The Quest for Xenobiotic Enzymes: From New Enzymes for Chemistry to a Novel Chemistry of Life

Genetic Functionalization of Protein-Based Biomaterials via Protein Fusions

Proteins implement many useful functions, including binding ligands with unparalleled affinity and specificity, catalyzing stereospecific chemical reactions, and directing cell behavior. Incorporating proteins into materials has the potential to imbue devices with these desirable traits. This review highlights recent advances in creating active materials by genetically fusing a self-assembling protein to a functional protein. These fusion proteins form materials while retaining the function of interest. Key advantages of this approach include elimination of a separate functionalization step during materials synthesis, uniform and dense coverage of the material by the functional protein, and stabilization of the functional protein. This review focuses on macroscale materials and discusses (i) multiple strategies for successful protein fusion design, (ii) successes and limitations of the protein fusion approach, (iii) engineering solutions to bypass any limitations, (iv) applications of protein fusion materials, including tissue engineering, drug delivery, enzyme immobilization, electronics, and biosensing, and (v) opportunities to further develop this useful technique.

Enhanced Sequence-Activity Mapping and Evolution of Artificial Metalloenzymes by Active Learning

Tailored enzymes are crucial for the transition to a sustainable bioeconomy. However, enzyme engineering is laborious and failure-prone due to its reliance on serendipity. The efficiency and success rates of engineering campaigns may be improved by applying machine learning to map the sequence-activity landscape based on small experimental data sets. Yet, it often proves challenging to reliably model large sequence spaces while keeping the experimental effort tractable. To address this challenge, we present an integrated pipeline combining large-scale screening with active machine learning, which we applied to engineer an artificial metalloenzyme (ArM) catalyzing a new-to-nature hydroamination reaction. Combining lab automation and next-generation sequencing, we acquired sequence-activity data for several thousand ArM variants. We then used Gaussian process regression to model the activity landscape and guide further screening rounds. Critical characteristics of our pipeline include the cost-effective generation of information-rich data sets, the integration of an explorative round to improve the model's performance, and the inclusion of experimental noise. Our approach led to an order-of-magnitude boost in the hit rate while making efficient use of experimental resources. Search strategies like this should find broad utility in enzyme engineering and accelerate the development of novel biocatalysts.

Rational design of a bacterial import system for new-to-nature molecules

Integration of novel compounds into biological processes holds significant potential for modifying or expanding existing cellular functions. However, the cellular uptake of these compounds is often hindered by selectively permeable membranes. We present a novel bacterial transport system that has been rationally designed to address this challenge. Our approach utilizes a highly promiscuous sulfonate membrane transporter, which allows the passage of cargo molecules attached as amides to a sulfobutanoate transport vector molecule into the cytoplasm of the cell. These cargoes can then be unloaded from the sulfobutanoyl amides using an engineered variant of the enzyme γ-glutamyl transferase, which hydrolyzes the amide bond and releases the cargo molecule within the cell. Here, we provide evidence for the broad substrate specificity of both components of the system by evaluating a panel of structurally diverse sulfobutanoyl amides. Furthermore, we successfully implement the synthetic uptake system in vivo and showcase its functionality by importing an impermeant non-canonical amino acid.

Design of Artificial Enzymes: Insights into Protein Scaffolds

The design of artificial enzymes has emerged as a promising tool for the generation of potent biocatalysts able to promote new-to-nature reactions with improved catalytic performances, providing a powerful platform for wide-ranging applications and a better understanding of protein functions and structures. The selection of an appropriate protein scaffold plays a key role in the design process. This review aims to give a general overview of the most common protein scaffolds that can be exploited for the generation of artificial enzymes. Several examples are discussed and categorized according to the strategy used for the design of the artificial biocatalyst, namely the functionalization of natural enzymes, the creation of a new catalytic site in a protein scaffold bearing a wide hydrophobic pocket and de novo protein design. The review is concluded by a comparison of these different methods and by our perspective on the topic.

A protein scaffold enables hydrogen evolution for a Ni-bisdiphosphine complex

An artificial metalloenzyme acting as a functional biomimic of hydrogenase enzymes was activated by assembly via covalent attachment of the molecular complex, [Ni(PN^glycineP)₂]^2-, within a structured protein scaffold. Electrocatalytic H₂ production was observed from pH 3.0 to 10.0 for the artificial enzyme, while no electrocatalytic activity was observed for similar [Ni(PNP)₂]²⁺ systems.

Artificial metalloenzymes in a nutshell: the quartet for efficient catalysis

Artificial metalloenzymes combine the inherent reactivity of transition metal catalysis with the sophisticated reaction control of natural enzymes. By providing new opportunities in bioorthogonal chemistry and biocatalysis, artificial metalloenzymes have the potential to overcome certain limitations in both drug discovery and green chemistry or related research fields. Ongoing advances in organometallic catalysis, directed evolution, and bioinformatics are enabling the design of increasingly powerful systems that outperform conventional catalysis in a growing number of cases. Therefore, this review article collects challenges and opportunities in designing artificial metalloenzymes described in recent review articles. This will provide an equitable insight for those new to and interested in the field.

