A Computational Library Design Protocol for Rapid Improvement of Protein Stability: FRESCO

Engineering Bacterial Laccase with Improved Catalytic Activity and Thermostability by Rational Design

Laccases (benzenediol:oxygen oxidoreductases) are important multi-copper oxidases with widespread applications in industry. Here, Bacillus subtilis laccase CotA that has been widely studied was engineered to improve catalytic activity and thermostability via rational design. After iterative mutation of beneficial mutation sites, a triple mutant of CotA laccase (DTA) was obtained, whose catalytic activity and thermostability were improved by 2.7-fold and 1.4-fold compared with the wild-type (WT) CotA, respectively. The enhanced activity of DTA is primarily due to strengthened intermolecular forces in the active site, while its improved thermostability is attributed to increased hydrophobic residues, augmented protein surface flexibility, collectively rendering DTA a more active and stable enzyme with potential industrial applications. Compared to WT, DTA can degrade mycotoxins aflatoxin B1 (55.09% vs 44.51%) and ZEN (zearalenone) (71.59% vs 41.09%) more efficiently, and DTA can also better pretreat lignocellulose, promoting the hydrolysis of cellulose by cellulase. All these indicate that DTA has the potential to be used in industry.

Overview of various protein engineering strategies to improve the catalytic activity, thermostability, and acid/base stability of β-glucanase

β-Glucan is highly valued in the food and medical industries due to its various physiological functions. However, its aqueous solution tends to have high viscosity, which negatively impacts the brewing and feed industries. By hydrolyzing β-glucosidic bonds, β-glucanase could reduce the adverse effects of β-glucan. For this reason, β-glucanase is widely utilized in the brewing and animal feed production. The limited thermal and acid stability of β-glucanase restricts its applications in industrial settings. Therefore, it is of great importance to enhance the stability of existing β-glucanases through protein engineering. This review summarizes current integrated technical methods for the molecular modification of β-glucanases, including error-prone PCR, site-saturation mutagenesis, DNA recombination, sequence alignment, N- and C-terminal modifications, surface charge optimization, intermolecular force optimization, and rigidity of flexible regions. The aim is to provide a theoretical basis and practical guidance for the further modification of β-glucanases.

Optimized protocols to measure stability of ligninolytic enzymes

Biocatalysis is considered a critical component for developing a sustainable bioeconomy, and stability is a crucial enzyme property for biotechnological and industrial applications. Enzymes with higher thermostability are more durable and desirable in industrial settings due to their resilience across various operational conditions, which helps reduce overall enzyme costs. Understanding an enzyme's thermal stability ensures its long-term efficacy and performance. Thermodynamic stability reflects the equilibrium between the native, functional protein, and unfolded state, and the kinetic or long-term stability is associated with the irreversible inactivation of the enzyme. Therefore, the thermostability of biocatalysts can be characterized by their melting temperature (Tm) when 50 % of the enzyme is unfolded and the half-life time (t1/2), reporting the time gap to the loss of 50 % of the activity at a specific temperature. This parameter is crucial for assessing the feasibility of an enzymatic-based (bio)process, as it indicates the enzyme's temperature-dependent deactivation and operational stability over time. The optimum temperature of an enzyme (Topt) usually reflects its (thermo)stability, particularly the stability of the native state. Here, we describe protocols for accessing the thermodynamic and kinetic stability of different ligninolytic enzymes, including laccases and DyP-type peroxidases. We provide practical examples and emphasize the challenges encountered during experimental procedures and data analysis. While these protocols are tailored to these specific enzymes, they can be broadly applied to other proteins and enzymes.

