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.

Stress relaxation is an important design parameter of biomaterials that can provide an artificial microenvironment mimicking natural extracellular matrix (ECM). Here, we report a novel hydrogel platform based on sodium alginate (NaAlg) with tunable stress relaxation. We first developed a new synthesis route to introduce alkoxyamine functional groups into the alginate polymer backbone. By mixing the resulting polymer (NaAlg-AA) with aldehydecontaining oxidized alginate (NaAlg-Ald), oxime cross-linked alginate hydrogels were prepared. We demonstrate that highly tunable stress relaxation and mechanical properties can be achieved by systematically varying the composition (concentration, polymer mixing ratios, degree of oxidation of NaAlg-Ald) or environmental factors (pH, temperature, and use of catalyst). Combined with the natural capability of the alginate to be cross-linked by divalent cations, the developed hydrogel formations possess the unique capability of dual cross-linking mechanisms with different gelation kinetics. We demonstrated that this dual cross-linking capability can (i) be utilized for the creation of hydrogels in microbead or microthread geometries and (ii) be useful for biomedical applications that require both the fast encapsulation of cells in hydrogels (fast calcium cross-linking) and the provision of controlled viscoelastic environments to cultured cells for an extended period (durable oxime cross-linking). With biocompatibility confirmed by the culture of a B-cell line encapsulated within the developed hydrogel, this novel hydrogel platform provides a good prospect in various applications where stress relaxation plays a key role in cell−matrix interactions.

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 (ΔG solv,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.

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