Towards controlling activity of a peptide asparaginyl ligase (PAL) by lumazine synthetase compartmentalization

Peptide asparaginyl ligases (PALs) hold significant potential in protein bioconjugation due to their excellent kinetic properties and broad substrate compatibility. However, realizing their full potential in biocatalytic applications requires precise control of their activity. Inspired by nature, we aimed to compartmentalize a representative PAL, OaAEP1-C247A, within protein containers to create artificial organelles with substrate sorting capability. Two encapsulation approaches were explored using engineered lumazine synthases (AaLS). The initial strategy involved tagging the PAL with a super-positively charged GFP(+36) for encapsulation into the super-negatively charged AaLS-13 variant, but it resulted in undesired truncation of the enzyme. The second approach involved genetic fusion of the OaAEP1-C247A with a circularly permutated AaLS variant (cpAaLS) and its co-production with AaLS-13, which successfully enabled compartmentalization of the PAL within a patch-work protein cage. Although the caged PAL retained its activity, it was significantly reduced compared to the free enzyme (∼30-40-fold), likely caused by issues related to OaAEP1-C247A stability and folding. Nevertheless, these findings demonstrated the feasibility of the AaLS encapsulation approach and encourage further optimization in the design of peptide-ligating artificial organelles in E. coli, aiming for a more effective and stable system for protein modifications.

Protein engineering using circular permutation - structure, function, stability, and applications

Protein engineering is important for creating novel variants from natural proteins, enabling a wide range of applications. Approaches such as rational design and directed evolution are routinely used to make new protein variants. Computational tools like de novo design can introduce new protein folds. Expanding the amino acid repertoire to include unnatural amino acids with non-canonical side chains in vitro by native chemical ligation and in vivo via codon expansion methods broadens sequence and structural possibilities. Circular permutation (CP) is an invaluable approach to redesigning a protein by rearranging the amino acid sequence, where the connectivity of the secondary structural elements is altered without changing the overall structure of the protein. Artificial CP proteins (CPs) are employed in various applications such as biocatalysis, sensing of small molecules by fluorescence, genome editing, ligand-binding protein switches, and optogenetic engineering. Many studies have shown that CP can lead to either reduced or enhanced stability or catalytic efficiency. The effects of CP on a protein's energy landscape cannot be predicted a priori. Thus, it is important to understand how CP can affect the thermodynamic and kinetic stability of a protein. In this review, we discuss the discovery and advancement of techniques to create protein CP, and existing reviews on CP. We delve into the plethora of biological applications for designed CP proteins. We subsequently discuss the experimental and computational reports on the effects of CP on the thermodynamic and kinetic stabilities of proteins of various topologies. An understanding of the various aspects of CP will allow the reader to design robust CP proteins for their specific purposes.

A Robust Growth-Based Selection Platform to Evolve an Enzyme via Dependency on Noncanonical Tyrosine Analogues

Growth-based selections evaluate the fitness of individual organisms at a population level. In enzyme engineering, such growth selections allow for the rapid and straightforward identification of highly efficient biocatalysts from extensive libraries. However, selection-based improvement of (synthetically useful) biocatalysts is challenging, as they require highly dependable strategies that artificially link their activities to host survival. Here, we showcase a robust and scalable growth-based selection platform centered around the complementation of noncanonical amino acid-dependent bacteria. Specifically, we demonstrate how serial passaging of populations featuring millions of carbamoylase variants autonomously selects biocatalysts with up to 90,000-fold higher initial rates. Notably, selection of replicate populations enriched diverse biocatalysts, which feature distinct amino acid motifs that drastically boost carbamoylase activity. As beneficial substitutions also originated from unintended copying errors during library preparation or cell division, we anticipate that our growth-based selection platform will be applicable to the continuous, autonomous evolution of diverse biocatalysts in the future.

Strategies for designing biocatalysts with new functions

The engineering of natural enzymes has led to the availability of a broad range of biocatalysts that can be used for the sustainable manufacturing of a variety of chemicals and pharmaceuticals. However, for many important chemical transformations there are no known enzymes that can serve as starting templates for biocatalyst development. These limitations have fuelled efforts to build entirely new catalytic sites into proteins in order to generate enzymes with functions beyond those found in Nature. This bottom-up approach to enzyme development can also reveal new fundamental insights into the molecular origins of efficient protein catalysis. In this tutorial review, we will survey the different strategies that have been explored for designing new protein catalysts. These methods will be illustrated through key selected examples, which demonstrate how highly proficient and selective biocatalysts can be developed through experimental protein engineering and/or computational design. Given the rapid pace of development in the field, we are optimistic that designer enzymes will begin to play an increasingly prominent role as industrial biocatalysts in the coming years.

Controlling Monoterpene Isomerization by Guiding Challenging Carbocation Rearrangement Reactions in Engineered Squalene-Hopene Cyclases

The interconversion of monoterpenes is facilitated by a complex network of carbocation rearrangement pathways. Controlling these isomerization pathways is challenging when using common Brønsted and Lewis acid catalysts, which often produce product mixtures that are difficult to separate. In contrast, natural monoterpene cyclases exhibit high control over the carbocation rearrangement reactions but are reliant on phosphorylated substrates. In this study, we present engineered squalene-hopene cyclases from Alicyclobacillus acidocaldarius (AacSHC) that catalyze the challenging isomerization of monoterpenes with unprecedented precision. Starting from a promiscuous isomerization of (+)-β-pinene, we first demonstrate noticeable shifts in the product distribution solely by introducing single point mutations. Furthermore, we showcase the tuneable cation steering by enhancing (+)-borneol selectivity from 1 % to >90 % (>99 % de) aided by iterative saturation mutagenesis. Our combined experimental and computational data suggest that the reorganization of key aromatic residues leads to the restructuring of the water network that facilitates the selective termination of the secondary isobornyl cation. This work expands our mechanistic understanding of carbocation rearrangements and sets the stage for target-oriented skeletal reorganization of broadly abundant terpenes.

Spatial Heterogeneity and Strong Coupling of FeII /FeIII in an Individual Metal-Organic Framework Nanoparticle for Efficient CO2 Photoreduction

The synthesis and characterization of an FeII /FeIII metal-organic framework (MOF) nanocrystal with spatial heterogeneity that arises from the non-uniform distribution of different valence states is disclosed. The FeII /FeIII -Ni Prussian blue analog (PBA) delivers superior photocatalytic performance in the selective CO2 reduction reaction thanks to the strong FeII /FeIII coupling, with CO yield up to 12.27 mmol g-1 h-1 and 90.6% selectivity under visible-light irradiation. Density functional theory calculation and experimental studies prove that the spatial heterogeneity of FeII /FeIII in the individual MOF nanocrystal not only directs and expedites the charge transfer within a catalyst particle but also creates the heterogeneity of catalytically-active Ni sites for efficient CO2 photoreduction. The current findings add to a growing literature of materials with compositional heterogeneity and provide a reference for future research.