Bioinformatics and Computationally Supported Redesign of Aspartase for β-Alanine Synthesis by Acrylic Acid Hydroamination

Aspartate ammonia lyases catalyze the reversible amination of fumarate to l-aspartate. Recent studies demonstrate that the thermostable enzyme from Bacillus sp. YM55-1 (AspB) can be engineered for the enantioselective production of substituted β-amino acids. This reaction would be attractive for the conversion of acrylic acid to β-alanine, which is an important building block for the preparation of bioactive compounds. Here we describe a bioinformatics and computational approach aimed at introducing the β-alanine synthesis activity. Three strategies were used: First, we redesigned the α-carboxylate binding pocket of AspB to introduce activity with the acrylic acid. Next, different template enzymes were identified by genome mining, equipped with a redesigned α-carboxylate pocket, and investigated for β-alanine synthesis, which yielded variants with better activity. Third, interactions of the SS-loop that covers the active site and harbors a catalytic serine were computationally redesigned using energy calculations to stabilize reactive conformations and thereby further increase the desired β-alanine synthesis activity. Different improved enzymes were obtained and the best variants showed k cat values with acrylic acid of at least 0.6-1.5 s-1 with K M values in the high mM range. Since the β-alanine production of wild-type enzyme was below the detection limit, this suggests that the k cat/K m was improved by at least 1000-fold. Crystal structures of the 6-fold mutant of redesigned AspB and the similarly engineered aspartase from Caenibacillus caldisaponilyticus revealed that their ligand-free structures have the SS-loop in a closed (reactive) conformation, which for wild-type AspB is only observed in the substrate-bound enzyme. AlphaFold-generated models suggest that other aspartase variants redesigned for acrylic acid hydroamination also prefer a 3D structure with the loop in a closed conformation. The combination of binding pocket redesign, genome mining, and enhanced active-site loop closure thus created effective β-alanine synthesizing variants of aspartase.

Structure Prediction and Computational Protein Design for Efficient Biocatalysts and Bioactive Proteins

The ability to predict and design protein structures has led to numerous applications in medicine, diagnostics and sustainable chemical manufacture. In addition, the wealth of predicted protein structures has advanced our understanding of how life's molecules function and interact. Honouring the work that has fundamentally changed the way scientists research and engineer proteins, the Nobel Prize in Chemistry in 2024 was awarded to David Baker for computational protein design and jointly to Demis Hassabis and John Jumper, who developed AlphaFold for machine-learning-based protein structure prediction. Here, we highlight notable contributions to the development of these computational tools and their importance for the design of functional proteins that are applied in organic synthesis. Notably, both technologies have the potential to impact drug discovery as any therapeutic protein target can now be modelled, allowing the de novo design of peptide binders and the identification of small molecule ligands through in silico docking of large compound libraries. Looking ahead, we highlight future research directions in protein engineering, medicinal chemistry and material design that are enabled by this transformative shift in protein science.

Insight into Protein Engineering: From In silico Modelling to In vitro Synthesis

Protein engineering alters the polypeptide chain to obtain a novel protein with improved functional properties. This field constantly evolves with advanced in silico tools and techniques to design novel proteins and peptides. Rational incorporating mutations, unnatural amino acids, and post-translational modifications increases the applications of engineered proteins and peptides. It aids in developing drugs with maximum efficacy and minimum side effects. Currently, the engineering of peptides is gaining attention due to their high stability, binding specificity, less immunogenic, and reduced toxicity properties. Engineered peptides are potent candidates for drug development due to their high specificity and low cost of production compared with other biologics, including proteins and antibodies. Therefore, understanding the current perception of designing and engineering peptides with the help of currently available in silico tools is crucial. This review extensively studies various in silico tools available for protein engineering in the prospect of designing peptides as therapeutics, followed by in vitro aspects. Moreover, a discussion on the chemical synthesis and purification of peptides, a case study, and challenges are also incorporated.

A computational strategy to improve the activity of tyrosine phenol-lyase for the synthesis of L-DOPA

Enzymes with high catalytic activity and stability are essential for industrial production, yet most natural enzymes do not meet these requirements. Therefore, efficient strategies for enzyme engineering are crucial. In this study, we developed a cost-effective computational design strategy to enhance the activity of tyrosine phenol-lyase (TPL) for the production of L-DOPA. By integrating structural analysis with computational design, and guided by our understanding of conformational flexibility of TPL, we identified a region where enhanced stability is most likely to facilitate enzyme activity. We screened stabilizing mutations by Cartesian_ddg in Rosetta. After identifying single stabilizing mutations, we grouped the nearby positions harboring multiple stabilizing mutations and calculated the energy of combinatorial variants. We found two promising groups where most variants exhibited lower calculated energy than the wild-type. Experimental validation showed five variants in these groups exhibit increased activity, with the two best variants showing catalytic activity enhancements of 1.8-fold and 1.6-fold compared to the wild-type enzyme.

