Determination of binding constants from titration data This is a development version!
Stuff might (will!) go wrong...

### Welcome!

On this webpage you can determine binding/association constants from titration data using any equilibrium model. We do not use commonly known approximation methods such as the Benesi–Hildebrand or Scatchard plot, but we use non-linear optimization to fit the observed titration data to calculated titration data, which we calculate by numerically solving equilibrium concentrations from a set of binding constants and equilibrium reactions. We therefore don't have to algebraically solve for the equilibrium species concentrations (Hunter's method; recently implemented by Thordarson at Supramolecular.org), which limits the equilibrium models to 1:1, 1:2 and 2:1 stoichiometries. Our website offers functionality similar to HypNMR.

info_outline Software description info_outline Titration methods

This script was developed by Dr. R. Becker during his doctoral study at the University of Amsterdam (NL) and has been used in the following publications:

Insert your titration data in the tables below.
Or load example data and play around:

### Observed values

Select or define the equilibrium model.
{{s.name}}

{{expr}}

### Statistical factors

Set the optimization parameters in the fields below.

Optimize! Stop

### Fitting results

Sum of squared residuals (SSR): {{SSR}} Averaged R2: {{compoundR2}} R2 @ {{obs_names[0][$index]}}: {{R2[$index]}}

### Raw data output

Copy this data into spreadsheet (delimiter = [tab])
X-axis scale: {{ chart_xaxis_scale }} Titration curves Experimental titration curves and calculated titration curves. Residual errors Difference between experimental titration curves and calculated titration curves. Species mole fractions Calculated species mole fractions from the fitted binding constant and alpha parameters.