Advances in alginate lyases and the potential application of enzymatic prepared alginate oligosaccharides: A mini review

Alginate is mainly a linear polysaccharide composed of randomly arranged β-D-mannuronic acid and α-L-guluronic acid linked by α, β-(1,4)-glycosidic bonds. Alginate lyases degrade alginate mainly adopting a β-elimination mechanism, breaking the glycosidic bonds between the monomers and forming a double bond between the C4 and C5 sugar rings to produce alginate oligosaccharides consisting of 2-25 monomers, which have various physiological functions. Thus, it can be used for the continuous industrial production of alginate oligosaccharides with a specific degree of polymerization, in accordance with the requirements of green exploitation of marine resources. With the development of structural analysis, the quantity of characterized alginate lyase structures is progressively growing, leading to a concomitant improvement in understanding the catalytic mechanism. Additionally, the use of molecular modification methods including rational design, truncated expression of non-catalytic domains, and recombination of conserved domains can improve the catalytic properties of the original enzyme, enabling researchers to screen out the enzyme with the expected excellent performance with high success rate and less workload. This review presents the latest findings on the catalytic mechanism of alginate lyases and outlines the methods for molecular modifications. Moreover, it explores the connection between the degree of polymerization and the physiological functions of alginate oligosaccharides, providing a reference for enzymatic preparation development and utilization.

Understanding activity-stability tradeoffs in biocatalysts by enzyme proximity sequencing

Understanding the complex relationships between enzyme sequence, folding stability and catalytic activity is crucial for applications in industry and biomedicine. However, current enzyme assay technologies are limited by an inability to simultaneously resolve both stability and activity phenotypes and to couple these to gene sequences at large scale. Here we present the development of enzyme proximity sequencing, a deep mutational scanning method that leverages peroxidase-mediated radical labeling with single cell fidelity to dissect the effects of thousands of mutations on stability and catalytic activity of oxidoreductase enzymes in a single experiment. We use enzyme proximity sequencing to analyze how 6399 missense mutations influence folding stability and catalytic activity in a D-amino acid oxidase from Rhodotorula gracilis. The resulting datasets demonstrate activity-based constraints that limit folding stability during natural evolution, and identify hotspots distant from the active site as candidates for mutations that improve catalytic activity without sacrificing stability. Enzyme proximity sequencing can be extended to other enzyme classes and provides valuable insights into biophysical principles governing enzyme structure and function.

In Vitro Enzyme Self-Selection Using Molecular Programs

Directed evolution provides a powerful route for in vitro enzyme engineering. State-of-the-art techniques functionally screen up to millions of enzyme variants using high throughput microfluidic sorters, whose operation remains technically challenging. Alternatively, in vitro self-selection methods, analogous to in vivo complementation strategies, open the way to even higher throughputs, but have been demonstrated only for a few specific activities. Here, we leverage synthetic molecular networks to generalize in vitro compartmentalized self-selection processes. We introduce a programmable circuit architecture that can link an arbitrary target enzymatic activity to the replication of its encoding gene. Microencapsulation of a bacterial expression library with this autonomous selection circuit results in the single-step and screening-free enrichment of genetic sequences coding for programmed enzymatic phenotypes. We demonstrate the potential of this approach for the nicking enzyme Nt.BstNBI (NBI). We applied autonomous selection conditions to enrich for thermostability or catalytic efficiency, manipulating up to 107 microcompartments and 5 × 105 variants at once. Full gene reads of the libraries using nanopore sequencing revealed detailed mutational activity landscapes, suggesting a key role of electrostatic interactions with DNA in the enzyme's turnover. The most beneficial mutations, identified after a single round of self-selection, provided variants with, respectively, 20 times and 3 °C increased activity and thermostability. Based on a modular molecular programming architecture, this approach does not require complex instrumentation and can be repurposed for other enzymes, including those that are not related to DNA chemistry.

Reagent Engineering for Group Transfer Biocatalysis

Biocatalysis has become a major driver in the innovation of preparative chemistry. Enzyme discovery, engineering and computational design have matured to reliable strategies in the development of biocatalytic processes. By comparison, substrate engineering has received much less attention. In this Minireview, we highlight the idea that the design of synthetic reagents may be an equally fruitful and complementary approach to develop novel enzyme-catalysed group transfer chemistry. This Minireview discusses key examples from the literature that illustrate how synthetic substrates can be devised to improve the efficiency, scalability and sustainability, as well as the scope of such reactions. We also provide an opinion as to how this concept might be further developed in the future, aspiring to replicate the evolutionary success story of natural group transfer reagents, such as adenosine triphosphate (ATP) and S-adenosyl methionine (SAM).

Iron Heme Enzyme-Catalyzed Cyclopropanations with Diazirines as Carbene Precursors: Computational Explorations of Diazirine Activation and Cyclopropanation Mechanism

The mechanism of cyclopropanations with diazirines as air-stable and user-friendly alternatives to commonly employed diazo compounds within iron heme enzyme-catalyzed carbene transfer reactions has been studied by means of density functional theory (DFT) calculations of model systems, quantum mechanics/molecular mechanics (QM/MM) calculations, and molecular dynamics (MD) simulations of the iron carbene and the cyclopropanation transition state in the enzyme active site. The reaction is initiated by a direct diazirine-diazo isomerization occurring in the active site of the enzyme. In contrast, an isomerization mechanism proceeding via the formation of a free carbene intermediate in lieu of a direct, one-step isomerization process was observed for model systems. Subsequent reaction with benzyl acrylate takes place through stepwise C-C bond formation via a diradical intermediate, delivering the cyclopropane product. The origin of the observed diastereo- and enantioselectivity in the enzyme was investigated through MD simulations, which indicate a preferred formation of the cis-cyclopropane by steric control.