Addressing epistasis in the design of protein function

Mutations in protein active sites can dramatically improve function. The active site, however, is densely packed and extremely sensitive to mutations. Therefore, some mutations may only be tolerated in combination with others in a phenomenon known as epistasis. Epistasis reduces the likelihood of obtaining improved functional variants and dramatically slows natural and lab evolutionary processes. Research has shed light on the molecular origins of epistasis and its role in shaping evolutionary trajectories and outcomes. In addition, sequence- and AI-based strategies that infer epistatic relationships from mutational patterns in natural or experimental evolution data have been used to design functional protein variants. In recent years, combinations of such approaches and atomistic design calculations have successfully predicted highly functional combinatorial mutations in active sites. These were used to design thousands of functional active-site variants, demonstrating that, while our understanding of epistasis remains incomplete, some of the determinants that are critical for accurate design are now sufficiently understood. We conclude that the space of active-site variants that has been explored by evolution may be expanded dramatically to enhance natural activities or discover new ones. Furthermore, design opens the way to systematically exploring sequence and structure space and mutational impacts on function, deepening our understanding and control over protein activity.

Opportunities and challenges in design and optimization of protein function

The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calculations, as well as machine learning tools, have dramatically improved protein engineering and design. In this Review, we discuss how these methods have enabled the design of increasingly complex structures and therapeutically relevant activities. Additionally, protein optimization methods have improved the stability and activity of complex eukaryotic proteins. Thanks to their increased reliability, computational design methods have been applied to improve therapeutics and enzymes for green chemistry and have generated vaccine antigens, antivirals and drug-delivery nano-vehicles. Moreover, the high success of design methods reflects an increased understanding of basic rules that govern the relationships among protein sequence, structure and function. However, de novo design is still limited mostly to α-helix bundles, restricting its potential to generate sophisticated enzymes and diverse protein and small-molecule binders. Designing complex protein structures is a challenging but necessary next step if we are to realize our objective of generating new-to-nature activities.

Application of an alchemical free energy method for the prediction of thermostable DuraPETase variants

Non-equilibrium (NEQ) alchemical free energy calculations are an emerging tool for accurately predicting changes in protein folding free energy resulting from amino acid mutations. In this study, this method in combination with the Rosetta ddg monomer tool was applied to predict more thermostable variants of the polyethylene terephthalate (PET) degrading enzyme DuraPETase. The Rosetta ddg monomer tool efficiently enriched promising mutations prior to more accurate prediction by NEQ alchemical free energy calculations. The relative change in folding free energy of 96 single amino acid mutations was calculated by NEQ alchemical free energy calculation. Experimental validation of ten of the highest scoring variants identified two mutations (DuraPETaseS61M and DuraPETaseS223Y) that increased the melting temperature (Tm) of the enzyme by up to 1 °C. The calculated relative change in folding free energy showed an excellent correlation with experimentally determined Tm resulting in a Pearson's correlation coefficient of r =  - 0.84. Limitations in the prediction of strongly stabilizing mutations were, however, encountered and are discussed. Despite these challenges, this study demonstrates the practical applicability of NEQ alchemical free energy calculations in prospective enzyme engineering projects. KEY POINTS: • Rosetta ddg monomer enriches stabilizing mutations in a library of DuraPETase variants • NEQ free energy calculations accurately predict changes in Tm of DuraPETase • The DuraPETase variants S223Y, S42M, and S61M have increased Tm.

High-Throughput Screening Techniques for the Selection of Thermostable Enzymes

The acquisition of a thermostable enzyme is an indispensable prerequisite for its successful implementation in industrial applications and the development of novel functionalities. Various protein engineering approaches, including rational design, semirational design, and directed evolution, have been employed to enhance thermostability. However, all of these approaches require sensitive and reliable high-throughput screening (HTS) technologies to efficiently and rapidly identify variants with improved properties. While numerous reviews focus on modification strategies for enhancing enzyme thermostability, there is a dearth of literature reviewing HTS methods specifically aimed at this objective. Herein, we present a comprehensive overview of various HTS methods utilized for modifying enzyme thermostability across different screening platforms. Additionally, we highlight significant recent examples that demonstrate the successful application of these methods. Furthermore, we address the technical challenges associated with HTS technologies used for screening thermostable enzyme variants and discuss valuable perspectives to promote further advancements in this field. This review serves as an authoritative reference source offering theoretical support for selecting appropriate screening strategies tailored to specific enzymes with the aim of improving their thermostability.

