Unified superresolution experiments and stochastic theory provide mechanistic insight into protein ion-exchange adsorptive separations

Significance Adsorption of proteins underlies the purification of biopharmaceuticals, as well as therapeutic apheresis, immunoassays, and biosensors. In particular, separation of proteins by interactions with charged ligands on surfaces (ion-exchange chromatography) is an essential tool of the modern pharmaceutical industry. By quantifying the interactions of single proteins with individual charged ligands, we demonstrate that clusters of charges are necessary to create functional adsorption sites and that even chemically identical ligands create sites of varying kinetic properties that depend on steric availability at the interface. 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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