You will need some ITC data to proceed with the tutorial. If you don't have any, the example.itc is included with every release, which we will use throughout this tutorial.
Import the dataset
File->Import Data then choose the .itc file. The ITCTools window will look like this:
Every imported dataset will be shown as a tab in the notebook. Parameters of the run (including the injection schedule) are shown in the "Run parameters window".
Hit Optimize button on the right. The optimization is done with currently selected model (choose in the "Model" box - models other than OneSite are still experiemntal) and results shown in the appropriate box. OneSite model lists the following parameters (with fitting errors):
Notice that it is free energy, not the binding constant, which is refined. In my experience, this makes the fitting process much more stable and initial values of parameters easier to guess.
- n - stoichiometry
- DH - binding enthalpy
- DG - free energy of binding
- Kd - dissociation constand (derived from DG)
- binding entropy (derived from DH/DG)
- entropic contribution to the free energy
- Dilution heat
Hit the Plot button and you'll see this window:
You can zoom, pan and export the image. I don't feel it is a publication quality, so you can use Export results button to get a file with data which you can then import into, say, SigmaPlot (my personal favorite). Notice that some data points are red, not blue - these were deemed outliers and excluded from fitting.
Playing with model
Hit the Parameters button to change individual parameters. It opens a dialog with individual parameters and a graph which will be updated if you change the parameter values in the dialog and hit the Plot button. The outlier cutoff parameter can be changed here too - increase its value to make the fitting process more liberal to outliers. Hit OK if you want to store the modified parameters.
You can do that by using the Concentrations button. It applies to the dataset in the currently selected tab only. The original files are not modified, but I will add this as an option in the future (in fact, .itc files are text, and it's easy to just edit them manually to correct concentrations permanently).
You can plot things other than fitted data using Plot menu:
- Heat - heat trace with baseline subtracted. You can output this into a file using File->Export data. This is what you need to create a Microcal-style "final figure". I will add similar feature in the future releases, although I personally believe that the heat traces are a waste of journal space.
- Temperature - sample cell temperature during the experiment.
- Baseline - orginal raw heat with the baseline. You can check here if some of the injections had a baseline messed up, although you can't really do anything about it (at least not yet).
- Raw heat - same as above, only without the baseline. I can't imagine why would anyone need this, but whatever.
- Titration - this gives you the individual injection heat effects versus stoichiometry. You can inspect the integration results here prior to optimization (although the same can be done with Plot button if you learn to ignore the meaningless curve produced prior to fitting, which uses the starting values of all parameters).
Averaging multiple experiments
Yes, the results are reported with errors, but these simply reflect how well your model fits a particular dataset. To get real errors, one has to repeat the same experiement few times and then get the mean values and standard errors. Once you have the data, import them all (you can select multiple files), run optimization and then calculate the mean and errors using File->Model averaging. The results will be in the log-window (bottom half of the main frame). You can select the model to use and list of datasets to include, so there is no need to close any before this calculation. Experiments do not have to be perfectly identical (i.e. concentrations may vary).
This is it for now. Send me an email if you have any questions/suggestions.