Dzakula Z, Andjus R K, Bozić M
Biophysical Laboratory, University of Belgrade, Yugoslavia.
J Theor Biol. 1991 Nov 7;153(1):61-88. doi: 10.1016/s0022-5193(05)80353-4.
In order to broaden the scope and increase the utility of differential scanning calorimetry, a theoretical model of calorimetric thermograms is presently proposed which facilitates their biophysical interpretation and accounts explicitly for their modifications induced by denaturing agents and/or pH. The model rests mainly on statistical-physical considerations, the denaturation-linked increase of the number of binding sites for denaturants (including H+) serving as the conceptual basis for thermogram modelling. Denaturants were envisioned as contributing indirectly to thermal denaturation by forming complexes preferentially with unfolded protein molecules, shifting thus the equilibrium towards the denatured phase. After postulating the probability of complex formation, mean numbers of the relevant molecular species were computed by ensemble averaging. Finally, an eight-parameter expression has been derived defining protein heat capacity as a function of both temperature and denaturant concentration (or pH), each of the eight parameters having a distinct biophysical meaning. The model has been tested by applying it to the prediction of the pH-dependence of thermograms. Four proteins have been considered (lysozyme, myoglobin, apomyoglobin, and ribonuclease A), each represented by a series of three to four published thermograms recorded under different pH conditions. Model equations, fitted simultaneously to all thermograms in a pH series, reproduced correctly experimental tracings. Parameter values obtained as best-fit requirements (particularly those representing the number of binding sites unmasked by denaturation and the free energy of ion binding) were in close agreement with empirical, mainly potentiometric, data from literature. The empirically established pH-independence of the total enthalpy of denaturation, the phenomenon of cold denaturation, the pH-dependence of the Gibbs free energy of denaturation, of the melting temperature and of the temperature of cold denaturation, were all correctly predicted by the model. Combined effects of multiple denaturants, including the effects of pH in the presence of denaturants other than protons, are also predictable by the model.
为了拓宽差示扫描量热法的应用范围并提高其实用性,目前提出了一种量热热谱图的理论模型,该模型有助于对其进行生物物理解释,并明确说明了变性剂和/或pH值引起的热谱图变化。该模型主要基于统计物理考虑,变性剂(包括H +)结合位点数量的变性相关增加作为热谱图建模的概念基础。变性剂被设想为通过优先与未折叠的蛋白质分子形成复合物而间接促进热变性,从而使平衡向变性相转移。在假设复合物形成的概率之后,通过系综平均计算相关分子种类的平均数。最后,推导出了一个八参数表达式,将蛋白质热容量定义为温度和变性剂浓度(或pH值)的函数,八个参数中的每一个都具有独特的生物物理意义。该模型已通过将其应用于热谱图pH依赖性的预测进行了测试。考虑了四种蛋白质(溶菌酶、肌红蛋白、脱辅基肌红蛋白和核糖核酸酶A),每种蛋白质由在不同pH条件下记录的三到四个已发表的热谱图系列表示。同时拟合pH系列中所有热谱图的模型方程正确地再现了实验曲线。作为最佳拟合要求获得的参数值(特别是那些代表变性后暴露的结合位点数量和离子结合自由能的参数值)与文献中的经验数据(主要是电位滴定数据)密切一致。该模型正确预测了经验确定的变性总焓的pH独立性、冷变性现象、变性吉布斯自由能、解链温度和冷变性温度的pH依赖性。多种变性剂的联合作用,包括在除质子以外的变性剂存在下pH的影响,该模型也可预测。