Engineering the thermal stability of a polyphosphate kinase by ancestral sequence reconstruction to expand the temperature boundary for an industrially applicable ATP regeneration system

ATP-dependent energy-consuming enzymatic reactions are widely used in cell-free biocatalysis. However, the direct addition of large amounts of expensive ATP can greatly increase cost, and enzymatic production is often difficult to achieve as a result. Although a polyphosphate kinase (PPK)-polyphosphate-based ATP regeneration system has the potential to solve this challenge, the generally poor thermal stability of PPKs limits the widespread use of this method. In this paper, we evaluated the thermal stability of a PPK from Sulfurovum lithotrophicum (SlPPK2). After directed evolution and computation-supported design, we found that SlPPK2 is very recalcitrant and cannot acquire beneficial mutations. Inspired by the usually outstanding stability of ancestral enzymes, we reconstructed the ancestral sequence of the PPK family and used it as a guide to construct three heat-stable variants of SlPPK2, of which the L35F/T144S variant has a half-life of more than 14 h at 60°C. Molecular dynamics simulations were performed on all enzymes to analyze the reasons for the increased thermal stability. The results showed that mutations at these two positions act synergistically from the interior and surface of the protein, leading to a more compact structure. Finally, the robustness of the L35F/T144S variant was verified in the synthesis of nucleotides at high temperature. In practice, the use of this high-temperature ATP regeneration system can effectively avoid byproduct accumulation. Our work extends the temperature boundary of ATP regeneration and has great potential for industrial applications.IMPORTANCEATP regeneration is an important basic applied study in the field of cell-free biocatalysis. Polyphosphate kinase (PPK) is an enzyme tool widely used for energy regeneration during enzymatic reactions. However, the thermal stability of the PPKs reported to date that can efficiently regenerate ATP is usually poor, which greatly limits their application. In this study, the thermal stability of a difficult-to-engineer PPK from Sulfurovum lithotrophicum was improved, guided by an ancestral sequence reconstruction strategy. The optimal variant has a 4.5-fold longer half-life at 60°C than the wild-type enzyme, thus enabling the extension of the temperature boundary for ATP regeneration. The ability of this variant to regenerate ATP was well demonstrated during high-temperature enzymatic production of nucleotides.

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.

Fixing Flavins: Hijacking a Flavin Transferase for Equipping Flavoproteins with a Covalent Flavin Cofactor

Most flavin-dependent enzymes contain a dissociable flavin cofactor. We present a new approach for installing in vivo a covalent bond between a flavin cofactor and its host protein. By using a flavin transferase and carving a flavinylation motif in target proteins, we demonstrate that "dissociable" flavoproteins can be turned into covalent flavoproteins. Specifically, four different flavin mononucleotide-containing proteins were engineered to undergo covalent flavinylation: a light-oxygen-voltage domain protein, a mini singlet oxygen generator, a nitroreductase, and an old yellow enzyme-type ene reductase. Optimizing the flavinylation motif and expression conditions led to the covalent flavinylation of all four flavoproteins. The engineered covalent flavoproteins retained function and often exhibited improved performance, such as higher thermostability or catalytic performance. The crystal structures of the designed covalent flavoproteins confirmed the designed threonyl-phosphate linkage. The targeted flavoproteins differ in fold and function, indicating that this method of introducing a covalent flavin-protein bond is a powerful new method to create flavoproteins that cannot lose their cofactor, boosting their performance.

