Department of Chemical and Biological Engineering, Iowa State University, Ames, IA 50011, USA.
J Chromatogr A. 2012 Aug 3;1249:103-14. doi: 10.1016/j.chroma.2012.06.009. Epub 2012 Jun 12.
The most significant cost of recombinant protein production lies in the optimization of the downstream purification methods, mainly due to a lack of knowledge of the separation behavior of the host cell proteins (HCP). To reduce the effort required for purification process development, this work was aimed at modeling the separation behavior of a complex mixture of proteins in cation-exchange chromatography (CEX). With the emergence of molecular pharming as a viable option for the production of recombinant pharmaceutical proteins, the HCP mixture chosen was an extract of corn germ. Aqueous two phase system (ATPS) partitioning followed by two-dimensional electrophoresis (2DE) provided data on isoelectric point, molecular weight and surface hydrophobicity of the extract and step-elution fractions. A multivariate random forest (MVRF) method was then developed using the three characterization variables to predict the elution pattern of individual corn HCP. The MVRF method achieved an average root mean squared error (RMSE) value of 0.0406 (fraction of protein eluted in each CEX elution step) for all the proteins that were characterized, providing evidence for the effectiveness of both the characterization method and the analysis approach for protein purification applications.
重组蛋白生产的最大成本在于下游纯化方法的优化，主要是因为缺乏对宿主细胞蛋白（HCP）分离行为的了解。为了减少纯化工艺开发所需的工作量，这项工作旨在对阳离子交换色谱（CEX）中复杂蛋白质混合物的分离行为进行建模。随着分子制药作为生产重组药物蛋白的可行选择的出现，所选择的 HCP 混合物是玉米胚芽的提取物。双水相系统（ATPS）分配和二维电泳（2DE）提供了提取物和分步洗脱部分的等电点、分子量和表面疏水性的数据。然后，使用三个特征变量开发了一种多元随机森林（MVRF）方法，以预测单个玉米 HCP 的洗脱模式。MVRF 方法对所有被表征的蛋白质的平均均方根误差（RMSE）值为 0.0406（在每个 CEX 洗脱步骤中洗脱的蛋白质分数），为表征方法和用于蛋白质纯化应用的分析方法的有效性提供了证据。
