树脂结构对预测单组分批量数据中的二组分蛋白质吸附行为在离子交换树脂中的影响
Jürgen Beck1, Rainer Hahn1, Giorgio Carta2
1Institute of Bioprocess Science and Engineering, Department of Biotechnology and Food Science, BOKU Vienna, Austria.
Journal of chromatography. A
|October 31, 2025
概括
在色谱学中预测蛋白质吸附对于分离过程至关重要. 一种可逆不可逆结合模型准确地预测了复杂树脂结构上的多元组件蛋白质吸附,与更简单的模型不同.
科学领域:
- 生物化学工程 生物化学工程
- 分离科学 分离科学
- 染色体学 染色体学 是一种染色学.
背景情况:
- 了解多组分吸附平衡和动力学对于设计和建模分离过程至关重要.
- 之前的工作突出了树脂结构对前置色谱中的二元组分离的影响.
研究的目的:
- 预测二进制蛋白质混合物的吸附行为,使用单元数据对离子交换树脂.
- 评估不同吸附模型在捕获蛋白质在具有明显孔隙结构的树脂上的行为方面的性能.
主要方法:
- 使用康阿尔巴 (CA) 和绿色光蛋白 (GFP) 作为模型蛋白质.
- 研究了两个离子交换树脂:Q Sepharose FF (同质毛孔) 和 POROS 50 HQ (双模毛孔).
- 采用一个孔隙扩散模型,具有竞争性的朗格穆尔异温,以及其他竞争性的双朗格穆尔和可逆不可逆结合模型.
主要成果:
- 标准孔隙扩散模型准确地预测了Q Sepharose FF上的吸附.
- 这种模型低估了POROS 50 HQ的GFP绑定能力的两倍.
- 可逆不可逆结合模型准确地预测了POROS 50 HQ的平衡和动力数据 (平均偏差<15%).
结论:
- POROS 50 HQ的双模孔结构显著影响了GFP的结合能力.
- 先进的机械模型,如可逆-不可逆结合模型,对于预测复杂色谱系统中的多元组件吸附是必要的.
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