Stairway to Stereoisomers: Engineering Short- and Medium-Chain Ketoreductases To Produce Chiral Alcohols

The short- and medium-chain dehydrogenase/reductase superfamilies are responsible for most chiral alcohol production in laboratories and industries. In nature, they participate in diverse roles such as detoxification, housekeeping, secondary metabolite production, and catalysis of several chemicals with commercial and environmental significance. As a result, they are used in industries to create biopolymers, active pharmaceutical intermediates (APIs), and are also used as components of modular enzymes like polyketide synthases for fabricating bioactive molecules. Consequently, random, semi-rational and rational engineering have helped transform these enzymes into product-oriented efficient catalysts. The rise of newer synthetic chemicals and their enantiopure counterparts has proved challenging, and engineering them has been the subject of numerous studies. However, they are frequently limited to the synthesis of a single chiral alcohol. The study attempts to defragment and describe hotspots of engineering short- and medium-chain dehydrogenases/reductases for the production of chiral synthons.

Stability of enzyme immobilized on the nanofluidic channel surface

The lifetime of an enzyme is critical to prevent system failure and optimize maintenance schedules in biological and analytical chemistry. The lifetime metrics of an enzyme can be evaluated from enzyme activity in terms of catalytic cycles per enzyme at various storage times. Trypsin, which is a gold-standard enzyme in proteomics, has been known to decrease activity due to self-digestion. To improve the activity of trypsin, enzyme reactors have developed by immobilizing in micro and nanospace. However, an evaluation method for the catalytic cycle has not been established due to major issues such as nonuniform space, unstable liquid transport, and self-digestion during immobilization in conventional work. To solve these issues, we have previously developed an ultra-fast enzyme reactor with a well-defined nanofabrication method, stable liquid transport, and partial enzyme modification. Here, we aimed to investigate catalytic cycles in a nanochannel. To extend enzyme lifetime efficiently, we have evaluated the optimal immobilization process and catalytic cycles of trypsin. As a result, immobilized enzyme densities by the trypsinogen immobilization process were increased at all concentrations compared to the trypsin immobilization process. To evaluate the lifetime of trypsin, the immobilized enzyme densities and activities were almost the same before and after 72 h of enzyme storage, and the calculated catalytic cycles were 1740. These results indicated that self-digestion of the immobilized enzyme was highly suppressed. Consequently, the reaction efficiency has been evaluated depending on the catalytic cycles from the substrate for the first time, while preventing self-digestion by trypsin.

Using High-Throughput Molecular Dynamics Simulation to Enhance the Computational Design of Kemp Elimination Enzymes

Computational enzyme design has been successfully applied to identify new alternatives to natural enzymes for the biosynthesis of important compounds. However, the moderate catalytic activities of de novo designed enzymes indicate that the modeling accuracy of current computational enzyme design methods should be improved. Here, high-throughput molecular dynamics simulations were used to enhance computational enzyme design, thus allowing the identification of variants with higher activities in silico. Different time schemes of high-throughput molecular dynamics simulations were tested to identify the catalytic features of evolved Kemp eliminases. The 20 × 1 ns molecular dynamics simulation scheme was sufficiently accurate and computationally viable to screen the computationally designed massive variants of Kemp elimination enzymes. The developed hybrid computational strategy was used to redesign the most active Kemp eliminase, HG3.17, and five variants were generated and experimentally confirmed to afford higher catalytic efficiencies than that of HG3.17, with one double variant (D52Q/A53S) exhibiting a 55% increase. The hybrid computational enzyme design strategy is general and computationally economical, with which we anticipate the efficient creation of practical enzymes for industrial biocatalysis.

Alteration of Chain-Length Selectivity and Thermostability of Rhizopus oryzae Lipase via Virtual Saturation Mutagenesis Coupled with Disulfide Bond Design

