AFFINImeter new version!

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

What is new in this release?

  • In collaboration with Mestrelab Software, AFFINImeter can now analyze Nuclear Magnetic Resonance (NMR)  titration curves.

  • The Main toolbar has been simplified:

Data” & “Projects” have been merged into a single “Projects & Data*” menu

You can filter the elements to show by selecting “Projects & Data” (default), only “Projects” or only “Data“.

A new option has been included to easily pre-visualize the settings of your experiments directly from the list of data & projects.

The “Instruments” management menu has been removed.

*Data elements are represented by this icon –>  
*Projects elements are represented by this icon–> 

 

  • Now you can organize all your data and projects into folders:

 

  • Organize your data & projects as you would do on your computer.
  • Looking for your already existing KinITC data? Go to Projects & Data, and look into the folder “KINITC”.
  • A new parameter has been introduced to measure the quality of the FIT: Goodness of Fit

The GoF (Goodness of Fit) is the probability of finding the fitted value within a normal distribution with half-width equal to the uncertainty of each experimental point. The GoF for a curve is obtained as the mean GoF of all its points. The ideal value of perfect fit would be Gof=100%.

This parameter will be available when you execute a new FIT project/or re-execute an older project. If you visualize an already executed project, the previous parameter (χ 2) still will be present.

What have we improved from the previous version?

  • We have incorporated the possibility to perform blank subtraction right after raw data upload and processing.
  • Multiple minor usability improvements and performance tweaks.
  • Multiple bug fixes and issues suggested by our users have been implemented and resolved.

 

Try the new AFFINImeter here

The course of Isothermal Titration Calorimetry data analysis: second part

In the second part of this course, we are going to show you how to perform the analysis of binding isotherms considering an independent sites approach.
This approach uses a reaction scheme based on the binding of the ligand to individual sites present in the receptor and considering that all the sites are independent; thus, it supplies site binding constants.
This approach offers a sole reaction scheme where a receptor with a certain number of sites “n” binds to the ligand.
The sites are grouped into sets to discern between sites that are non-equivalent.

If you want to know more about how to get the stoichiometry (number of sites) and site binding constants with the independent sites approach you can click here:

Stoichiometric and site constants – two approaches to analyze data with AFFINImeter

The first video tutorial presented is about how to use an independent sites approach to perform fittings:

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Into another subject, to introduce the second fitting approach that can be performed with AFFINImeter (Stoichiometric equilibria), we will describe how to use the model builder.
This original tool allows to design and apply your own binding model in an easy way. Check the following video to know the versatility of the model builder:

Finally, if you want to try the Model Builder click here:

Model Builder

 

Stoichiometric and site constants: two approaches to analyze data with AFFINImeter.

The interaction between two species, i.e. a protein and its ligand, is defined by means of the equilibria existing between free and bound species and the binding constant(s) associated to each equilibrium. This scenario can be described in terms or reaction schemes following two approaches:

a) Based on equilibria between existing stoichiometric species, to obtain stoichiometric binding constants and

b) Based on equilibria between the ligand and specific interaction site(s) of the protein, to obtain site binding constants.

affinimeter-approaches-small

The understanding of both approaches/type of binding constants is key for a correct interpretation of the results after data analysis, in order to get key structural and mechanistic information of the binding event; i.e. the presence or absence of cooperative interactions when a ligand binds to a multivalent receptor.
The design of binding models for ITC curve fitting with AFFINImeter can be done following these two approaches, to perform analysis based on stoichiometric and/or site binding constants.

The scientific team of AFFINImeter has just released three NOTES regarding this subject to guide users into the right selection of binding model approach and a better understanding of stoichiometric vs site binding constants.

Comparative table of the two approaches for binding model design available in AFFINImeter
Characteristics of the two approaches for binding model design available in AFFINImeter

 

DOWNLOAD PDF FILES HERE:

Or visit the RESOURCES section of AFFINImeter web page where you find tutorials, webinars, cases of use, among others.

The importance of the treatment of ITC raw data in calorimetry experiments

Isothermal titration calorimetry (ITC) is an extremely sensitive technique to assess for the formation/disruption of complex chemical/biological species in solution. During the last years, the increase in instrument sensitivity as well as the reduction of the sample concentration required to perform experiments, have made possible to expand the application range of ITC, which is expected to continue growing.

Quality of the ITC Raw Data?

The amount and the quality of useful information that can be obtained from an ITC experiment depend on several factors including the purity of the samples, the concentration of the solutions prepared, the choice of injection volume and its length in time. The researcher handling the instrument is responsible for the appropiate selection of these variables as part of the experimental setup. They can be optimized on the basis of previous experience and also taking advantage of computational simulations. A key factor for this is that ITC is an incremental technique and so the results depend strongly on the injection volume employed to perform the experiment.

Kinetic information from ITC Experiments

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20th International Symposium on Surfactants in Solution (Coimbra, Portugal)

The AFFINImeter innovation team has developed an original model to analyze dissociation ITC isotherms of aggregates ranging from (protein) dimers to large supramolecular clusters (like micelles).  With this model the average number of molecules in the aggregates, the molar free energy and enthalpy of transfer from the aggregate to the solution and the dilution of both monomers and aggregates can be obtained. This model soon will be available in the AFFINImeter Software.

The validation of this model comparing our results with those determined from other experimental methods is going to be presented in the 20th International Symposium on Surfactants in Solution (SIS, June 2014), where our CSO Angel Piñeiro is giving Oral presentation on Monday  June 23, 2014.  

How to perform a neat Isothermal Titration Calorimetry experiment?

In a Isothermal Titration Calorimetry experiment, If the injected volume or any of the concentrations is too small, or if the ratio between both concentration values is not appropriate, then the signal-to-noise ratio will be low and the uncertainty of any result will be high.

Scheme of a ITC Experiment
Isothermal Titration Calorimetry Experiment

Determinant factors of poor quality results in Isothermal Titration Calorimetry Experiments

The control of these factors might be limited by the available amount or the corresponding solutes (they can be expensive or difficult to synthesize/purify). If the total number of titrations is low then the solute in the sample cell will not be saturated and the quality of the results will be poor. Additionally, in reactions for which multiple chemical species can be formed it is always better to simultaneously fit several experimental data series, each focusing the sampling in a different concentration region which is more sensitive to any of the species.

Advantages of prior Isotherm Simulation

The simulator tool provided by AFFINImeter allows you to test the effect of the parameters listed above on your experiment in order to optimize its design, thus saving time and samples.

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