Biotechnological innovations in nanocellulose production from waste biomass with a focus on pineapple waste

New materials' synthesis and utilization have shown many critical challenges in healthcare and other industrial sectors as most of these materials are directly or indirectly developed from fossil fuel resources. Environmental regulations and sustainability concepts have promoted the use of natural compounds with unique structures and properties that can be biodegradable, biocompatible, and eco-friendly. In this context, nanocellulose (NC) utility in different sectors and industries is reported due to their unique properties including biocompatibility and antimicrobial characteristics. The bacterial nanocellulose (BNC)-based materials have been synthesized by bacterial cells and extracted from plant waste materials including pineapple plant waste biomass. These materials have been utilized in the form of nanofibers and nanocrystals. These materials are found to have excellent surface properties, low density, and good transparency, and are rich in hydroxyl groups for their modifications to other useful products. These materials are well utilized in different sectors including biomedical or health care centres, nanocomposite materials, supercapacitors, and polymer matrix production. This review explores different approaches for NC production from pineapple waste residues using biotechnological interventions, approaches for their modification, and wider applications in different sectors. Recent technological developments in NC production by enzymatic treatment are critically discussed. The utilization of pineapple waste-derived NC from a bioeconomic perspective is summarized in the paper. The chemical composition and properties of nanocellulose extracted from pineapple waste may have unique characteristics compared to other sources. Pineapple waste for nanocellulose production aligns with the principles of sustainability, waste reduction, and innovation, making it a promising and novel approach in the field of nanocellulose materials.

Improving plastic degrading enzymes via directed evolution

Plastic degrading enzymes have immense potential for use in industrial applications. Protein engineering efforts over the last decade have resulted in considerable enhancement of many properties of these enzymes. Directed evolution, a protein engineering approach that mimics the natural process of evolution in a laboratory, has been particularly useful in overcoming some of the challenges of structure-based protein engineering. For example, directed evolution has been used to improve the catalytic activity and thermostability of polyethylene terephthalate (PET)-degrading enzymes, although its use for the improvement of other desirable properties, such as solvent tolerance, has been less studied. In this review, we aim to identify some of the knowledge gaps and current challenges, and highlight recent studies related to the directed evolution of plastic-degrading enzymes.

Exploration of the In Vitro Violacein Synthetic Pathway with Substrate Analogues

Evolution has gifted enzymes with the ability to synthesize an abundance of small molecules with incredible control over efficiency and selectivity. Central to an enzyme's role is the ability to selectively catalyze reactions in the milieu of chemicals within a cell. However, for chemists it is often desirable to extend the substrate scope of reactions to produce analogue(s) of a desired product and therefore some degree of enzyme promiscuity is often desired. Herein, we examine this dichotomy in the context of the violacein biosynthetic pathway. Importantly, we chose to interrogate this pathway with tryptophan analogues in vitro, to mitigate possible interference from cellular components and endogenous tryptophan. A total of nine tryptophan analogues were screened for by analyzing the substrate promiscuity of the initial enzyme, VioA, and compared to the substrate tryptophan. These results suggested that for VioA, substitutions at either the 2- or 4-position of tryptophan were not viable. The seven analogues that showed successful substrate conversion by VioA were then applied to the five enzyme cascade (VioABEDC) for the production of violacein, where l-tryptophan and 6-fluoro-l-tryptophan were the only substrates which were successfully converted to the corresponding violacein derivative(s). However, many of the other tryptophan analogues did convert to various substituted intermediaries. Overall, our results show substrate promiscuity with the initial enzyme, VioA, but much less for the full pathway. This work demonstrates the complexity involved when attempting to analyze substrate analogues within multienzymatic cascades, where each enzyme involved within the cascade possesses its own inherent promiscuity, which must be compatible with the remaining enzymes in the cascade for successful formation of a desired product.

Novel Biocatalysts from Specialized Metabolism

Enzymes are increasingly recognized as valuable (bio)catalysts that complement existing synthetic methods. However, the range of biotransformations used in the laboratory is limited. Here we give an overview on the biosynthesis-inspired discovery of novel biocatalysts that address various synthetic challenges. Prominent examples from this dynamic field highlight remarkable enzymes for protecting-group-free amide formation and modification, control of pericyclic reactions, stereoselective hetero- and polycyclizations, atroposelective aryl couplings, site-selective C-H activations, introduction of ring strain, and N-N bond formation. We also explore unusual functions of cytochrome P450 monooxygenases, radical SAM-dependent enzymes, flavoproteins, and enzymes recruited from primary metabolism, which offer opportunities for synthetic biology, enzyme engineering, directed evolution, and catalyst design.

Light-driven eco-evolutionary dynamics in a synthetic replicator system

Darwinian evolution involves the inheritance and selection of variations in reproducing entities. Selection can be based on, among others, interactions with the environment. Conversely, the replicating entities can also affect their environment generating a reciprocal feedback on evolutionary dynamics. The onset of such eco-evolutionary dynamics marks a stepping stone in the transition from chemistry to biology. Yet the bottom-up creation of a molecular system that exhibits eco-evolutionary dynamics has remained elusive. Here we describe the onset of such dynamics in a minimal system containing two synthetic self-replicators. The replicators are capable of binding and activating a co-factor, enabling them to change the oxidation state of their environment through photoredox catalysis. The replicator distribution adapts to this change and, depending on light intensity, one or the other replicator becomes dominant. This study shows how behaviour analogous to eco-evolutionary dynamics-which until now has been restricted to biology-can be created using an artificial minimal replicator system.

Massive integration of large gene libraries in the chromosome of Escherichia coli

Large gene libraries are frequently created in Escherichia coli plasmids, which can induce cell toxicity and expression instability due to the high gene dosage. To address these limitations, gene libraries can be integrated in a single copy into the bacterial chromosome. Here, we describe an efficient system for the massive integration (MAIN) of large gene libraries in the E. coli chromosome that generates in-frame gene fusions that are expressed stably. MAIN uses a thermosensitive integrative plasmid that is linearized in vivo to promote extensive integration of the gene library via homologous recombination. Positive and negative selections efficiently remove bacteria lacking gene integration in the target site. We tested MAIN with a library of 107 VHH genes that encode nanobodies (Nbs). The integration of VHH genes into a custom target locus of the E. coli chromosome enabled stable expression and surface display of the Nbs. Next-generation DNA sequencing confirmed that MAIN preserved the diversity of the gene library after integration. Finally, we screened the integrated library to select Nbs that bind a specific antigen using magnetic and fluorescence-activated cell sorting. This allowed us to identify Nbs binding the epidermal growth factor receptor that were not previously isolated in a similar screening of a multicopy plasmid library. Our results demonstrate that MAIN enables large gene library integration into the E. coli chromosome, creating stably expressed in-frame fusions for functional screening.

Engineering status of protein for improving microbial cell factories

With the development of metabolic engineering and synthetic biology, microbial cell factories (MCFs) have provided an efficient and sustainable method to synthesize a series of chemicals from renewable feedstocks. However, the efficiency of MCFs is usually limited by the inappropriate status of protein. Thus, engineering status of protein is essential to achieve efficient bioproduction with high titer, yield and productivity. In this review, we summarize the engineering strategies for metabolic protein status, including protein engineering for boosting microbial catalytic efficiency, protein modification for regulating microbial metabolic capacity, and protein assembly for enhancing microbial synthetic capacity. Finally, we highlight future challenges and prospects of improving microbial cell factories by engineering status of protein.