Rhizopus oryzae lipase (ROL) is one of the most important enzymes used in the food, biofuel, and pharmaceutical industries. However, the highly demanding conditions of industrial processes can reduce its stability and activity. To seek a feasible method to improve both the catalytic activity and the thermostability of this lipase, first, the structure of ROL was divided into catalytic and noncatalytic regions by identifying critical amino acids in the crevice-like binding pocket. Second, a mutant screening library aimed at improvement of ROL catalytic performance by virtual saturation mutagenesis of residues in the catalytic region was constructed based on Rosetta's Cartesian_ddg protocol. A double mutant, E265V/S267W (with an E-to-V change at residue 265 and an S-to-W change at residue 267), with markedly improved catalytic activity toward diverse chain-length fatty acid esters was identified. Then, computational design of disulfide bonds was conducted for the noncatalytic amino acids of E265V/S267W, and two potential disulfide bonds, S61C-S115C and E190C-E238C, were identified as candidates. Experimental data validated that the variant E265V/S267W/S61C-S115C/E190C-E238C had superior stability, with an increase of 8.5°C in the melting temperature and a half-life of 31.7 min at 60°C, 4.2-fold longer than that of the wild-type enzyme. Moreover, the variant improved the lipase activity toward five 4-nitrophenyl esters by 1.5 to 3.8 times, exhibiting a potential to modify the catalytic efficiency. IMPORTANCE Rhizopus oryzae lipase (ROL) is very attractive in biotechnology and industry as a safe and environmentally friendly biocatalyst. Functional expression of ROL in Escherichia coli facilitates effective high-throughput screening for positive variants. This work highlights a method to improve both selectivity and thermostability based on a combination of virtual saturation mutagenesis in the substrate pocket and disulfide bond prediction in the noncatalytic region. Using the method, ROL thermostability and activity to diverse 4-nitrophenyl esters could be substantially improved. The strategy of rational introduction of multiple mutations in different functional domains of the enzyme is a great prospect in the modification of biocatalysts.

Non-canonical amino acids as a tool for the thermal stabilization of enzymes

Biocatalysis has become a powerful alternative for green chemistry. Expanding the range of amino acids used in protein biosynthesis can improve industrially appealing properties such as enantioselectivity, activity and stability. This review will specifically delve into the thermal stability improvements that non-canonical amino acids (ncAAs) can confer to enzymes. Methods to achieve this end, such as the use of halogenated ncAAs, selective immobilization and rational design, will be discussed. Additionally, specific enzyme design considerations using ncAAs are discussed along with the benefits and limitations of the various approaches available to enhance the thermal stability of enzymes.

Computation-Aided Engineering of Cytochrome P450 for the Production of Pravastatin

CYP105AS1 is a cytochrome P450 from Amycolatopsis orientalis that catalyzes monooxygenation of compactin to 6-epi-pravastatin. For fermentative production of the cholesterol-lowering drug pravastatin, the stereoselectivity of the enzyme needs to be inverted, which has been partially achieved by error-prone PCR mutagenesis and screening. In the current study, we report further optimization of the stereoselectivity by a computationally aided approach. Using the CoupledMoves protocol of Rosetta, a virtual library of mutants was designed to bind compactin in a pro-pravastatin orientation. By examining the frequency of occurrence of beneficial substitutions and rational inspection of their interactions, a small set of eight mutants was predicted to show the desired selectivity and these variants were tested experimentally. The best CYP105AS1 variant gave >99% stereoselective hydroxylation of compactin to pravastatin, with complete elimination of the unwanted 6-epi-pravastatin diastereomer. The enzyme-substrate complexes were also examined by ultrashort molecular dynamics simulations of 50 × 100 ps and 5 × 22 ns, which revealed that the frequency of occurrence of near-attack conformations agreed with the experimentally observed stereoselectivity. These results show that a combination of computational methods and rational inspection could improve CYP105AS1 stereoselectivity beyond what was obtained by directed evolution. Moreover, the work lays out a general in silico framework for specificity engineering of enzymes of known structure.

Structure- and computational-aided engineering of an oxidase to produce isoeugenol from a lignin-derived compound

Various 4-alkylphenols can be easily obtained through reductive catalytic fractionation of lignocellulosic biomass. Selective dehydrogenation of 4-n-propylguaiacol results in the formation of isoeugenol, a valuable flavor and fragrance molecule and versatile precursor compound. Here we present the engineering of a bacterial eugenol oxidase to catalyze this reaction. Five mutations, identified from computational predictions, are first introduced to render the enzyme more thermostable. Other mutations are then added and analyzed to enhance chemoselectivity and activity. Structural insight demonstrates that the slow catalytic activity of an otherwise promising enzyme variant is due the formation of a slowly-decaying covalent substrate-flavin cofactor adduct that can be remedied by targeted residue changes. The final engineered variant comprises eight mutations, is thermostable, displays good activity and acts as a highly chemoselective 4-n-propylguaiacol oxidase. We lastly use our engineered biocatalyst in an illustrative preparative reaction at gram-scale. Our findings show that a natural enzyme can be redesigned into a tailored biocatalyst capable of valorizing lignin-based monophenols.

