Fit SAXS data on disordered proteins


Thank you for choosing to use the Sosnick Lab's SAXSonIDPs server to interpret your SAXS data. Our goal is to provide access to tools we have developed to extract information about the conformational ensemble of disordered proteins and other flexible polymers, and to compare the results to methods from the field of polymer physics.

Please cite our work which can be found at:
Riback JA, Bowman MA, Zmyslowski AM, Knoverek CR, Jumper JM, Hinshaw JR, Kaye EB, Freed KF, Clark PL*, Sosnick TR*. Innovative scattering analysis shows hydrophobic disordered proteins are expanded in water. (2017) Science. 358 (238-241)
Riback JA†, Bowman MA†, Zmyslowski AM, Plaxco KW, Clark PL*, Sosnick TR*. Commonly-used FRET fluorophores promote collapse of an otherwise disordered protein. (2019) PNAS. 116 (18) 8889-8894

To begin fitting your data, go to the section labeled Step 1: Select SAXS data to fit

Please contact Joshua Riback for more information, help fitting, or comments on the website.

Select data to fit

If you have your own data accessible, choose it here:

If you wish to have multiple files fitted, choose them here: (currently unavailable)

The file format must contain contain q, I(q), and non-zero errors. Select configuration options below:
Column separation:
Units of q:
header lines to remove:
footer lines to remove:

Choose from published data:

Note: Since we fit the scattering profile out to large q, reliable fitting requires the data have a proper background subtracted. You may fit our data to obtain an ideal of the expected deviations and the sensitivity of our fitting function.

To fit with current options click otherwise proceed to the section labled Step 2: Select fit function, fit parameters, and output style

Select fit function:

This section will contain warnings about each model and points to note. IF YOU SEE THIS WEBSITE IS NOT WORKING =(

Choose fit parameters:




Select output style:

Fitting is conducted using all points in the fitting range. To visually improve the data quality, we provide an option for rebinning the data with appropriate errors (recommended for publication).

How many data points would you like to have shown every decade in q?

(Again, note this is for aesthetics, fitting is done BEFORE binning)

To compare with expected pre-factor R0 vs. ν trend for polypeptides (polymer MFF only), please provide the number of residues in your protein 

Once you are done click to proceed.

If you see this then functionality and you have fit, then the text warning you about the limitations of each MFF is missing. Consult us or our papers for important limitations and for details on proper use.

Log-Log Plot and Dimensionless Kratky Plots of scattering data and fit

or or or

Trace of expected pre-factor R0 versus ν

(point calculated using given AA length and best fit parameters to polymer MFF)

or or

Probability distribution for Rg and Ree

or or or