Recognition of the thermal dissociation/denaturation mechanisms for multimeric proteins through DSC experiments: a thermodynamic insight

• Thermograms differ according to the protein dissociation/denaturation mechanism • Stand-alone thermodynamic equations depict common protein dissociation mechanisms • Ready-to-use mathematical solutions are available for homomer thermodynamic analysis The importance of knowing the conformational structure of a protein and the related mechanism of denaturation stems from the crucial role that these macromolecules perform in the biological world, and hence the wide spectrum of possible applications in the frame of biological and pharmaceutical research activities. However, in a biological context where a significant number of proteins exists as multimers, stand-alone thermodynamic equations able to simulate and fit Differential Scanning Calorimetry (DSC) profiles involving dissociation phenomena are still missing: different valuable models have been reported in the literature since the 1980s but all were based on the application of experimental protein conversion fractions from the native to the dissociated/denatured state. In this frame, the present work develops thermodynamic equations that are completely independent of experimental data and are related to three main models: i) N n ↔ n D ; ii) N n ↔ n M ↔ n D ; iii) N n ↔ I n ↔ n D . Beside inspecting the influence of each fitting parameter on the theoretical C p ( T ) curve for the single models, two applications to experimental results are also discussed. Furthermore, aiming at simplifying the application of thermodynamic equations to proteins of biological and/or pharmaceutical interest, the work develops extensively the solutions for all the models considering the most common homomers, i.e. , dimers, trimers, and tetramers. The methodology and strategy proposed here, that link statistical mechanics concepts (canonical partition function) with the classical thermodynamics’ equilibrium constant, are general and pave the way for the development of models that may reflect more complex scenarios than those considered in this work, if the case.