Ihms Elihu C, Kleckner Ian R, Gollnick Paul, Foster Mark P
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio.
Department of Biological Sciences, State University of New York at Buffalo, Buffalo, New York.
Biophys J. 2017 Apr 11;112(7):1328-1338. doi: 10.1016/j.bpj.2017.02.031.
Allostery pervades macromolecular function and drives cooperative binding of ligands to macromolecules. To decipher the mechanisms of cooperative ligand binding it is necessary to define at a microscopic level the structural and thermodynamic consequences of binding of each ligand to its allosterically coupled site(s). However, dynamic sampling of alternative conformations (microstates) in allosteric molecules complicates interpretation of both structural and thermodynamic data. Isothermal titration calorimetry has the potential to directly quantify the thermodynamics of allosteric interactions, but usually falls short of enabling mechanistic insight. This is because 1) its measurements reflect the sum of overlapping caloric processes involving binding-linked population shifts within and between microstates, and 2) data are generally fit with phenomenological binding polynomials that are underdetermined. Nevertheless, temperature-dependent binding data have the potential to resolve overlapping thermodynamic processes, while mechanistically constrained models enable hypothesis testing and identification of informative parameters. We globally fit temperature-dependent isothermal titration calorimetry data for binding of 11 tryptophan ligands to the homo-undecameric trp RNA-binding Attenuation Protein from Bacillus stearothermophilus using nearest-neighbor statistical thermodynamic models. This approach allowed us to distinguish alternative nearest-neighbor interaction models, and quantifies the thermodynamic contribution of neighboring ligands to individual binding sites. We also perform conventional Hill equation modeling and illustrate how comparatively limited it is in quantitative or mechanistic value. This work illustrates the potential of mechanistically constrained global fitting of binding data to yield the microscopic thermodynamic parameters essential for deciphering mechanisms of cooperativity in a wide range of ligand-regulated homo-oligomeric assemblies.
变构作用普遍存在于大分子功能中,并驱动配体与大分子的协同结合。为了解析协同配体结合的机制,有必要在微观层面定义每个配体与其变构偶联位点结合的结构和热力学后果。然而,变构分子中替代构象(微观状态)的动态采样使结构和热力学数据的解释变得复杂。等温滴定量热法有潜力直接量化变构相互作用的热力学,但通常无法提供机制性的见解。这是因为:1)其测量反映了涉及微观状态内和微观状态间结合相关群体转移的重叠热过程的总和;2)数据通常用欠定的现象学结合多项式拟合。尽管如此,温度依赖性结合数据有潜力解析重叠的热力学过程,而机制受限模型能够进行假设检验并识别信息参数。我们使用最近邻统计热力学模型对11种色氨酸配体与嗜热栖热放线菌的同十一聚体trp RNA结合衰减蛋白的结合进行了温度依赖性等温滴定量热数据的全局拟合。这种方法使我们能够区分替代的最近邻相互作用模型,并量化相邻配体对各个结合位点的热力学贡献。我们还进行了传统的希尔方程建模,并说明了其在定量或机制价值方面的局限性。这项工作说明了对结合数据进行机制受限的全局拟合以产生破译广泛的配体调节同寡聚体组装体中协同作用机制所必需的微观热力学参数的潜力。