KRATKY ANALYSIS ... by Robert P. Rambo, Ph.D.

The "unfolded-ness" or "random coil" likeness of your biological macromolecule can be qualitatively assessed by means of a Kratky plot. The plot uses your merged data and can be created using any plotting or spreadsheet program but we will demonstrate it using ScÅtter and at the end using the old version of Primus


Courtesy of Putnam, C.D., Hammel, M., Hura, G.L., and Tainer, J.A. Q Rev Biophys. 2007 40(3):191-285

The Kratky interpretation originates from Debye's scattering formulation of a Gaussian coil. Debye's equation shows that within a limited range of data, the scattering intensities for macromolecules behaving as Gaussian-like coils will plateau in a q2 x I(q) vs q plot. To begin, load some data and then switch to the "Analysis" tab and click on the Kratky button (yellow circle Figure 1). Here, we have loaded two datasets, glucose isomerase (blue) and the SAM-I riboswitch (green).

Figure 1:

The Kratky button transforms the data and plots (Figure 2). In this case, I previously scaled the two datasets together so that they are close together in the Kratky plot. As you can see, glucose isomerase does not plateau whereas SAM-I does. These are extreme cases that compare a compact versus a flexible particle. SAM-I is an RNA riboswitch that requires Mg2+ and s-adensyl-methionine to fold into a discrete compact structure. This SAXS data of SAM-I is in the absence of the metabolite. In many cases, the presence of a plateau will be followed by a slow descent to baseline for partially flexible particles. More evidence can be gained through examining the particle volume and Porod exponent. In some cases, poor buffer subtraction can lead artificially to elevated baselines at high q.

Also, if you see in Figure 1, glucose isomerase and SAM-I have similar Rg values though SAM-I is 4 times smaller than glucose isomerase. The Rg comparison strongly supports the notion that the mass distribution of SAM-I is wide and dispersed over a large space leading to a relatively large Rg value (as we would expect for an unfolding of the RNA).

Figure 2:


For Primus, to load your data (see Figure 3), 1st click the "Select" button and find your data file. In this example, I have selected a file called TyMV_1.dat. After selecting the file, click OK to load the name in the dialogue box as seen in 1. Then click the "Plot" button to plot the data in Primus (arrow 2 in Figure 4).

Figure 3:
Figure 4:

Now, your data should be plotted. The next step in making a Kratky plot with Primus requires you to click on the "Sasplot" button (see Figure 5). This will start a new program called Sasplot which runs on top of Primus. Your data will be re-plotted, so don't be concerned.

Figure 5:

This next step is more for visual aesthetics, it changes the symbols used to plot the data from dots to circles. This change is achieved by clicking on "Symbols" (Figure 6).

Figure 6:

The Kratky plot is a transformation of the data where the y-axis is I(q)*q2 (or I(s)*s^2 in SASplot). This is easily done in Sasplot. Click on the "View" tab as highlighted in Figure 7 and a drop down menu should appear.

Figure 7:

In the drop-down menu, select "Y*s^2::X".

Figure 8:

And like magic, your data is re-plotted as a Kratky plot (Figure 9). Unfortunately, there is no easy way to save the plot or do anything meaningful with it via Sasplot. I recommend using your favorite plotting program, mine is Gnuplot or R, to create the plot for your presentations or manuscripts.

Figure 9: