Bio-Molecular Thermodynamics of Protein Precipitation in Aqueous Solutions

实验和理论生物处理研究的目的是建立一个从水溶液中的蛋白质混合物中分离出目标蛋白质的分子-热动力学模型。蛋白质的分离是通过盐类、非离子聚合物或两者都诱导的沉淀来实现的。得到的系统由两个平衡的液体相组成，其中一个富含目标蛋白质。提出了一个描述蛋白质沉淀相平衡的分子热力学模型。这个模型源于对沉淀溶液中分子间力的理解；它使用平均球近似将参照系定义为带电硬球的混合物。对这个参照系的摄动是色散力、偶极-偶极力，或许还有特定的联结力的结果。根据该模型计算的渗透压将与由膜渗透压计获得的渗透压数据以及通过低角激光散射测量的渗透第二维里系数进行比较。实验相平衡(沉淀)测量将提供可与分子热力学模型进行比较的数据。当蛋白质发生显著聚集时，来自光散射的蛋白质聚集尺寸分布数据将被用来补充理论。这项研究的目的是为蛋白质沉淀过程的合理设计建立一种面向工程的相关性。这项研究的长期好处是，它可能为更好地理解蛋白质结晶生物过程提供有用的知识。

Experimental and theoretical bio-processing studies are directed toward the development of a molecular-thermodyamic model for separationg a target protein from a mixture of proteins in aqueuous solution. Protein separation is achieved by precipitation induced by salts, nonionic polymers, or both. The resulting system consists of two liquid phases in equilbrium, with one enriched in the target protein. A molecular-thermosynamic model is outlined for describing protein-precipitation phase equilibria. This model is derived from an understanding of the intermolecular forces in the precipitating solutions; it uses the mean-spherical- approximation to define the reference system as a mixture of charged hard spheres. Pertubations to this reference system result from the dispersion forces, dipole-dipole forces and perhaps, specific association forces. Osmotic pressures calculated from the model will be compared to osmotic-pressure data obtained from membrane osmometry and to osmotic second virial coefficients measured by low-angle laser-light scattering. Experimental phase-equilibrium (precipitation) measurements will provide data against which the molecular- thermodynamic model can be compared. Protein aggregate size distribution data from light scattering will be used to augment the theory when significant aggregation occurs. The goal of this reech is to establish an engineering-oriented correlation for the rational design of protein-precipitation processes. The long-range benefit of this research is that it is likely to provide useful knowledge for a better understanding of protein crystallization bioprocesses.