The most potent software for Isothermal Titration Calorimetry Data Analysis

AFFINImeter is a potent software for Isothermal Titration Calorimetry (ITC) experiments. It was developed to optimize the design of ITC experiments , to analyze ITC measurements, to aid in the interpretation of ITC data, and to organize and share ITC results.

AFFINImeter: Easy. Versatile. Powerful.

AFFINImeter is an original software that takes the Isothermal Titration Calorimetry technique to a whole new level!

A software for Isothermal Titration Calorimetry data analysis and Isothermal Titration Calorimetry Experiment Simulation that includes an unlimited variety of molecular interaction models. 

Design your own model with the easy-to-use Model Builder

Complex reaction schemes can be written to describe a real scenario in chemical language. The calculation of the thermodynamic parameters involved in those reactions requires the development of coupled equations associated to the different equilibria and the implementation of such equations in a computational code. AFFINImeter provides an exclusive “Model Builder” to write the chemical equations describing your system.
Using AFFINImeter you can simulate and/or analyze ITC data

  • Competitive Sequential Binding Models involving up to 3 different molecules without limitation in the stoichiometry of the resulting complexes.
  • Competitive Independent Binding Models without limitation in the number of sets of identical sites.

Perform global analysis of several ITC isotherms

Complex binding models are usually described by many variable parameters and, in such cases, a single experimental curve is insufficient to achieve a robust analysis. Instead, the simultaneous analysis of several curves must be performed. If the same model applies to all the measurements, the parameters of the different curves should be identical to each other. There are also situations where a different model applies to each experimental curve but one or more parameters are shared. This happens, for instance, when combining an experiment involving two competing ligands and a host with another experiment where one of the ligands is absent. Additionally, mainly when applying complex models, you may want to correlate parameters by means of analytical or logical equations. All the situations described in this paragraph can be easily solved using AFFINImeter.