期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 111, 期 6, 页码 2075-2080出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1318405111
关键词
ion-exchange chromatography; single-molecule kinetics; bioseparations; optical nanoscopy
资金
- National Science Foundation (NSF) [CBET-1134417, CHE-1151647]
- Welch Foundation [C-1787, E-1264]
- National Institutes of Health [GM94246-01A1]
- NSF [CBET-1133965]
- Huffington-Woestemeyer Professorship
- NSF for Graduate Research Fellowship [0940902]
- Division Of Chemistry
- Direct For Mathematical & Physical Scien [1151647] Funding Source: National Science Foundation
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [1133965] Funding Source: National Science Foundation
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [1134417] Funding Source: National Science Foundation
Chromatographic protein separations, immunoassays, and biosensing all typically involve the adsorption of proteins to surfaces decorated with charged, hydrophobic, or affinity ligands. Despite increasingly widespread use throughout the pharmaceutical industry, mechanistic detail about the interactions of proteins with individual chromatographic adsorbent sites is available only via inference from ensemble measurements such as binding isotherms, calorimetry, and chromatography. In this work, we present the direct superresolution mapping and kinetic characterization of functional sites on ion-exchange ligands based on agarose, a support matrix routinely used in protein chromatography. By quantifying the interactions of single proteins with individual charged ligands, we demonstrate that clusters of charges are necessary to create detectable adsorption sites and that even chemically identical ligands create adsorption sites of varying kinetic properties that depend on steric availability at the interface. Additionally, we relate experimental results to the stochastic theory of chromatography. Simulated elution profiles calculated from the molecular-scale data suggest that, if it were possible to engineer uniform optimal interactions into ion-exchange systems, separation efficiencies could be improved by as much as a factor of five by deliberately exploiting clustered interactions that currently dominate the ion-exchange process only accidentally.
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