Engineering Enzymes for Environmental Sustainability

The development and implementation of sustainable catalytic technologies is key to delivering our net-zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, polyethylene terephthalate (PET). Finally, biocatalytic approaches for accessing petroleum-based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of cleaner and more efficient chemical industry.

Engineering Enzymes for Environmental Sustainability

The development and implementation of sustainable catalytic technologies is key to delivering our net-zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2 ) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, polyethylene terephthalate (PET). Finally, biocatalytic approaches for accessing petroleum-based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of cleaner and more efficient chemical industry.

High-Throughput Engineering of Nonribosomal Extension Modules

Nonribosomal peptides constitute an important class of natural products that display a wide range of bioactivities. They are biosynthesized by large assembly lines called nonribosomal peptide synthetases (NRPSs). Engineering NRPS modules represents an attractive strategy for generating customized synthetases for the production of peptide variants with improved properties. Here, we explored the yeast display of NRPS elongation and termination modules as a high-throughput screening platform for assaying adenylation domain activity and altering substrate specificity. Depending on the module, display of A-T bidomains or C-A-T tridomains, which also include an upstream condensation domain, proved to be most effective. Reprograming a tyrocidine synthetase elongation module to accept 4-propargyloxy-phenylalanine, a noncanonical amino acid that is not activated by the native protein, illustrates the utility of this approach for altering NRPS specificity at internal sites.

Mutexa: A Computational Ecosystem for Intelligent Protein Engineering

Protein engineering holds immense promise in shaping the future of biomedicine and biotechnology. This Review focuses on our ongoing development of Mutexa, a computational ecosystem designed to enable "intelligent protein engineering". In this vision, researchers will seamlessly acquire sequences of protein variants with desired functions as biocatalysts, therapeutic peptides, and diagnostic proteins through a finely-tuned computational machine, akin to Amazon Alexa's role as a versatile virtual assistant. The technical foundation of Mutexa has been established through the development of a database that combines and relates enzyme structures and their respective functions (e.g., IntEnzyDB), workflow software packages that enable high-throughput protein modeling (e.g., EnzyHTP and LassoHTP), and scoring functions that map the sequence-structure-function relationship of proteins (e.g., EnzyKR and DeepLasso). We will showcase the applications of these tools in benchmarking the convergence conditions of enzyme functional descriptors across mutants, investigating protein electrostatics and cavity distributions in SAM-dependent methyltransferases, and understanding the role of nonelectrostatic dynamic effects in enzyme catalysis. Finally, we will conclude by addressing the future steps and fundamental challenges in our endeavor to develop new Mutexa applications that assist the identification of beneficial mutants in protein engineering.

Engineering of Therapeutic and Detoxifying Enzymes

Therapeutic enzymes present excellent opportunities for the treatment of human disease, modulation of metabolic pathways and system detoxification. However, current use of enzyme therapy in the clinic is limited as naturally occurring enzymes are seldom optimal for such applications and require substantial improvement by protein engineering. Engineering strategies such as design and directed evolution that have been successfully implemented for industrial biocatalysis can significantly advance the field of therapeutic enzymes, leading to biocatalysts with new-to-nature therapeutic activities, high selectivity, and suitability for medical applications. This minireview highlights case studies of how state-of-the-art and emerging methods in protein engineering are explored for the generation of therapeutic enzymes and discusses gaps and future opportunities in the field of enzyme therapy.

Workflow for High-throughput Screening of Enzyme Mutant Libraries Using Matrix-assisted Laser Desorption/Ionization Mass Spectrometry Analysis of Escherichia coli Colonies

High-throughput molecular screening of microbial colonies and DNA libraries are critical procedures that enable applications such as directed evolution, functional genomics, microbial identification, and creation of engineered microbial strains to produce high-value molecules. A promising chemical screening approach is the measurement of products directly from microbial colonies via optically guided matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Measuring the compounds from microbial colonies bypasses liquid culture with a screen that takes approximately 5 s per sample. We describe a protocol combining a dedicated informatics pipeline and sample preparation method that can prepare up to 3,000 colonies in under 3 h. The screening protocol starts from colonies grown on Petri dishes and then transferred onto MALDI plates via imprinting. The target plate with the colonies is imaged by a flatbed scanner and the colonies are located via custom software. The target plate is coated with MALDI matrix, MALDI-MS analyzes the colony locations, and data analysis enables the determination of colonies with the desired biochemical properties. This workflow screens thousands of colonies per day without requiring additional automation. The wide chemical coverage and the high sensitivity of MALDI-MS enable diverse screening projects such as modifying enzymes and functional genomics surveys of gene activation/inhibition libraries. Key features • Mass spectrometry analyzes a range of compounds from E. coli colonies as a proxy for liquid culture testing enzyme mutant libraries. • Colonies are transferred to a MALDI target plate by a simple imprinting method. • The screen compares the ratio among several products or searches for the qualitative presence of specific compounds. • The protocol requires a MALDI mass spectrometer.

Growth-coupled high throughput selection for directed enzyme evolution

Directed enzyme evolution has revolutionized the rapid development of enzymes with desired properties. However, the lack of a high-throughput method to identify the most suitable variants from a large pool of genetic diversity poses a major bottleneck. To overcome this challenge, growth-coupled in vivo high-throughput selection approaches (GCHTS) have emerged as a novel selection system for enzyme evolution. GCHTS links the survival of the host cell with the properties of the target protein, resulting in a screening system that is easily measurable and has a high throughput-scale limited only by transformation efficiency. This allows for the rapid identification of desired variants from a pool of >109 variants in each experiment. In recent years, GCHTS approaches have been extensively utilized in the directed evolution of multiple enzymes, demonstrating success in catalyzing non-native substrates, enhancing catalytic activity, and acquiring novel functions. This review introduces three main strategies employed to achieve GCHTS: the elimination of toxic compounds via desired variants, enabling host cells to thrive in hazardous conditions; the complementation of an auxotroph with desired variants, where essential genes for cell growth have been eliminated; and the control of the transcription or expression of a reporter gene related to host cell growth, regulated by the desired variants. Additionally, we highlighted the recent developments in the in vivo continuous evolution of enzyme technology, including phage-assisted continuous evolution (PACE) and orthogonal DNA Replication (OrthoRep). Furthermore, this review discusses the challenges and future prospects in the field of growth-coupled selection for protein engineering.

Engineering and Expression Strategies for Optimization of L-Asparaginase Development and Production

Genetic engineering for heterologous expression has advanced in recent years. Model systems such as Escherichia coli, Bacillus subtilis and Pichia pastoris are often used as host microorganisms for the enzymatic production of L-asparaginase, an enzyme widely used in the clinic for the treatment of leukemia and in bakeries for the reduction of acrylamide. Newly developed recombinant L-asparaginase (L-ASNase) may have a low affinity for asparagine, reduced catalytic activity, low stability, and increased glutaminase activity or immunogenicity. Some successful commercial preparations of L-ASNase are now available. Therefore, obtaining novel L-ASNases with improved properties suitable for food or clinical applications remains a challenge. The combination of rational design and/or directed evolution and heterologous expression has been used to create enzymes with desired characteristics. Computer design, combined with other methods, could make it possible to generate mutant libraries of novel L-ASNases without costly and time-consuming efforts. In this review, we summarize the strategies and approaches for obtaining and developing L-ASNase with improved properties.

Acid-resistant enzymes: the acquisition strategies and applications

Enzymes have promising applications in chemicals, food, pharmaceuticals, and other variety products because of their high efficiency, specificity, and environmentally friendly properties. However, due to the complexity of raw materials, pH, temperature, solvents, etc., the application range of enzymes is greatly limited in the industry. Protein engineering and enzyme immobilization are classical strategies to overcome the limitations of industrial applications. Although the pH tendency of enzymes has been extensively researched, the mechanism underlying enzyme acid resistance is unclear, and a less practical strategy for altering the pH propensity of enzymes has been suggested. This review proposes that the optimum pH of enzyme is determined by the pKa values of active center ionizable amino acid residues. Three levels of acquiring acid-resistant enzymes are summarized: mining from extreme environments and enzyme databases, modification with protein engineering and enzyme microenvironment engineering, and de novo synthesis. The industrial applications of acid-resistant enzymes in chemicals, food, and pharmaceuticals are also summarized. KEY POINTS: • The mechanism of enzyme acid resistance is fundamentally determined. • The three aspects of the method for acquiring acid-resistant enzymes are summarized. • Computer-aided strategies and artificial intelligence are used to obtain acid-resistant enzymes.

Custom tuning of Rieske oxygenase reactivity

Rieske oxygenases use a Rieske-type [2Fe-2S] cluster and a mononuclear iron center to initiate a range of chemical transformations. However, few details exist regarding how this catalytic scaffold can be predictively tuned to catalyze divergent reactions. Therefore, in this work, using a combination of structural analyses, as well as substrate and rational protein-based engineering campaigns, we elucidate the architectural trends that govern catalytic outcome in the Rieske monooxygenase TsaM. We identify structural features that permit a substrate to be functionalized by TsaM and pinpoint active-site residues that can be targeted to manipulate reactivity. Exploiting these findings allowed for custom tuning of TsaM reactivity: substrates are identified that support divergent TsaM-catalyzed reactions and variants are created that exclusively catalyze dioxygenation or sequential monooxygenation chemistry. Importantly, we further leverage these trends to tune the reactivity of additional monooxygenase and dioxygenase enzymes, and thereby provide strategies to custom tune Rieske oxygenase reaction outcomes.

Role of mutations in a chemoenzymatic enantiodivergent C(sp3)-H insertion: exploring the mechanism and origin of stereoselectivity

New-to-nature enzymes have emerged as powerful catalysts in recent years for streamlining various stereoselective organic transformations. While synthetic strategies employing engineered enzymes have witnessed proliferating success, there is limited clarity on the mechanistic front and more so when considering molecular-level insights into the role of selected mutations, dramatically escalating catalytic competency and selectivity. We have investigated the mechanism and correlation between mutations and exquisite stereoselectivity of a lactone carbene insertion into the C(sp3)-H bond of substituted aniline, catalyzed by two mutants of a cytochrome P450 variant, "P411" (engineered through directed evolution) in which the axial cysteine has been mutated to serine, utilizing various computational tools. The pivotal role of S264 and L/R328 mutations in the active site has been delineated computationally using two cluster models, thus rationalizing the enantiodivergence. This report provides much-needed insights into the origin of enantiodivergence, furnishing a mechanistic framework for understanding the anchoring effects of H-bond donor residues with the lactone ring. This study is expected to have important implications in the rational design of stereodivergent enzymes and toward successful in silico enzyme designing.

Insight into de-regulation of amino acid feedback inhibition: a focus on structure analysis method

Regulation of amino acid's biosynthetic pathway is of significant importance to maintain homeostasis and cell functions. Amino acids regulate their biosynthetic pathway by end-product feedback inhibition of enzymes catalyzing committed steps of a pathway. Discovery of new feedback resistant enzyme variants to enhance industrial production of amino acids is a key objective in industrial biotechnology. Deregulation of feedback inhibition has been achieved for various enzymes using in vitro and in silico mutagenesis techniques. As enzyme's function, its substrate binding capacity, catalysis activity, regulation and stability are dependent on its structural characteristics, here, we provide detailed structural analysis of all feedback sensitive enzyme targets in amino acid biosynthetic pathways. Current review summarizes information regarding structural characteristics of various enzyme targets and effect of mutations on their structures and functions especially in terms of deregulation of feedback inhibition. Furthermore, applicability of various experimental as well as computational mutagenesis techniques to accomplish feedback resistance has also been discussed in detail to have an insight into various aspects of research work reported in this particular field of study.

In vitro continuous protein evolution empowered by machine learning and automation

Directed evolution has become one of the most successful and powerful tools for protein engineering. However, the efforts required for designing, constructing, and screening a large library of variants can be laborious, time-consuming, and costly. With the recent advent of machine learning (ML) in the directed evolution of proteins, researchers can now evaluate variants in silico and guide a more efficient directed evolution campaign. Furthermore, recent advancements in laboratory automation have enabled the rapid execution of long, complex experiments for high-throughput data acquisition in both industrial and academic settings, thus providing the means to collect a large quantity of data required to develop ML models for protein engineering. In this perspective, we propose a closed-loop in vitro continuous protein evolution framework that leverages the best of both worlds, ML and automation, and provide a brief overview of the recent developments in the field.

