Checking the quality of the fittings in AFFINImeter

As important as obtaining a set of parameters corresponding to a model able to describe the experimental data is to ensure, with a certain statistical probability, that the analysis is correct. Often, this is a complicated task. AFFINImeter´s philosophy is to make things simple. We have developed a number of mathematical and statistical tools that are useful to assess how robust your analysis is.

The next paragraphs will explain the meaning of some parameters implemented in AFFINImeter and how to interpret them in terms of the quality of the analysis.


What is the meaning of Standard errors in AFFINImeter?

Standard errors come from the variance-covariance matrix obtained from the partial derivatives of the objective function with respect to the fitting parameters. These are the errors commonly determined in nonlinear fitting algorithms based on derivatives, such as the Levenberg-Marquardt method that we employ in combination with the Simulated Annealing method to optimize the efficiency of the minimization process.

What is the meaning of Statistical errors in AFFINImeter?

Statistical errors are determined from the standard deviation of the parameters obtained by repeating the fitting as many times as experimental points are available in the target data series, each time ignoring one point in these extra fittings. For instance, in a binding isotherm consisting of 30 points, all of them are employed in the main minimization process (weighted by their corresponding uncertainty). The resulting parameters are used as seeds for 30 independent fittings (of 29 points each) where the data points are sequentially removed one at a time. In this case, AFFINImeter gets 30 independent solutions for each parameter (in addition to the one provided by the main fitting). The removal of the points that weight a lot in the fittings induces a significant change in the parameters that, in its turn, increases the standard deviation (the statistical error in AFFINImeter). This is the so-called  Jackknife method.

By default, the statistical uncertainties are activated in AFFINImeter but we do provide also the standard errors in order to have a useful alternative value for the uncertainty of the fitting parameters.

What is the meaning of Local Minima table in AFFINImeter?

Additional useful information to be considered in the resulting analysis with AFFINImeter is the local minima table. This table provides an estimation on how the results obtained depend on the initial values (seeds) of the fitting algorithm. AFFINImeter executes several minimizations runs (20 by default) for each analysis and it selects the values that provide the best fitting (lowest c2 value). A robust fitting is achieved when the same results are reached independently of the random initial seeds. If the local minima table shows different results for the different runs of the algorithm with similar c2 values, the analysis is probably overparameterized. In that case, it will necessary to simplify the model, thus reducing the number of fitting variables, or to include additional data series for a global fitting, thus reducing the number of degrees of freedom in the analysis.



AFFINImeter fits with scientific publications


Recently we received the great news because AFFINImeter has been used and mentioned in some scientific publications.

The first one, It´s a review of the applications of Isothermal Titration Calorimetry from 2011 to 2015 . The author describes that:

“AFFINImeter produces commercial software that can be used for analysis of displacement assays, micellisation experiments, kinITC, the application of complex models for complex interactions and ligand-induced conformational change.” R. J. Falconer

Most of all publications have used KinITC method and the last one, the authors have used advanced tools like applying complex binding models or working with species distribution plot.


Press on the links bellow to take a look at the publications:

2nd Annual European MicroCal Meeting

The Second Annual European MicroCal Meeting will be held this September 26th-27th at the Institut Pasteur in Paris, and AFFINImeter will be there.

It is important to mention that our Scientific staff will attempt to this meeting:

Eva Muñoz, our senior scientist as part of ARBRE European molecular biophysics network participates in the in scientific organizing committee.

Ángel Piñeiro (co-founder and CSO) will impart a workshop about AFFINImeter.

This event is co-organized by Malvern Instruments, Institut Pasteur and ARBRE European molecular biophysics network

Therefore it will be a good opportunity to learn about the latest applications of the microcalorimetry:

Isothermal titration and differential scanning calorimetry  (ITC and DSC).

You won’t miss it!


