Combinatorial High-Throughput Screening of Complex Polymeric Enzyme Immobilization Supports

Recent advances have demonstrated the promise of complex multicomponent polymeric supports to enable supra-biological enzyme performance. However, the discovery of such supports has been limited by time-consuming, low-throughput synthesis and screening. Here, we describe a novel combinatorial and high-throughput platform that enables rapid screening of complex and heterogeneous copolymer brushes as enzyme immobilization supports, named combinatorial high-throughput enzyme support screening (CHESS). Using a 384-well plate format, we synthesized arrays of three-component polymer brushes in the microwells using photoactivated surface-initiated polymerization and immobilized enzymes in situ. The utility of CHESS to identify optimal immobilization supports under thermally and chemically denaturing conditions was demonstrated usingBacillus subtilisLipase A (LipA). The identification of supports with optimal compositions was validated by immobilizing LipA on polymer-brush-modified biocatalyst particles. We further demonstrated that CHESS could be used to predict the optimal composition of polymer brushes a priori for the previously unexplored enzyme, alkaline phosphatase (AlkP). Our findings demonstrate that CHESS represents a predictable and reliable platform for dramatically accelerating the search of chemical compositions for immobilization supports and further facilitates the discovery of biocompatible and stabilizing materials.

Supra-biological performance of immobilized enzymes enabled by chaperone-like specific non-covalent interactions

Designing complex synthetic materials for enzyme immobilization could unlock the utility of biocatalysis in extreme environments. Inspired by biology, we investigate the use of random copolymer brushes as dynamic immobilization supports that enable supra-biological catalytic performance of immobilized enzymes. This is demonstrated by immobilizing Bacillus subtilis Lipase A on brushes doped with aromatic moieties, which can interact with the lipase through multiple non-covalent interactions. Incorporation of aromatic groups leads to a 50 °C increase in the optimal temperature of lipase, as well as a 50-fold enhancement in enzyme activity. Single-molecule FRET studies reveal that these supports act as biomimetic chaperones by promoting enzyme refolding and stabilizing the enzyme's folded and catalytically active state. This effect is diminished when aromatic residues are mutated out, suggesting the importance of π-stacking and π-cation interactions for stabilization. Our results underscore how unexplored enzyme-support interactions may enable uncharted opportunities for using enzymes in industrial biotransformations.

Understanding Design Rules for Optimizing the Interface between Immobilized Enzymes and Random Copolymer Brushes

A long-standing goal in the field of biotechnology is to develop and understand design rules for the stabilization of enzymes upon immobilization to materials. While immobilization has sometimes been successful as a strategy to stabilize enzymes, the design of synthetic materials that stabilize enzymes remains largely empirical. We sought to overcome this challenge by investigating the mechanistic basis for the stabilization of immobilized lipases on random copolymer brush surfaces comprised of poly(ethylene glycol) methacrylate (PEGMA) and sulfobetaine methacrylate (SBMA), which represent novel heterogeneous supports for immobilized enzymes. Using several related but structurally diverse lipases, including Bacillus subtilis lipase A (LipA), Rhizomucor miehei lipase, Candida rugosa lipase, and Candida antarctica lipase B (CALB), we showed that the stability of each lipase at elevated temperatures was strongly dependent on the fraction of PEGMA in the brush layer. This dependence was explained by developing and applying a new algorithm to quantify protein surface hydrophobicity, which involved using unsupervised cluster analysis to identify clusters of hydrophobic atoms. Characterization of the lipases showed that the optimal brush composition correlated with the free energy of solvation per enzyme surface area, which ranged from -17.1 kJ/mol·nm² for LipA to -11.8 kJ/mol·nm² for CALB. Additionally, using this algorithm, we found that hydrophobic patches consisting of aliphatic residues had a higher free energy than patches consisting of aromatic residues. By providing the basis for rationally tuning the interface between enzymes and materials, this understanding will transform the use of materials to reliably ruggedize enzymes under extreme conditions.