Practical 9: Kinetics of the Calvin Cycle.

For this proctical we will be investigating the control analysis properties of the Calvin cycle described in the previous lecture. Download it here.

The goal is to generate a dataset in which the rows are the Vmax values of the enzymes in the model, and the columns the reactions. Each cell will contain the flux control coefficient of reaction fluxes to Vmax.

1. Having loaded the model, we need to create a dataset to hold our results, the item names will be the names of the reactions in the model:

   • >>> fccs = DataSets.DataSet(ItemNames=m.sm.cnames)

2. The names of the Vmax parameters are:

   • >>> vms =['FBPase_ch_vm', 'SBPase_ch_vm', 'TP_Piap_vm', 'Ru5Pk_ch_vm', 'LR_vm', 'Rbco_vm', 'StSynth_vm', 'StPase_vm', 'EQMult']

     • This line can be copy and pasted into the ScrumPy command line.

3. Now, for each Vmax, we need to calculate the sensitivity of the steady-state reaction rates to a small change in the Vmax value:

   • >>> for v in vms:
             result = m.ScaledSensits(v, m.sm.cnames)
             fccs.NewRow(result, name=v)

4. The DataSet, fccs, can be examined from within ScrumPy, but it may be more convenient to save it as a file and view it using the libreoffice spreadsheet:

   • >>> print >>open("fccs.txt","w"), fccs

   • This saves the results in a file called "fccs.txt". You can load this into libreoffice by selecting File/New/Spreadsheet followed by Insert/Sheet from file