CalFitter: a web server for analysis of protein thermal denaturation data

Area of Science:

• Biophysics
• Structural Biology
• Computational Biology

Background:

• Understanding protein folding pathways is crucial but limited by experimental tools and data analysis methods.
• Existing tools for analyzing protein thermal denaturation data are often experiment-specific and offer limited model selection.
• Accurate data analysis is essential for interpreting results from techniques like calorimetry and spectroscopy.

Purpose of the Study:

• To develop a unified web server, CalFitter, for comprehensive data fitting and analysis of protein thermal denaturation data.
• To provide a platform with a wide selection of protein unfolding pathway models, including those for irreversible transitions.
• To facilitate interactive analysis and simulation of protein unfolding pathways.

Main Methods:

• Development of the CalFitter web server, a unified platform for data analysis.
• Implementation of simultaneous global data fitting for various experimental data types.
• Inclusion of 12 distinct protein unfolding pathway models, accommodating irreversible transitions.

Main Results:

• CalFitter enables comprehensive analysis of protein thermal denaturation data.
• The server supports simultaneous global fitting across multiple data types.
• It offers 12 unfolding pathway models, including often-omitted irreversible transitions, and provides optimal parameters and confidence intervals.

Conclusions:

• The CalFitter web server provides a versatile and user-friendly solution for analyzing protein thermal denaturation data.
• It enhances the study of protein folding pathways by offering a broader range of models and integrated analysis capabilities.
• The platform facilitates direct user interaction for data analysis and model simulation, accessible at https://loschmidt.chemi.muni.cz/calfitter/.