Determination of thermodynamic functions from scanning calorimetry data. II. For the system that includes self‐dissociation / association process

Abstract

SynopsisThe basic relations between the molar fractions and the scanning calorimetry data for the system that includes self-dissociation/asociation process such as m,A, * m,A, F? m,A, F? ... * mnAn are presented, where m, is the stoichiometric coefficient of the zth state Ai. The relations are described for each state j as where f i ( T ) is the molar fraction function of state j and AHj(T) is the difference enthalpy function of the system referred to the state j , which can be obtained by scanning calorimetry; R is the gas constant; and T is the absolute temperature. By these relations, scanning calorimetry data can be deconvoluted in order to determine the thermodynamic functions by means of single and double deconvolution. The concentration dependence of the data is analyzed by a method presented in this paper. The nonlinear least squares fitting method for the determination of the functions is discussed. For an example of the application of this method to the actual scanning calorimetry data, thermodynamic data of multistate thermal transition of Vibrio parahaemolyticus hemolysin are analyzed.

Domain organization of flagellar hook protein from Salmonella typhimurium

“…The ratio of the calorimetric and the effective van't Hoff enthalpies is significantly larger than 1.0 in both cases; therefore, these calorimetric profiles reflect multistate transitions [13], suggesting that H32 and H22 are composed of multiple cooperative folding units, or domains. The double deconvolution method of Kidokoro and Wada [10]followed by a non‐linear least‐square fitting procedure [11, 12]was applied to analyze the multistate thermal denaturation of H32 and H22. The results of this analysis are illustrated in Table 2 .…”

“…The heat capacity functions of hook fragments were analyzed by the double deconvolution procedure of Kidokoro and Wada [10], assuming that the native state heat capacities are quadratic functions of the temperature and the heat capacity changes between the native and intermediate states are constants. The obtained thermodynamic parameters were further adjusted by a non‐linear least‐square fitting method [11]using the SALS program [12].…”

Thermodynamic Properties of BPTI Variants with Highly Simplified Amino Acid Sequences

“…The global fitting determines common values for the thermodynamic parameters (ΔH Tm , T m , ΔC p ) that simultaneously fit all of the experimental heat capacity curves. 36,37 Thermodynamic functions…”

“…The thermodynamic parameters were first determined by analyzing the individual apparent heat capacity curves with a two-state model using a non-linear least-square fitting method, 35 and a linear temperature dependence of the heat capacity of the native and denatured states. 36 The results were used as initial values for determining the thermodynamic parameters by a global fitting of all of the denaturation curves obtained at different pH values. The global fitting determines common values for the thermodynamic parameters (ΔH Tm , T m , ΔC p ) that simultaneously fit all of the experimental heat capacity curves.…”

Protein heat capacity reflects the dynamics of enthalpy exchange between the single macromolecule and the surroundings

“…The advantage of using statistical mechanics for the analysis of the energetic properties of proteins has been shown convincingly in a series of pioneering articles 1–15. Particularly the view that a protein solution can be considered, in the Gibbsian sense, as a canonical ensemble of small, yet macroscopic systems immersed in a heat bath has been emphasized by Cooper in two pivotal studies 4, 5.…”