Protein engineering via sequence-performance mapping

Discovery and evolution of new and improved proteins has empowered molecular therapeutics, diagnostics, and industrial biotechnology. Discovery and evolution both require efficient screens and effective libraries, although they differ in their challenges because of the absence or presence, respectively, of an initial protein variant with the desired function. A host of high-throughput technologies-experimental and computational-enable efficient screens to identify performant protein variants. In partnership, an informed search of sequence space is needed to overcome the immensity, sparsity, and complexity of the sequence-performance landscape. Early in the historical trajectory of protein engineering, these elements aligned with distinct approaches to identify the most performant sequence: selection from large, randomized combinatorial libraries versus rational computational design. Substantial advances have now emerged from the synergy of these perspectives. Rational design of combinatorial libraries aids the experimental search of sequence space, and high-throughput, high-integrity experimental data inform computational design. At the core of the collaborative interface, efficient protein characterization (rather than mere selection of optimal variants) maps sequence-performance landscapes. Such quantitative maps elucidate the complex relationships between protein sequence and performance-e.g., binding, catalytic efficiency, biological activity, and developability-thereby advancing fundamental protein science and facilitating protein discovery and evolution.

Application of molecular dynamics simulation in the field of food enzymes: improving the thermal-stability and catalytic ability

Enzymes can produce high-quality food with low pollution, high function, high acceptability, and medical aid. However, most enzymes, in their native form, do not meet the industrial requirements. Sequence-based and structure-based methods are the two main strategies used for enzyme modification. Molecular Dynamics (MD) simulation is a sufficiently comprehensive technology, from a molecular perspective, which has been widely used for structure information analysis and enzyme modification. In this review, we summarize the progress and development of MD simulation, particularly for software, force fields, and a standard procedure. Subsequently, we review the application of MD simulation in various food enzymes for thermostability and catalytic improvement was reviewed in depth. Finally, the limitations and prospects of MD simulation in food enzyme modification research are discussed. This review highlights the significance of MD simulation and its prospects in food enzyme modification.

Protein-Inspired Control over Synthetic Polymer Folding for Structured Functional Nanoparticles in Water

The folding of proteins into functional nanoparticles with defined 3D structures has inspired chemists to create simple synthetic systems mimicking protein properties. The folding of polymers into nanoparticles in water proceeds via different strategies, resulting in the global compaction of the polymer chain. Herein, we review the different methods available to control the conformation of synthetic polymers and collapse/fold them into structured, functional nanoparticles, such as hydrophobic collapse, supramolecular self-assembly, and covalent cross-linking. A comparison is made between the design principles of protein folding to synthetic polymer folding and the formation of structured nanocompartments in water, highlighting similarities and differences in design and function. We also focus on the importance of structure for functional stability and diverse applications in complex media and cellular environments.

Nature-inspired Enzyme engineering and sustainable catalysis: biochemical clues from the world of plants and extremophiles

The use of enzymes to accelerate chemical reactions for the synthesis of industrially important products is rapidly gaining popularity. Biocatalysis is an environment-friendly approach as it not only uses non-toxic, biodegradable, and renewable raw materials but also helps to reduce waste generation. In this context, enzymes from organisms living in extreme conditions (extremozymes) have been studied extensively and used in industries (food and pharmaceutical), agriculture, and molecular biology, as they are adapted to catalyze reactions withstanding harsh environmental conditions. Enzyme engineering plays a key role in integrating the structure-function insights from reference enzymes and their utilization for developing improvised catalysts. It helps to transform the enzymes to enhance their activity, stability, substrates-specificity, and substrate-versatility by suitably modifying enzyme structure, thereby creating new variants of the enzyme with improved physical and chemical properties. Here, we have illustrated the relatively less-tapped potentials of plant enzymes in general and their sub-class of extremozymes for industrial applications. Plants are exposed to a wide range of abiotic and biotic stresses due to their sessile nature, for which they have developed various mechanisms, including the production of stress-response enzymes. While extremozymes from microorganisms have been extensively studied, there are clear indications that plants and algae also produce extremophilic enzymes as their survival strategy, which may find industrial applications. Typical plant enzymes, such as ascorbate peroxidase, papain, carbonic anhydrase, glycoside hydrolases and others have been examined in this review with respect to their stress-tolerant features and further improvement via enzyme engineering. Some rare instances of plant-derived enzymes that point to greater exploration for industrial use have also been presented here. The overall implication is to utilize biochemical clues from the plant-based enzymes for robust, efficient, and substrate/reaction conditions-versatile scaffolds or reference leads for enzyme engineering.

Enzyme Stability-Activity Trade-Off: New Insights from Protein Stability Weaknesses and Evolutionary Conservation

A general limitation of the use of enzymes in biotechnological processes under sometimes nonphysiological conditions is the complex interplay between two key quantities, enzyme activity and stability, where the increase of one is often associated with the decrease of the other. A precise stability-activity trade-off is necessary for the enzymes to be fully functional, but its weight in different protein regions and its dependence on environmental conditions is not yet elucidated. To advance this issue, we used the formalism that we have recently developed to effectively identify stability strength and weakness regions in protein structures and applied it to a large set of globular enzymes with known experimental structure and catalytic sites. Our analysis showed a striking oscillatory pattern of free energy compensation centered on the catalytic region. Indeed, catalytic residues are usually nonoptimal with respect to stability, but residues in the first shell around the catalytic site are, on the average, stability strengths and thus compensate for this lack of stability; residues in the second shell are weaker again, and so on. This trend is consistent across all enzyme families. It is accompanied by a similar, but less pronounced, pattern of residue conservation across evolution. In addition, we analyzed cold- and heat-adapted enzymes separately and highlighted different patterns of stability strengths and weaknesses, which provide insight into the longstanding problem of catalytic rate enhancement in cold environments. The successful comparison of our stability and conservation results with experimental fitness data, obtained by deep mutagenesis scanning, led us to propose criteria for improving catalytic activity while maintaining enzyme stability, a key goal in enzyme design.

Molecular Complementarity of Proteomimetic Materials for Target-Specific Recognition and Recognition-Mediated Complex Functions

As biomolecules essential for sustaining life, proteins are generated from long chains of 20 different α-amino acids that are folded into unique 3D structures. In particular, many proteins have molecular recognition functions owing to their binding pockets, which have complementary shapes, charges, and polarities for specific targets, making these biopolymers unique and highly valuable for biomedical and biocatalytic applications. Based on the understanding of protein structures and microenvironments, molecular complementarity can be exhibited by synthesizable and modifiable materials. This has prompted researchers to explore the proteomimetic potentials of a diverse range of materials, including biologically available peptides and oligonucleotides, synthetic supramolecules, inorganic molecules, and related coordination networks. To fully resemble a protein, proteomimetic materials perform the molecular recognition to mediate complex molecular functions, such as allosteric regulation, signal transduction, enzymatic reactions, and stimuli-responsive motions; this can also expand the landscape of their potential bio-applications. This review focuses on the recognitive aspects of proteomimetic designs derived for individual materials and their conformations. Recent progress provides insights to help guide the development of advanced protein mimicry with material heterogeneity, design modularity, and tailored functionality. The perspectives and challenges of current proteomimetic designs and tools are also discussed in relation to future applications.

