Framework for Optimizing Polymeric Supports for Immobilized Biocatalysts by Computational Analysis of Enzyme Surface Hydrophobicity

Abstract

Immobilization is a powerful strategy for improving enzyme usability and stability in various technologies that employ biocatalysis. However, the interactions leading to stabilization or destabilization remain poorly understood, and a support that may stabilize one enzyme may destabilize another. Employing chemically heterogeneous and complex random copolymer brushes as supports, we demonstrate a rational approach toward estimating the chemical composition of an optimally stabilizing enzyme immobilization support by computational analysis of enzyme surface hydrophobicity. This approach was tested by immobilizing a range of enzymes with diverse functions and hydrophobicity on tunable statistical random copolymer brush supports composed of poly(ethylene glycol) methacrylate (PEGMA) and sulfobetaine methacrylate (SBMA). Remarkably, we observed greatly improved enzyme performance as a function of brush composition with enhancements in the retention of catalytic activity at temperatures as high as 90 °C. Additionally, we observed an increase in activity at the optimal temperature by as much as 20-fold relative to the activity at the optimal temperature of the unimmobilized form of the enzyme. Most significantly, our results showed that the optimal composition of the brush support correlated with the overall hydrophobicity of the enzyme surface (ΔGsolv,total/area), which was determined from computational analysis. This correlation provides a framework for the choice of polymer brush supports based on enzyme structure and stabilizing enzymes using complex synthetic materials.