| Literature DB >> 31659038 |
Nicholas A Moringo1, Logan D C Bishop1, Hao Shen1, Anastasiia Misiura1, Nicole C Carrejo1, Rashad Baiyasi2, Wenxiao Wang2, Fan Ye2, Jacob T Robinson2,3, Christy F Landes4,2,5,6.
Abstract
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.Entities:
Keywords: membrane chromatography; salting out; single-molecule tracking; stochastic theory of chromatography
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Year: 2019 PMID: 31659038 PMCID: PMC6859367 DOI: 10.1073/pnas.1909860116
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205