DNA Polymerases for Whole Genome Amplification: Considerations and Future Directions

In the same way that specialized DNA polymerases (DNAPs) replicate cellular and viral genomes, only a handful of dedicated proteins from various natural origins as well as engineered versions are appropriate for competent exponential amplification of whole genomes and metagenomes (WGA). Different applications have led to the development of diverse protocols, based on various DNAPs. Isothermal WGA is currently widely used due to the high performance of Φ29 DNA polymerase, but PCR-based methods are also available and can provide competent amplification of certain samples. Replication fidelity and processivity must be considered when selecting a suitable enzyme for WGA. However, other properties, such as thermostability, capacity to couple replication, and double helix unwinding, or the ability to maintain DNA replication opposite to damaged bases, are also very relevant for some applications. In this review, we provide an overview of the different properties of DNAPs widely used in WGA and discuss their limitations and future research directions.

Second-Shell Residues Contribute to Catalysis by Predominately Preorganizing the Apo State in PafA

Residues beyond the first coordination shell are often observed to make considerable cumulative contributions in enzymes. Due to typically indirect perturbations of multiple physicochemical properties of the active site, however, their individual and specific roles in enzyme catalysis and disease-causing mutations remain difficult to predict and understand at the molecular level. Here we analyze the contributions of several second-shell residues in phosphate-irrepressible alkaline phosphatase of flavobacterium (PafA), a representative system as one of the most efficient enzymes. By adopting a multifaceted approach that integrates quantum-mechanical/molecular-mechanical free energy computations, molecular-mechanical molecular dynamics simulations, and density functional theory cluster model calculations, we probe the rate-limiting phosphoryl transfer step and structural properties of all relevant enzyme states. In combination with available experimental data, our computational results show that mutations of the studied second-shell residues impact catalytic efficiency mainly by perturbation of the apo state and therefore substrate binding, while they do not affect the ground state or alter the nature of phosphoryl transfer transition state significantly. Several second-shell mutations also modulate the active site hydration level, which in turn influences the energetics of phosphoryl transfer. These mechanistic insights also help inform strategies that may improve the efficiency of enzyme design and engineering by going beyond the current focus on the first coordination shell.

Immobilized biocatalyst engineering: Biocatalytic tool to obtain attractive enzymes for industry

Biocatalysis can improve current bioprocesses by identifying or improving enzymes that withstand harsh and unnatural operating conditions. Immobilized Biocatalyst Engineering (IBE) is a novel strategy integrating protein engineering and enzyme immobilization as a single workflow. Using IBE, it is possible to obtain immobilized biocatalysts whose soluble performance would not be selected. In this work, Bacillus subtilis lipase A (BSLA) variants obtained through IBE were characterized as soluble and immobilized biocatalysts, and how the interactions with the support affect their structure and catalytic performance were analyzed using intrinsic protein fluorescence. Variant P5G3 (Asn89Asp, Gln121Arg) showed a 2.6-fold increased residual activity after incubation at 76 °C compared to immobilized wild-type (wt) BSLA. On the other hand, variant P6C2 (Val149Ile) showed 4.4 times higher activity after incubation in 75 % isopropyl alcohol (36 °C) compared to Wt_BSLA. Furthermore, we studied the advancement of the IBE platform by performing synthesis and immobilizing the BSLA variants using a cell-free protein synthesis (CFPS) approach. The observed differences in immobilization performance, high temperature, and solvent resistance between the in vivo-produced variants and Wt_BSLA were confirmed for the in vitro synthesized enzymes. These results open the door for designing strategies integrating IBE and CFPS to generate and screen improved immobilized enzymes from genetic diversity libraries. Furthermore, it was confirmed that IBE is a platform that can be used to obtain improved biocatalysts, especially those with an unremarkable performance as soluble biocatalysts, which wouldn't be selected for immobilization and further development for specific applications.

Engineering TNA polymerases through iterative cycles of directed evolution

DNA polymerases are important tools for biotechnology, synthetic biology, and chemical biology as they are routinely used to amplify and edit genetic information. However, natural polymerases do not recognize artificial genetic polymers (also known as xeno-nucleic acids or XNAs) with unique sugar-phosphate backbone structures. Directed evolution offers a possible solution to this problem by facilitating the discovery of engineered versions of natural polymerases that can copy genetic information back and forth between DNA and XNA. Here we report a directed evolution strategy for discovering polymerases that can synthesize threose nucleic acid (TNA) on DNA templates. The workflow involves library generation and expression in E. coli, high-throughput microfluidics-based screening of uniform water-in-oil droplets, plasmid recovery, secondary screening, and library regeneration. This technique is sufficiently general that it could be applied to a wide range of problems involving DNA modifying enzymes.

In-depth analysis of biocatalysts by microfluidics: An emerging source of data for machine learning

Nowadays, the vastly increasing demand for novel biotechnological products is supported by the continuous development of biocatalytic applications which provide sustainable green alternatives to chemical processes. The success of a biocatalytic application is critically dependent on how quickly we can identify and characterize enzyme variants fitting the conditions of industrial processes. While miniaturization and parallelization have dramatically increased the throughput of next-generation sequencing systems, the subsequent characterization of the obtained candidates is still a limiting process in identifying the desired biocatalysts. Only a few commercial microfluidic systems for enzyme analysis are currently available, and the transformation of numerous published prototypes into commercial platforms is still to be streamlined. This review presents the state-of-the-art, recent trends, and perspectives in applying microfluidic tools in the functional and structural analysis of biocatalysts. We discuss the advantages and disadvantages of available technologies, their reproducibility and robustness, and readiness for routine laboratory use. We also highlight the unexplored potential of microfluidics to leverage the power of machine learning for biocatalyst development.

Enzyme Cascade with Horseradish Peroxidase Readout for High-Throughput Screening and Engineering of Human Arginase-1

We report an enzyme cascade with horseradish peroxidase-based readout for screening human arginase-1 (hArg1) activity. We combined the four enzymes hArg1, ornithine decarboxylase, putrescine oxidase, and horseradish peroxidase in a reaction cascade that generated colorimetric or fluorescent signals in response to hArg1 activity and used this cascade to assay wild-type and variant hArg1 sequences as soluble enzymes and displayed on the surface of Escherichia coli. We screened a curated 13-member hArg1 library covering mutations that modified the electrostatic environment surrounding catalytic residues D128 and H141, and identified the R21E variant with a 13% enhanced catalytic turnover rate compared to wild type. Our scalable one-pot single-step arginase assay with continuous kinetic readout is amenable to high-throughput screening and directed evolution of arginase libraries and testing drug candidates for arginase inhibition.