Recent trends in biocatalysis

Biocatalysis has undergone revolutionary progress in the past century. Benefited by the integration of multidisciplinary technologies, natural enzymatic reactions are constantly being explored. Protein engineering gives birth to robust biocatalysts that are widely used in industrial production. These research achievements have gradually constructed a network containing natural enzymatic synthesis pathways and artificially designed enzymatic cascades. Nowadays, the development of artificial intelligence, automation, and ultra-high-throughput technology provides infinite possibilities for the discovery of novel enzymes, enzymatic mechanisms and enzymatic cascades, and gradually complements the lack of remaining key steps in the pathway design of enzymatic total synthesis. Therefore, the research of biocatalysis is gradually moving towards the era of novel technology integration, intelligent manufacturing and enzymatic total synthesis.

Artificial Organelles: Towards Adding or Restoring Intracellular Activity

Compartmentalization is one of the main characteristics that define living systems. Creating a physically separated microenvironment allows nature a better control over biological processes, as is clearly specified by the role of organelles in living cells. Inspired by this phenomenon, researchers have developed a range of different approaches to create artificial organelles: compartments with catalytic activity that add new function to living cells. In this review we will discuss three complementary lines of investigation. First, orthogonal chemistry approaches are discussed, which are based on the incorporation of catalytically active transition metal-containing nanoparticles in living cells. The second approach involves the use of premade hybrid nanoreactors, which show transient function when taken up by living cells. The third approach utilizes mostly genetic engineering methods to create bio-based structures that can be ultimately integrated with the cell's genome to make them constitutively active. The current state of the art and the scope and limitations of the field will be highlighted with selected examples from the three approaches.

Recent Advances in Biocatalysis with Chemical Modification and Expanded Amino Acid Alphabet

The two main strategies for enzyme engineering, directed evolution and rational design, have found widespread applications in improving the intrinsic activities of proteins. Although numerous advances have been achieved using these ground-breaking methods, the limited chemical diversity of the biopolymers, restricted to the 20 canonical amino acids, hampers creation of novel enzymes that Nature has never made thus far. To address this, much research has been devoted to expanding the protein sequence space via chemical modifications and/or incorporation of noncanonical amino acids (ncAAs). This review provides a balanced discussion and critical evaluation of the applications, recent advances, and technical breakthroughs in biocatalysis for three approaches: (i) chemical modification of cAAs, (ii) incorporation of ncAAs, and (iii) chemical modification of incorporated ncAAs. Furthermore, the applications of these approaches and the result on the functional properties and mechanistic study of the enzymes are extensively reviewed. We also discuss the design of artificial enzymes and directed evolution strategies for enzymes with ncAAs incorporated. Finally, we discuss the current challenges and future perspectives for biocatalysis using the expanded amino acid alphabet.

Systematic engineering of artificial metalloenzymes for new-to-nature reactions

Artificial metalloenzymes (ArMs) catalyzing new-to-nature reactions could play an important role in transitioning toward a sustainable economy. While ArMs have been created for various transformations, attempts at their genetic optimization have been case specific and resulted mostly in modest improvements. To realize their full potential, methods to rapidly discover active ArM variants for ideally any reaction of interest are required. Here, we introduce a reaction-independent, automation-compatible platform, which relies on periplasmic compartmentalization in Escherichia coli to rapidly and reliably engineer ArMs based on the biotin-streptavidin technology. We systematically assess 400 ArM mutants for five bioorthogonal transformations involving different metals, reaction mechanisms, and reactants, which include novel ArMs for gold-catalyzed hydroamination and hydroarylation. Activity enhancements up to 15-fold highlight the potential of the systematic approach. Furthermore, we suggest smart screening strategies and build machine learning models that accurately predict ArM activity from sequence, which has crucial implications for future ArM development.

Artificial Metalloenzymes: From Selective Chemical Transformations to Biochemical Applications

Artificial metalloenzymes (ArMs) comprise a synthetic metal complex in a protein scaffold. ArMs display performances combining those of both homogeneous catalysts and biocatalysts. Specifically, ArMs selectively catalyze non-natural reactions and reactions inspired by nature in water under mild conditions. In the past few years, the construction of ArMs that possess a genetically incorporated unnatural amino acid and the directed evolution of ArMs have become of great interest in the field. Additionally, biochemical applications of ArMs have steadily increased, owing to the fact that compartmentalization within a protein scaffold allows the synthetic metal complex to remain functional in a sea of inactivating biomolecules. In this review, we present updates on: 1) the newly reported ArMs, according to their type of reaction, and 2) the unique biochemical applications of ArMs, including chemoenzymatic cascades and intracellular/in vivo catalysis. We believe that ArMs have great potential as catalysts for organic synthesis and as chemical biology tools for pharmaceutical applications.