 71st Calorimetry conference (CalCon 2016)


71st Calorimetry Conference held in Oahu (Hawaii, USA)

It was a great pleasure for us attend the conference and on behalf of AFFINImeter, we want to thank CalCon 2016 for organising what once again proved to be an excellent conference

Thanks for making us partakers of this incredible scientific program which we really enjoyed and to gave us the opportunity to attend at calorimetry tutorial.

We mark our calendar to attend to Calorimetry Conference for the next year.




5 Tips to optimize your ITC experiments for kinetic analysis.

Since the method KinITC was implemented in AFFINImeter many researchers have been using it to obtain kinetic information of binding interactions from ITC data; the good news is that no special experimental setup different from the standard ITC experiment is required to register data for kinetic analysis! The information is derived from analysis of the thermogram of regular ITC titrations and therefore one can obtain kinetic information from old ITC data right away.

There are few recommendations though if you are planning to perform new ITC experiments, focused on getting high-quality data for kinetic analysis:

1) Set the time between successive power measurements to 1s or 2s. This will give a better definition of the thermogram peaks and therefore a more precise calculation of the equilibration times.

2) Set the time recording the baseline before the first injection to 1 or 2 minutes. In order to have a good reference when determining the signal baseline.

3) Leave enough time between injections so that a full equilibration for the overall set of injections is registered.

4) Clean thoroughly the instrument before the experiment. This is fundamental to optimize the response time of the instrument, which strongly determines the sensitivity of the kinetic analysis.

5) A high gain feedback mode is recommended in order provide the fastest response time (but, be careful because a high feedback mode can also generate signal overshooting after injection, which greatly difficulties the kinetic analysis! If overshooting happens, don´t use high gain model).

Need more information about this subject? Contact the Scientific team of AFFINImeter at

Follow these simple tips to increase the quality of your ITC data for kinetic analysis

Figure Junio2016

Variable Temperature ITC analysis with AFFINImeter

Analysis of Variable Temperature Isothermal Titration Calorimetry experiments with AFFINImeter

Monitoring a binding event with Isothermal Titration Calorimetry at different temperatures provides a powerful framework for elucidating interesting characteristics of the interaction. Analysis of the isotherms obtained determines the dependence of the association constant (KA) and binding enthalpy (ΔH) with temperature, information that can reveal mechanistic aspects of the interactions, i.e. the existence of allosteric effects and conformational changes (1).

Moreover, kinetic characterization of the interaction at various temperatures gives information about transition state thermodynamics, by means of the dependence of the association and dissociation rate constants (kon and koff) with the temperature. This way, activation free energies of association and dissociation are resolved into its enthalpic and entropic components (2).

Obtaining the full thermodynamic and kinetic profile of 1:1 interactions in a single ITC experiment is now possible with AFFINImeter and KinITC; in order to further exploit the potential of our analytical tools we have recently incorporated a new functionality in AFFINImeter that automatically analyzes variable temperature isothermal Titration Calorimetry assays through Van´t Hoff Plot (Ln(KA) vs 1/T), temperature dependence of ΔH (that determines changes in heat capacity, ΔCp) and Eyring plots (Ln(kon) vs 1/T and Ln(koff) vs 1/T) (3).

AFFINImeter is the only software that provides thermodynamic and kinetic information from a single ITC titration; now incorporates the automatic analysis of variable-temperature experiments.  

You can use this feature for free during one month, go to AFFINImeter webpage.


  • Freiburger L, Auclair K, Mittermaier A. Global ITC fitting methods in studies of protein allostery. Methods 2015, 76, pp 149-161.
  • GE Healthcare application note 80. Transition state thermodynamics using Biacore T100, (2007).
  • Ladbury, J. and Doyle, M. (2004). Biocalorimetry 2. Chichester: Wiley.

KinITC for TA and MicroCal Calorimeters – New version Release!

During the last months we’ve contacted you asking your opinion and experience with the software. Thanks to all your suggestions and comments we have improved the previous version of the software to make it easier, faster and more versatile.

What’s new in AFFINImeter?

