cEST: a flexible tool for calorimetric data analysis

A new MS-Excel utility based on the EST speciation tool (cEST) specifically designed to be applied to the analysis of calorimetric data is presented in this work. The cEST utility is able to fit calorimetric data with species of arbitrary stoichiometry and also automatically provides a complex statistical analysis of data fitting. This latter aspect is often very useful to discriminate the goodness of fit for different models. As cEST runs under MS-Excel, it is flexible in its implementation and allows a straightforward data import and graphing. Furthermore, it is open source and can be used within both Windows and MacOS operating systems. The applicability of cEST is tested toward data of different origin: experimental data, where the complex formation between Ag+, Co2+ and Cd2+ ions and terpyridine in anhydrous DMSO is studied, and simulated ITC points for biomolecular interactions with either two- or three-binding sites. In the case of metal complex formation, the combination with regression statistics allows the choice of the best model among those for which convergence is achieved. In this case, the Akaike Information Criterion is employed for selecting the model for the metal-terpyridine speciation. Our analysis, based on independent calorimetric data, provides models and thermodynamic parameters which are in good agreement with those of the original works obtained by combining different complementary techniques. Also, in all the examined cases, the results obtained for the biomolecular interactions provide thermodynamic parameters which are strictly in line with the published results.

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