Difference between revisions of "Kinetic model of Central Metabolism"

From ISMOC
Jump to: navigation, search
Line 27: Line 27:
 
rect 618 98 643 121 [[Glycogen phosphorylase|GP]]
 
rect 618 98 643 121 [[Glycogen phosphorylase|GP]]
 
rect 669 156 696 179 [[Glycogen synthase|GS]]
 
rect 669 156 696 179 [[Glycogen synthase|GS]]
rect 532 486 557 510 [[Dehydrogenase|DHases]]
+
rect 532 471 557 480 [[Dehydrogenase|DHases]]
 
rect 522 156 548 179 [[UDPG-pyrophosphorylase|UPP]]
 
rect 522 156 548 179 [[UDPG-pyrophosphorylase|UPP]]
 
rect 357 156 382 179 [[Phosphoglucomutase|PGLM]]
 
rect 357 156 382 179 [[Phosphoglucomutase|PGLM]]

Revision as of 10:05, 13 May 2014

A kinetic model of glycolysis with serine activation is constructed from the literature data [1][2][3][4][5].

Description of the model

Schematic diagram of the model is gvien here. The dotted line represents activation(+) or inhibition(-) and the dashed arrow indicate Pentose Phosphate Pathway reactions not included in the model. Click on a reaction to have more information

GLUTHKHPIPFK-1ALDOTPIGAPDHPGKPGAMENOPYKLDHMCTAKATPasePPPTKGPGSDHasesUPPPGLMSHMTSERoutGlYCoutPSPPSAPDHMPMGlycolysis with Serine Activation
About this image

Reactions

Details of the abbreviations for this model is listed here. Reactions of the model are listed below.

Initial concentration of the metabolites can be found here

Model File

The SBML file of the model can be found here.

Global parameters

The Vmax value in the paper "Modeling cancer glycolysis" is given in  U \times \text{(mg total cellular protein)}^{-1} unit [1]. To homogenize the units it is then converted back to \frac{mM}{min} by multiplying  U \times \text{(mg total cellular protein)}^{-1} with 65 as the HeLa cell was incubated in  65 \frac{\text{mg protein}}{\text{mL cell volume}}.

References

  1. 1.0 1.1 Marín-Hernández A, Gallardo-Pérez JC, Rodríguez-Enríquez S et al (2011). Modeling cancer glycolysis. Biochim Biophys Acta, 1807:755–767 (doi)
  2. Turnaev II, Ibragimova SS, Usuda Y et al (2006). Mathematical modeling of serine and glycine synthesis regulation in Escherichia coli. Proceedings of the fifth international conference on bioinformatics of genome regulation and structure 2:78–83
  3. Smallbone K, Stanford NJ (2013). Kinetic modeling of metabolic pathways: Application to serine biosynthesis. In: Systems Metabolic Engineering, Humana Press. pp. 113–121
  4. Palm, D.C. (2013). The regulatory design of glycogen metabolism in mammalian skeletal muscle (Ph.D.). University of Stellenbosch
  5. Ettore Murabito (2010). Application of differential metabolic control analysis to identify new targets in cancer treatment (Ph.D.). University of Manchester