GH2 family β-galactosidases evolution using degenerate oligonucleotide gene shuffling

OBJECTIVES

To improve the biochemical characteristics of the GH2 family β-galactosidases using a family shuffling method based on degenerate oligonucleotide gene shuffling.

RESULTS

Four β-galactosidase genes from the genus Alteromonas were divided into 14 gene segments, and each included the homologous sequence in the adjacent segments. The gene segments were regenerated into complete β-galactosidase genes and amplified by PCR. The obtained chimeric genes were cloned into a plasmid and screened for β-galactosidase activity. Approximately 320 positive clones were observed on the screening plate, of which nine sequenced genes were chimera. Additionally, the M22 and M250 mutants were expressed, purified, and characterized. The optimal temperature and substrate specificity of the recombinant M22 and M250 were consistent with those of the wild-type enzymes. The catalytic efficiency of recombinant M22 enzyme was higher than that of the wild-type enzymes, and the recombinant M250 displayed weak transglycosylation activity.

CONCLUSIONS

The chimeric genes of GH2 β-galactosidase were obtained using a controlled family shuffling that will provide an enzyme evolutionary method to obtain the β-galactosidases with excellent characteristics for laboratory and industrial purposes.

Structure-driven protein engineering for production of valuable natural products

Proteins are the most frequently used biocatalysts, and their structures determine their functions. Modifying the functions of proteins on the basis of their structures lies at the heart of protein engineering, opening a new horizon for metabolic engineering by efficiently generating stable enzymes. Many attempts at classical metabolic engineering have focused on improving specific metabolic fluxes and producing more valuable natural products by increasing gene expression levels and enzyme concentrations. However, most naturally occurring enzymes show limitations, and such limitations have hindered practical applications. Here we review recent advances in protein engineering in synthetic biology, chemoenzymatic synthesis, and plant metabolic engineering and describe opportunities for designing and constructing novel enzymes or proteins with desirable properties to obtain more active natural products.

Enlightening the Path to Protein Engineering: Chemoselective Turn-On Probes for High-Throughput Screening of Enzymatic Activity

Many successful stories in enzyme engineering are based on the creation of randomized diversity in large mutant libraries, containing millions to billions of enzyme variants. Methods that enabled their evaluation with high throughput are dominated by spectroscopic techniques due to their high speed and sensitivity. A large proportion of studies relies on fluorogenic substrates that mimic the chemical properties of the target or coupled enzymatic assays with an optical read-out that assesses the desired catalytic efficiency indirectly. The most reliable hits, however, are achieved by screening for conversions of the starting material to the desired product. For this purpose, functional group assays offer a general approach to achieve a fast, optical read-out. They use the chemoselectivity, differences in electronic and steric properties of various functional groups, to reduce the number of false-positive results and the analytical noise stemming from enzymatic background activities. This review summarizes the developments and use of functional group probes for chemoselective derivatizations, with a clear focus on screening for enzymatic activity in protein engineering.

Protection of catalytic cofactors by polypeptides as a driver for the emergence of primordial enzymes

Enzymes catalyze the chemical reactions of life. For nearly half of known enzymes, catalysis requires the binding of small molecules known as cofactors. Polypeptide-cofactor complexes likely formed at a primordial stage and became starting points for the evolution of many efficient enzymes. Yet, evolution has no foresight so the driver for the primordial complex formation is unknown. Here, we use a resurrected ancestral TIM-barrel protein to identify one potential driver. Heme binding at a flexible region of the ancestral structure yields a peroxidation catalyst with enhanced efficiency when compared to free heme. This enhancement, however, does not arise from protein-mediated promotion of catalysis. Rather, it reflects protection of bound heme from common degradation processes and a resulting longer life time and higher effective concentration for the catalyst. Protection of catalytic cofactors by polypeptides emerges as a general mechanism to enhance catalysis and may have plausibly benefited primordial polypeptide-cofactor associations.

A Photoenzymatic Strategy for Radical-Mediated Stereoselective Hydroalkylation with Diazo Compounds

Carbene insertion reactions initiated with diazo compounds have been widely used to develop unnatural enzymatic reactions. However, alternative functionalization of diazo compounds in enzymatic processes has been unexploited. Herein, we describe a photoenzymatic strategy for radical-mediated stereoselective hydroalkylation with diazo compounds. This method generates carbon-centered radicals through an ene reductase catalyzed photoinduced electron transfer process from diazo compounds, enabling the synthesis of γ-stereogenic carbonyl compounds in good yields and stereoselectivities. This study further expands the possible reaction patterns in photo-biocatalysis and offers a new approach to solving the selectivity challenges of radical-mediated reactions.

Toward real-world automated antibody design with combinatorial Bayesian optimization

Antibodies are multimeric proteins capable of highly specific molecular recognition. The complementarity determining region 3 of the antibody variable heavy chain (CDRH3) often dominates antigen-binding specificity. Hence, it is a priority to design optimal antigen-specific CDRH3 to develop therapeutic antibodies. The combinatorial structure of CDRH3 sequences makes it impossible to query binding-affinity oracles exhaustively. Moreover, antibodies are expected to have high target specificity and developability. Here, we present AntBO, a combinatorial Bayesian optimization framework utilizing a CDRH3 trust region for an in silico design of antibodies with favorable developability scores. The in silico experiments on 159 antigens demonstrate that AntBO is a step toward practically viable in vitro antibody design. In under 200 calls to the oracle, AntBO suggests antibodies outperforming the best binding sequence from 6.9 million experimentally obtained CDRH3s. Additionally, AntBO finds very-high-affinity CDRH3 in only 38 protein designs while requiring no domain knowledge.

Data-driven enzyme engineering to identify function-enhancing enzymes

Identifying function-enhancing enzyme variants is a 'holy grail' challenge in protein science because it will allow researchers to expand the biocatalytic toolbox for late-stage functionalization of drug-like molecules, environmental degradation of plastics and other pollutants, and medical treatment of food allergies. Data-driven strategies, including statistical modeling, machine learning, and deep learning, have largely advanced the understanding of the sequence-structure-function relationships for enzymes. They have also enhanced the capability of predicting and designing new enzymes and enzyme variants for catalyzing the transformation of new-to-nature reactions. Here, we reviewed the recent progresses of data-driven models that were applied in identifying efficiency-enhancing mutants for catalytic reactions. We also discussed existing challenges and obstacles faced by the community. Although the review is by no means comprehensive, we hope that the discussion can inform the readers about the state-of-the-art in data-driven enzyme engineering, inspiring more joint experimental-computational efforts to develop and apply data-driven modeling to innovate biocatalysts for synthetic and pharmaceutical applications.