Use and elucidation of biochemical data in the prediction of the membrane separation of biocolloids
Use and elucidation of biochemical data in the prediction of the membrane separation of biocolloids
复制标题
DOI：
10.1098/rspa.1999.0433
复制
发表时间：
1999-08-08
影响因子：
3.5
通讯作者：
Williams, PM
中科院分区：
文献类型：
--
作者：
Bowen, WR;Cao, XW;Williams, PM
生物技术工业中大规模工艺的成功设计和操作需要有效的工艺性能预测方法。这种预测方法应该基于对被加工材料的物理化学性质的了解。生物过程工程预测的一个主要挑战是利用复杂的三维结构信息，这些信息现在可用于许多生物材料。本论文开发了一种重要的分离方法：重组蛋白的膜超滤，在这种情况下是人乳铁蛋白。这种蛋白质被当作生物胶体处理。根据蛋白质的氨基酸序列和结构数据，以及实验测量的zeta电位，建立了考虑氯离子结合的乳铁蛋白-溶液界面的电荷调节模型。然后将该表面模型纳入蛋白质膜超滤速率的预测过程模型，该模型以复杂的方式考虑了发生在膜表面附近并控制该过程速率的蛋白质-蛋白质相互作用（静电、伦敦-范德华和熵）。通过实验得到的过程数据与模型预测的比较，发现乳铁蛋白分子之间存在进一步的吸引相互作用，这种相互作用可以通过指数衰减项来量化。在过程模型中结合这种相互作用，可以在广泛的溶液条件下成功地预测超滤速率。进一步吸引相互作用的存在已被渗透压测量定量地证实。因此，本文展示了如何将详细的结构信息成功地用于过程预测。它还显示了如何分析过程数据本身可以提供生物胶体相互作用的定量信息。随着生物过程工程师将生物科学的最新发现纳入成功工业过程的开发，这种方法可能变得越来越重要。
The successful design and operation of large-scale processes in the biotechnological industries requires effective methods for the prediction of process performance. Such predictive methods should be based on a knowledge of the physicochemical properties of the materials being processed. A major challenge for prediction in biological process engineering is to make use of the sophisticated three-dimensional structural information that is now available for many biological materials.The present paper develops such an approach for an important type of separation: the membrane ultrafiltration of a recombinant protein, in this case human lactoferrin. The protein is treated as a biocolloid. From the available amino acid sequence and structural data for the protein, together with the experimentally measured zeta potential, a charge-regulation model for the lactoferrin-solution interface is developed that takes into account chloride-ion binding. This surface model is then incorporated into a predictive process model for the rate of membrane ultrafiltration of proteins, which takes into account, in a sophisticated manner, the protein-protein interactions (electrostatic, London-van der Waals and entropic) that take place close to the membrane surface and which control the rate of the process. By comparison of the experimentally obtained process data with model predictions it is found that a further attractive interaction between lactoferrin molecules is present, which can be quantified through an exponential decay term. Incorporation of such an interaction in the process model allows successful prediction of the rate of ultrafiltration over a wide range of solution conditions. The existence of the further attractive interaction has been quantitatively verified by osmotic pressure measurements.Hence, the paper shows how detailed structural information may be successfully used for process prediction. It also shows how analysis of process data may itself provide quantitative information on the interactions of biocolloids. This type of approach is likely to become increasingly important as biological process engineers incorporate the latest findings in the biosciences into the development of successful industrial processes.