Pineda Sebastian P, Blanco Pablo M, Staňo Roman, Košovan Peter
Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University, Hlavova 8, 128 40 Prague 2, Czech Republic.
Department of Physics, NTNU - Norwegian University of Science and Technology, NO-7491 Trondheim, Norway.
Langmuir. 2025 Mar 4;41(8):5387-5398. doi: 10.1021/acs.langmuir.4c04942. Epub 2025 Feb 18.
When using dialysis ultra- or diafiltration to purify protein solutions, a dialysis buffer in the permeate is employed to set the pH in the protein solution. Failure to achieve the target pH may cause undesired precipitation of the valuable product. However, the pH in the permeate differs from that in the retentate, which contains the proteins. Experimental optimization of the process conditions is time-consuming and expensive, while accurate theoretical predictions still pose a major challenge. Current models of dialysis account for the Donnan equilibrium, acid-base properties, and ion-protein interactions, but they neglect the patchy distribution of ionizable groups on the proteins and its impact on the solution properties. Here, we present a simple computational model of a colloidal particle with weakly acidic sites on the surface, organized in patches. This minimalistic model allows systematic variation of the relevant parameters, while simultaneously demonstrating the essential physics governing the acid-base equilibria in protein solutions. Using molecular simulations in the Grand-Reaction ensemble, we demonstrate that interactions between ionizable sites significantly affect the nanoparticle charge and thereby contribute to pH difference between the permeate and retentate. We show that the significance of this contribution increases if the ionizable sites are located on a smaller patch. Protein solutions are governed by the same physics as our simple model. In this context, our results show that models which aim to quantitatively predict the pH in protein solutions during dialysis need to account for the patchy distribution of ionizable sites on the protein surface.
在使用透析超滤或渗滤纯化蛋白质溶液时，渗透液中的透析缓冲液用于调节蛋白质溶液的pH值。未能达到目标pH值可能会导致有价值的产物发生不期望的沉淀。然而，渗透液中的pH值与含有蛋白质的截留液中的pH值不同。对工艺条件进行实验优化既耗时又昂贵，而准确的理论预测仍然是一项重大挑战。目前的透析模型考虑了唐南平衡、酸碱性质和离子-蛋白质相互作用，但它们忽略了蛋白质上可电离基团的斑块状分布及其对溶液性质的影响。在这里，我们提出了一个简单的胶体颗粒计算模型，其表面具有呈斑块状分布的弱酸性位点。这个简约模型允许对相关参数进行系统变化，同时展示了控制蛋白质溶液中酸碱平衡的基本物理原理。通过在大反应系综中进行分子模拟，我们证明了可电离位点之间的相互作用会显著影响纳米颗粒的电荷，从而导致渗透液和截留液之间的pH值差异。我们表明，如果可电离位点位于较小的斑块上，这种贡献的重要性会增加。蛋白质溶液受与我们的简单模型相同的物理原理支配。在这种情况下，我们的结果表明，旨在定量预测透析过程中蛋白质溶液pH值的模型需要考虑蛋白质表面可电离位点的斑块状分布。