  • Availability of KinITC for TA and Microcal data files.
  • Inclusion of Multi Temperature Analysis: Van’t Hoff and Eyring plots
  • The project management section has improved, now you can easily organize your projects in Folders/Subfolders and move them from one to another.


Easier, Faster and more Versatile!

In this new version you will find several changes adressed to improve the user experience of the software, adding more features, making it easier and faster to user, and more versatile.


Go to the software!

What you have learned of Isothermal Titration Calorimetry with AFFINImeter in 2015?


What you have learned of Isothermal Titration Calorimetry with AFFINImeter in 2015?

The best gift we can get these holidays is to see that our support has helped your research, leading to improved scientific publications, PhD thesis, and increased research projects successfully accomplished… Happy Holidays!!

AFFINImeter is currently the best  software for the analysis of Isothermal Titration Calorimetry data to obtain a complete thermodynamic and kinetic characterization of molecular interactions. If you are already an user  you are probably aware of all this information, anyway,  we thought that you would like to have a compilation of all the resources we have developed for divulgation and didactic purposes during this year 2015!

For the upcoming year we promise you plenty of new features and improvements in AFFINImeter!

5 Ways in which AFFINImeter can improve your research!

  1. Get more citations from your publications.
  2. Harness the full interpretation of your data
  3. Save time and Material
  4. Get kinetics information from your new and old ITC files
  5. Leave no any ITC isotherm without a fitting. (Read here)

What is the Model Builder?

As you must know with AFFINImeter  complex reaction schemes can be written to describe a real scenario in chemical language. AFFINImeter provides an exclusive “Model Builder” to write the chemical equations describing your system. We have shown you how to take advantage of the model builder.

  1. Representative binding models based on a Stoichiometric equilibria and Independent sites approach.
  2. Stoichiometric and site constants: two approaches to analyze data with AFFINImeter.
  3. The stoichiometric equilibria approach to design binding models with AFFINImeter
  4. The independent sites approach to design binding models with AFFINImeter

Guide and tutorial of How to perform a Global analysis with AFFINImeter?

Global fitting reaction parameters 13012015

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. During this year we have prepared several cases of use to show you how to solve easily complex fitting analysis, for instance a global fitting of several ITC isotherms.

KinITC: Get all the kinetic information from your ITC raw data!

We have implemented KinITC, this is a methodology recently developed by Philippe Dumas (CNRS, France) to simultaneously get kinetic and thermodynamic information from a standard ITC experiment. With one single titration experiment it calculates the kinetic constants (kon and koff) and the thermodynamic data (KD and ΔH) of 1:1 binding interactions. The current implementation of kinITC in AFFINImeter is valid only for 1:1 interactions but we intend to extend this for more complex systems in the near future.

Did you miss our Webinars? Here you can get the slides of the presentations!

Malvern Webinar:

AFFINImeter was guest presenter of the Malvern webinar on advanced Isothermal Titration Calorimetry (ITC) data analysis. (Read more).

 UNAM webinar:
The following slides corresponds to different webinars that we have done for research groups interested in learning more about AFFINImeter.

Selected AFFINImeter publications

Solving complex interactions with AFFINInimeter: Competing ligands binding to a multiple site receptor

Isothermal Titration Calorimetry (ITC) is a versatile technique with the potential of deconvoluting the various binding events that may coexist in complex interactions. In this sense, a major drawback has been the lack of mathematical models and computational tools to properly analyze such experiments. AFFINImeter counts with an advanced functionality, the “Model Builder” with which researchers can easily design their own binding models through the combination of distinct (coupled) binding equilibria, to obtain thermodynamic and structural information from complex ITC experiments.

Two Competing ligands binding to a receptor with two sites

As a demonstration of the potential of AFFINImeter and its “Model Builder”, the analysis of an ITC experiment involving a receptor “M” (biomacromolecule) with two different binding sites (s1 and s2) that may accommodate two competing ligands (“A” and ”B”) is presented here.

Download complete case here: Competitive Binding case of use