAMPv16 0.08
KAMPv3 0.033
KATPv12 3.39
KATPv16 0.09
KATPv17 0.749
KATPv18 0.154
KATPv25 0.03
KATPv3 0.01
KDHAPv4 0.0364
KDHAPv5 0.838
KFru16P2v12 0.005
KFru16P2v4 0.0071
KFru6Pv2 0.071
KFru6Pv3 0.1
KG6Pv17 0.0667
KGSHv19 20.0
KGSSGv19 0.0652
KGlc6Pv1 0.0045
KGlc6Pv2 0.182
KGraPv4 0.1906
KGraPv5 0.428
KGraPv6 0.005
KMGlcv1 0.1
KMg23P2Gv1 3.44
KMgADPv12 0.474
KMgADPv7 0.35
KMgATPMgv1 1.14
KMgATPv1 1.44
KMgATPv3 0.068
KMgATPv7 0.48
KMgv1 1.03
KMgv3 0.44
KMinv0 6.9
KMoutv0 1.7
KNADHv6 0.0083
KNADPHv17 0.00312
KNADPHv18 0.0045
KNADPHv19 0.00852
KNADPv17 0.00367
KNADPv18 0.018
KNADPv19 0.07
KNADv6 0.05
KPEPv11 1.0
KPEPv12 0.225
KPGA23v17 2.289
KPGA23v18 0.12
KPv6 3.9
KR5Pv22 2.2
KR5Pv25 0.57
KRu5Pv21 0.19
KRu5Pv22 0.78
KX5Pv21 0.5
Kd1 0.0002
Kd2 0.00001
Kd23P2G 1.667
Kd3 0.00001
Kd4 0.0002
KdADP 0.76
KdAMP 16.64
KdATP 0.072
Keqv0 1.0
Keqv1 3900.0
Keqv10 0.145
Keqv11 1.7
Keqv12 13790.0
Keqv13 9090.0
Keqv14 14181.8
Keqv16 0.25
Keqv17 2000.0
Keqv18 141.7
Keqv19 1.04
Keqv2 0.3925
Keqv21 2.7
Keqv22 3.0
Keqv23 1.05
Keqv24 1.05
Keqv25 100000.0
Keqv26 1.2
Keqv27 1.0
Keqv28 1.0
Keqv29 1.0
Keqv3 100000.0
Keqv4 0.114
Keqv5 0.0407
Keqv6 0.000192
Keqv7 1455.0
Keqv8 100000.0
Keqv9 100000.0
KiGraPv4 0.0572
KiiGraPv4 0.176
Kv20 0.03
L0v12 19.0
L0v3 0.001072
Mgtot 2.8
NADPtot 0.052
NADtot 0.0655
Vmax1v1 15.8
Vmax2v1 33.2
Vmaxv0 33.6
Vmaxv10 2000.0
Vmaxv11 1500.0
Vmaxv12 570.0
Vmaxv13 2800000.0
Vmaxv16 1380.0
Vmaxv17 162.0
Vmaxv18 1575.0
Vmaxv19 90.0
Vmaxv2 935.0
Vmaxv21 4634.0
Vmaxv22 730.0
Vmaxv23 23.5
Vmaxv24 27.2
Vmaxv25 1.1
Vmaxv26 23.5
Vmaxv27 100.0
Vmaxv28 10000.0
Vmaxv29 10000.0
Vmaxv3 239.0
Vmaxv4 98.91000366
Vmaxv5 5456.600098
Vmaxv6 4300.0
Vmaxv7 5000.0
Vmaxv9 0.53
alfav0 0.54
kATPasev15 1.68
kDPGMv8 76000.0
kLDHv14 243.4
protein1 0.024
protein2 0.024

Local parameters

Id Value Reaction

Assignment rules

Definition

Rate rules

Definition

Algebraic rules

Definition
Trigger Assignments