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

Area of Science:

• Biochemistry
• Biophysics
• Computational Biology

Background:

• Isothermal titration calorimetry (ITC) is a powerful technique for studying binding affinities and thermodynamics.
• Analyzing complex ITC data, especially for events like protein unfolding, is challenging due to a lack of specialized methods.
• Existing methods for complex ITC data analysis are often manual and subjective.

Purpose of the Study:

• To introduce ANISPROU, a novel software for the automated and objective analysis of complex ITC data.
• To demonstrate ANISPROU's capability in extracting quantitative thermodynamic information from sodium dodecyl sulfate (SDS)-induced protein unfolding.
• To provide a robust method for analyzing multifaceted biomolecular interactions using ITC.

Main Methods:

• ANISPROU employs a semi-empirical approach to solve an inverse problem by optimizing parameters against experimental ITC data.
• The software utilizes an optimization algorithm, analogous to those in geophysics and imaging, to minimize data discrepancies.
• Automated analysis of SDS-induced protein unfolding data was performed using ANISPROU.

Main Results:

• ANISPROU successfully extracted binding isotherms and thermodynamic information from SDS-mediated protein unfolding data.
• The results obtained using ANISPROU are comparable to existing manual methods but offer enhanced robustness by utilizing the entire dataset.
• The software provides objective and automated analysis, overcoming limitations of previous techniques.

Conclusions:

• ANISPROU offers a significant advancement in analyzing complex ITC data, particularly for protein unfolding.
• The software is expected to be valuable for studying coupled interactions in various systems, including biomolecular, polymeric, and amphiphilic systems.
• ANISPROU facilitates a more comprehensive understanding of simultaneous structural changes and interactions.