A mechanistic examination of salting out in protein–polymer membrane interactions
A mechanistic examination of salting out in protein–polymer membrane interactions
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DOI:
10.1073/pnas.1909860116
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发表时间:
2019-10
期刊:
影响因子:
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通讯作者:
Nicholas A Moringo;Logan D. C. Bishop;Hao Shen;Anastasiia Misiura;Nicole C. Carrejo;Rashad Baiyasi;
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文献类型:
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作者:
Nicholas A Moringo;Logan D. C. Bishop;Hao Shen;Anastasiia Misiura;Nicole C. Carrejo;Rashad Baiyasi;
Significance Membrane-based protein separations are utilized broadly, and increasingly, to purify proteins for research and biopharmaceuticals. Like all steps in the purification process, the salt concentration is adjusted empirically in the mobile phase to elute a desired component of a protein mixture. There is insufficient quantitative description about the salting out process to allow for predictive optimization. By quantifying the interactions and kinetics of single proteins at the surface of a membrane as salt concentration is increased, we relate mechanistic nanoscale observables to an improvement in the peak broadness observed in real separations. This result suggests that simulations, informed by small-scale single-molecule observations, could be used to optimize separation conditions, leading to more efficient separations. Developing a mechanistic understanding of protein dynamics and conformational changes at polymer interfaces is critical for a range of processes including industrial protein separations. Salting out is one example of a procedure that is ubiquitous in protein separations yet is optimized empirically because there is no mechanistic description of the underlying interactions that would allow predictive modeling. Here, we investigate peak narrowing in a model transferrin–nylon system under salting out conditions using a combination of single-molecule tracking and ensemble separations. Distinct surface transport modes and protein conformational changes at the negatively charged nylon interface are quantified as a function of salt concentration. Single-molecule kinetics relate macroscale improvements in chromatographic peak broadening with microscale distributions of surface interaction mechanisms such as continuous-time random walks and simple adsorption–desorption. Monte Carlo simulations underpinned by the stochastic theory of chromatography are performed using kinetic data extracted from single-molecule observations. Simulations agree with experiment, revealing a decrease in peak broadening as the salt concentration increases. The results suggest that chemical modifications to membranes that decrease the probability of surface random walks could reduce peak broadening in full-scale protein separations. More broadly, this work represents a proof of concept for combining single-molecule experiments and a mechanistic theory to improve costly and time-consuming empirical methods of optimization.