Semi-empirical Analysis of Complex ITC Data from Protein-Surfactant Interactions

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Isothermal titration calorimetry (ITC) is a widely used method to determine binding affinities and thermodynamics in ligand-receptor interactions, but it also has the capability of providing detailed information on much more complex events. However, the lack of available methods to analyze ITC data is limiting the use of the technique in such multifaceted cases. Here, we present the software ANISPROU. Through a semi-empirical approach that allows for extraction of quantitative information from complex ITC data, ANISPROU solves an inverse problem where three parameters describing a set of predefined functions must be found. In analogy to strategies adopted in other scientific fields, such as geophysics, imaging, and many others, it employs an optimization algorithm which minimizes the difference between calculated and experimental data. In contrast to the existing methods, ANISPROU provides automated and objective analysis of ITC data on sodium dodecyl sulfate (SDS)-induced protein unfolding, and in addition, more information can be extracted from the data. Here, data series on SDS-mediated protein unfolding is analyzed, and binding isotherms and thermodynamic information on the unfolding events are extracted. The obtained binding isotherms as well as the enthalpy of different events are similar to those obtained using the existing manual methods, but our methodology ensures a more robust result, as the entire data set is used instead of single data points. We foresee that ANISPROU will be useful in other cases with complex enthalpograms, for example, in cases with coupled interactions in biomolecular, polymeric, and amphiphilic systems including cases where both structural changes and interactions occur simultaneously.

OriginalsprogEngelsk
TidsskriftAnalytical Chemistry
Vol/bind93
Udgave nummer37
Sider (fra-til)12698-12706
Antal sider9
ISSN0003-2700
DOI
StatusUdgivet - 21 sep. 2021

ID: 281222542