Exploration of Protein Unfolding by Modelling Calorimetry Data from Reheating

Authors

Mazurenko, S., Kunka, A., Beerens, K., Damborsky, J., Prokop, Z.

Source

SCIENTIFIC REPORTS 7: 16321 (2017)

Abstract

Studies of protein unfolding mechanisms are critical for understanding protein functions inside cells, de novo protein design as well as defining the role of protein misfolding in neurodegenerative disorders. Calorimetry has proven indispensable in this regard for recording full energetic profiles of protein unfolding and permitting data fitting based on unfolding pathway models. While both kinetic and thermodynamic protein stability are analysed by varying scan rates and reheating, the latter is rarely used in curve-fitting, leading to a significant loss of information from experiments. To extract this information, we propose fitting both first and second scans simultaneously. Four most common single-peak transition models are considered: (i) fully reversible, (ii) fully irreversible, (iii) partially reversible transitions, and (iv) general three-state models. The method is validated using calorimetry data for chicken egg lysozyme, mutated Protein A, three wild-types of haloalkane dehalogenases, and a mutant stabilized by protein engineering. We show that modelling of reheating increases the precision of determination of unfolding mechanisms, free energies, temperatures, and heat capacity differences. Moreover, this modelling indicates whether alternative refolding pathways might occur upon cooling. The Matlab-based data fitting software tool and its user guide are provided as a supplement.

Full text

Citation

Mazurenko, S., Kunka, A., Beerens, K., Damborsky, J., Prokop, Z., 2017: Exploration of Protein Unfolding by Modelling Calorimetry Data from Reheating. Scientific Reports 7: 16321.

Open Postdoc Position: Protein Engineering
Ondrej Vavra selected among Southmoravian PhD Talents
Professor Damborsky among Ceska hlava 2017 laureates
Ondrej Vavra celebrating success with his presentation on CaverDock
Lecture by Dr. Stavrakis from ETH Zurich
High evaluation of the team’s research performance
Klaudia Chmelova and Veronika Liskova passed doctoral state exam