Modeling complex equilibria in isothermal titration calorimetry experiments: thermodynamic parameters estimation for...

Area of Science:

• Biophysical Chemistry
• Thermodynamics
• Biochemistry

Background:

• Isothermal titration calorimetry (ITC) is a key method for characterizing ligand-binding interactions.
• Standard ITC software supports simple binding models (e.g., one or two binding sites).
• Complex binding scenarios often require custom thermodynamic models and analysis, posing a challenge for researchers.

Purpose of the Study:

• To develop and present an algorithm for analyzing complex ligand-binding equilibria using ITC data.
• To enable the accurate estimation of thermodynamic parameters for models with multiple overlapping binding sites.

Main Methods:

• Development of a nonlinear regression algorithm for analyzing ITC data.
• Implementation of the algorithm for models with up to four overlapping binding equilibria.
• Utilizing MATLAB for the computational analysis and providing the program.

Main Results:

• The developed algorithm successfully performs nonlinear regression analysis for multiple-binding-site models.
• Error analysis confirms that fitting ITC data with multiple parameters (up to nine) yields accurate thermodynamic parameters.
• The approach is applicable to complex scenarios like multiple overlapping binding equilibria.

Conclusions:

• The presented algorithm enhances the capability of ITC for studying intricate ligand-binding systems.
• Researchers can now more accurately quantify thermodynamic parameters in complex biological interactions.
• This work provides a valuable tool for advancing the understanding of molecular recognition events.