charge. Some groups have also written their own code, where they can introduce
correcting factors and optimize them at will. Here we provide a brief tutorial of its
use for DFT-based microkinetic modeling. We have implemented the input files for
several examples discussed below, and they are included in the Supplementary
Information (SI).
Reactions can be written directly, as shown in Fig. 3a. The reader can also follow
these comments with COPASI loading the ParamEstim.cps input file included in the
SI. Species are created automatically from them or may have been defined previously, but we have to specify the initial concentration of each one. We can define the
necessary rate constants (rb01k, rb01kr. . .) in the Global Quantities entry (Fig. 3b)
and then assign each rate constant to its reaction (Fig. 3c).
The corresponding differential equations are automatically generated and can be
seen in the Mathematical entry of the object tree, on the left panel. In COPASI, apart
from giving energies and equations, one can introduce directly the computational
reaction rates.
COPASI can also generate graphical Diagrams or schemes that can be manually
modified (Fig. 3d).
Once all the Reactions, Species, and necessary Global Quantities have been
defined and initialized, COPASI is ready for Time Course simulations, under the
Tasks entry on the left panel.
To carry out a Time Course simulation and visualize the results for the current
parameter values and initial concentrations, we simply have to choose or define an
output graph with the Output Assistant button (located at the bottom right of the
Time Course main panel, Fig. 4), set the time Duration and number of Intervals or
Interval Size, and click Run. The Plots can be modified and deactivated in the Output
Specifications entry of the left panel.
A handy feature of COPASI is the use of Sliders (Fig. 4) to easily modify
parameters (temperature, initial concentrations, barrier heights, etc.) and rerun the
simulation instantly. To visualize the Slider’s panel of the active Task (Time
Course), go to the Tools menu or click on its icon located below the menu.
Another useful task, called Parameter Estimation, allows the optimization of
parameters to obtain the best fit to a set of experimental data. The parameters to be
optimized from a Start Value (e.g., the as-calculated DFT values) within specified
Upper and Lower Bounds (the computation estimated error) are included in the
Parameters list (Fig. 5a) by first clicking on the green “+” button. This adds a new
line to the Parameters list window. And then the Object can be selected by clicking
the COPASI logo button located left to the “+” button. The Hooke and Jeeves can be
chosen as a good Method for these optimizations. An experimental data file
(ParamEstim-Experiments.txt, included in the SI), like the one shown in Fig. 5c,
can be prepared with Excel. It should have a header row, with a column named Time.
Experiments are separated by an empty line. Click on the Experimental Data button
of the Parameter Estimation panel, add the data file (Fig. 5b), specify the Separator
(use “tab” for easy copy/paste to Excel), and select Time Course as Experiment
Type. The header names should appear listed in the Column Name as shown. Assign
the appropriate Type and Model Object to each header. To propagate the definitions
90
M. Jaraíz
correcting factors and optimize them at will. Here we provide a brief tutorial of its
use for DFT-based microkinetic modeling. We have implemented the input files for
several examples discussed below, and they are included in the Supplementary
Information (SI).
Reactions can be written directly, as shown in Fig. 3a. The reader can also follow
these comments with COPASI loading the ParamEstim.cps input file included in the
SI. Species are created automatically from them or may have been defined previously, but we have to specify the initial concentration of each one. We can define the
necessary rate constants (rb01k, rb01kr. . .) in the Global Quantities entry (Fig. 3b)
and then assign each rate constant to its reaction (Fig. 3c).
The corresponding differential equations are automatically generated and can be
seen in the Mathematical entry of the object tree, on the left panel. In COPASI, apart
from giving energies and equations, one can introduce directly the computational
reaction rates.
COPASI can also generate graphical Diagrams or schemes that can be manually
modified (Fig. 3d).
Once all the Reactions, Species, and necessary Global Quantities have been
defined and initialized, COPASI is ready for Time Course simulations, under the
Tasks entry on the left panel.
To carry out a Time Course simulation and visualize the results for the current
parameter values and initial concentrations, we simply have to choose or define an
output graph with the Output Assistant button (located at the bottom right of the
Time Course main panel, Fig. 4), set the time Duration and number of Intervals or
Interval Size, and click Run. The Plots can be modified and deactivated in the Output
Specifications entry of the left panel.
A handy feature of COPASI is the use of Sliders (Fig. 4) to easily modify
parameters (temperature, initial concentrations, barrier heights, etc.) and rerun the
simulation instantly. To visualize the Slider’s panel of the active Task (Time
Course), go to the Tools menu or click on its icon located below the menu.
Another useful task, called Parameter Estimation, allows the optimization of
parameters to obtain the best fit to a set of experimental data. The parameters to be
optimized from a Start Value (e.g., the as-calculated DFT values) within specified
Upper and Lower Bounds (the computation estimated error) are included in the
Parameters list (Fig. 5a) by first clicking on the green “+” button. This adds a new
line to the Parameters list window. And then the Object can be selected by clicking
the COPASI logo button located left to the “+” button. The Hooke and Jeeves can be
chosen as a good Method for these optimizations. An experimental data file
(ParamEstim-Experiments.txt, included in the SI), like the one shown in Fig. 5c,
can be prepared with Excel. It should have a header row, with a column named Time.
Experiments are separated by an empty line. Click on the Experimental Data button
of the Parameter Estimation panel, add the data file (Fig. 5b), specify the Separator
(use “tab” for easy copy/paste to Excel), and select Time Course as Experiment
Type. The header names should appear listed in the Column Name as shown. Assign
the appropriate Type and Model Object to each header. To propagate the definitions
90
M. Jaraíz