Functional enzyme-polymer complexes

High-Efficiency Degradation of PET Plastics by Glutathione S-Transferase under Mild Conditions

Plastic pollution is a significant environmental concern globally. Plastics are normally considered chemically inert and resistant to biodegradation. Although many papers have reported enzyme-induced biodegradation of plastics, these studies are primarily limited to enzymes of microbial origin or engineered enzymes. This study reveals that poly(ethylene terephthalate) (PET, ∼6000 Da and 100 kDa) particles and plastic bottle debris (PBD, 24.9 kDa) can be efficiently degraded by a mammal-origin natural phase II metabolic isozyme, glutathione S-transferase (GST), under mild conditions. The degradation efficiency of PET plastics reached 98.9%, with a degradation rate of 2.6 g·L-1·h-1 under ambient or physiological conditions at 1 atm. PET plastics can be degraded by GST with varying environmental or biological factors (i.e., temperature, light irradiation, pH, and presence of humic acid or protein). We suggest a novel mechanism for PET degradation other than hydrolysis, i.e., the mechanism of cleavage and release of PET plastic monomers via nitridation and oxidation. This finding also reveals a novel function of GST, previously thought to only degrade small molecules (<1000 Da). This method has been successfully applied in real human serum samples. Additionally, we have tested and confirmed the ability to degrade PET of a mammal-origin natural digestive enzyme (trypsin) and a human-derived natural metabolic enzyme (CYP450). Overall, our findings provide a potential new route to plastic pollution control and contribute to our understanding of the metabolism and fate of plastics in organisms.

Integrating Enzymes with Supramolecular Polymers for Recyclable Photobiocatalytic Catalysis

Chemical modifications of enzymes excel in the realm of enzyme engineering due to its directness, robustness, and efficiency; however, challenges persist in devising versatile and effective strategies. In this study, we introduce a supramolecular modification methodology that amalgamates a supramolecular polymer with Candida antarctica lipase B (CalB) to create supramolecular enzymes (SupEnzyme). This approach features the straightforward preparation of a supramolecular amphiphilic polymer (β-CD@SMA), which was subsequently conjugated to the enzyme, resulting in a SupEnzyme capable of self-assembly into supramolecular nanoparticles. The resulting SupEnzyme nanoparticles can form micron-scale supramolecular aggregates through supramolecular and electrostatic interactions with guest entities, thus enhancing catalyst recycling. Remarkably, these aggregates maintain 80 % activity after seven cycles, outperforming Novozym 435. Additionally, they can effectively initiate photobiocatalytic cascade reactions using guest photocatalysts. As a consequence, our SupEnzyme methodology exhibits noteworthy adaptability in enzyme modification, presenting a versatile platform for various polymer, enzyme, and biocompatible catalyst pairings, with potential applications in the fields of chemistry and biology.

Selectivity of Complex Coacervation in Multi-Protein Mixtures

Liquid-liquid phase separation of biomolecules is increasingly recognized as relevant to various cellular functions, and complex coacervation of biomacromolecules, particularly proteins, is emerging as a key mechanism for this phenomenon. Complex coacervation is also being explored as a potential protein purification method due to its potential scalability, aqueous operation, and ability to produce a highly concentrated product. However, to date most studies of complex coacervation have evaluated the phase behavior of a binary mixture of two oppositely charged macromolecules. Therefore, a comprehensive understanding of the phase behavior of complex biological mixtures has yet to be established. To address this, a panel of engineered proteins was designed to allow for quantitative analysis of the complex coacervation of individual proteins within a multi-component mixture. The behavior of individual proteins was evaluated using a defined mixture of proteins that mimics the charge profile of the E. coli proteome. To allow for direct quantification of proteins in each phase, spectrally separated fluorescent proteins were used to construct the protein mixture. From this quantitative analysis, we observed that the coacervation behavior of individual proteins in the mixture was consistent with each other, which was distinctive from the behavior when each protein was evaluated in a single-protein system. Subtle differences in biophysical properties between the proteins became noticeable in the mixture, which allowed us to elucidate parameters for protein complex coacervation. With this understanding, we successfully designed methods to enrich a range of proteins of interest from a mixture of proteins.

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.

Data-Driven Design of Polymer-Based Biomaterials: High-throughput Simulation, Experimentation, and Machine Learning

Polymers, with the capacity to tunably alter properties and response based on manipulation of their chemical characteristics, are attractive components in biomaterials. Nevertheless, their potential as functional materials is also inhibited by their complexity, which complicates rational or brute-force design and realization. In recent years, machine learning has emerged as a useful tool for facilitating materials design via efficient modeling of structure-property relationships in the chemical domain of interest. In this Spotlight, we discuss the emergence of data-driven design of polymers that can be deployed in biomaterials with particular emphasis on complex copolymer systems. We outline recent developments, as well as our own contributions and takeaways, related to high-throughput data generation for polymer systems, methods for surrogate modeling by machine learning, and paradigms for property optimization and design. Throughout this discussion, we highlight key aspects of successful strategies and other considerations that will be relevant to the future design of polymer-based biomaterials with target properties.

Tailoring Interactions of Random Copolymer Polyelectrolyte Complexes to Remove Nanoplastic Contaminants from Water

We investigate the usage of polyelectrolyte complex materials for water remediation purposes, specifically their ability to remove nanoplastics from water, on which there is currently little to no prior research. We demonstrate that oppositely charged random copolymers are effective at quantitatively removing nanoplastic contamination from aqueous solution. The mechanisms underlying this remediation ability are explored through computational simulations, with corroborating quartz crystal microbalance adsorption experiments. We find that hydrophobic nanostructures and interactions likely play an important role.

Enzyme-Polymer Conjugates for Tuning, Enhancing, and Expanding Biocatalytic Activity

Combining polymers with functional proteins is an approach that has brought several successful stories in the field of biomedicine with PEGylated therapeutic proteins. The latest advances in polymer chemistry have facilitated the expansion of protein-polymer hybrids to other research areas such as biocatalysis. Polymers can impart stability and novel functionalities to the enzyme of interest, thereby improving the catalytic performance of a given reaction. In this review, we have revisited the main methodologies currently used for the synthesis of enzyme-polymer hybrids, unveiling the interplay between the configuration and the composition of the assembled structure and the eventual traits of the hybrid. Finally, the latest advances, such as the assembly of polymer-based chemoenzymatic nanoreactors and the use of deep learning methodologies to achieve the most suitable polymer compositions for catalysis, are discussed.

Rheology and Gelation of Hyaluronic Acid/Chitosan Coacervates

Hyaluronic acid (HA) and chitosan (CHI) are biopolyelectrolytes which are interesting for both the medical and polymer physics communities due to their biocompatibility and semi-flexibility, respectively. In this work, we demonstrate by rheology experiments that the linear viscoelasticity of HA/CHI coacervates depends strongly on the molecular weight of the polymers. Moduli for coacervates were found significantly higher than those of individual HA and CHI physical gels. A remarkable 1.5-fold increase in moduli was noted when catechol-conjugated HA and CHI were used instead. This was attributed to the conversion of coacervates to chemical gels by oxidation of 3,4-dihydroxyphenylalanine (DOPA) groups in HA and CHI to di-DOPA crosslinks. These rheological results put HA/CHI coacervates in the category of strong candidates as injectable tissue scaffolds or medical adhesives.