The structures and applications of microbial chondroitin AC lyase

As an important glycosaminoglycan hydrolase, chondroitin lyases can hydrolyze chondroitin sulfate (CS) and release disaccharides and oligosaccharides. They are further divided into chondroitin AC, ABC, and B lyases according to their spatial structure and substrate specificity. Chondroitin AC lyase can hydrolyze chondroitin sulfate A (CS-A), chondroitin sulfate C (CS-C), and hyaluronic acid (HA), making it an essential biocatalyst for the preparation of low molecular weight chondroitin sulfate, analysis of the structure of the chondroitin sulfate, treatment of spinal cord injury, and purification of heparin. This paper provides an overview of reported chondroitin AC lyases, including their properties and the challenges faced in industrial applications. Up to now, although many attempts have been adopted to improve the enzyme properties, the most important factors are still the low activity and stability. The relations between the stability of the enzyme and the spatial structure were also summarized and discussed. Also perspectives for remodeling the enzymes with protein engineering are included.

What Have We Learned from Design of Function in Large Proteins?

The overarching goal of computational protein design is to gain complete control over protein structure and function. The majority of sophisticated binders and enzymes, however, are large and exhibit diverse and complex folds that defy atomistic design calculations. Encouragingly, recent strategies that combine evolutionary constraints from natural homologs with atomistic calculations have significantly improved design accuracy. In these approaches, evolutionary constraints mitigate the risk from misfolding and aggregation, focusing atomistic design calculations on a small but highly enriched sequence subspace. Such methods have dramatically optimized diverse proteins, including vaccine immunogens, enzymes for sustainable chemistry, and proteins with therapeutic potential. The new generation of deep learning-based ab initio structure predictors can be combined with these methods to extend the scope of protein design, in principle, to any natural protein of known sequence. We envision that protein engineering will come to rely on completely computational methods to efficiently discover and optimize biomolecular activities.

Structural-Based Modeling in Protein Engineering. A Must Do

Biotechnological solutions will be a key aspect in our immediate future society, where optimized enzymatic processes through enzyme engineering might be an important solution for waste transformation, clean energy production, biodegradable materials, and green chemistry, for example. Here we advocate the importance of structural-based bioinformatics and molecular modeling tools in such developments. We summarize our recent experiences indicating a great prediction/success ratio, and we suggest that an early in silico phase should be performed in enzyme engineering studies. Moreover, we demonstrate the potential of a new technique combining Rosetta and PELE, which could provide a faster and more automated procedure, an essential aspect for a broader use.

De novo sequence redesign of a functional Ras-binding domain globally inverted the surface charge distribution and led to extreme thermostability

To acquire extremely thermostable proteins of given functions is challenging for conventional protein engineering. Here we applied ABACUS, a statistical energy function we developed for de novo amino acid sequence design, to globally redesign a Ras-binding domain (RBD), and obtained an extremely thermostable RBD that unfolds reversibly at above 110°C, the redesigned RBD experimentally confirmed to have expected structure and Ras-binding interface. Directed evolution of the redesigned RBD improved its Ras-binding affinity to the native protein level without excessive loss of thermostability. The designed amino acid substitutions were mostly at the protein surface. For many substitutions, strong epistasis or significantly differentiated effects on thermostability in the native sequence context relative to the redesigned sequence context were observed, suggesting the globally redesigned sequence to be unreachable through combining beneficial mutations of the native sequence. Further analyses revealed that by replacing 38 of a total of 48 non-interfacial surface residues at once, ABACUS redesign was able to globally "invert" the protein's charge distribution pattern in an optimized way. Our study demonstrates that computational protein design provides powerful new tools to solve challenging protein engineering problems.

Stabilizing AqdC, a Pseudomonas Quinolone Signal-Cleaving Dioxygenase from Mycobacteria, by FRESCO-Based Protein Engineering

The mycobacterial PQS dioxygenase AqdC, a cofactor-less protein with an α/β-hydrolase fold, inactivates the virulence-associated quorum-sensing signal molecule 2-heptyl-3-hydroxy-4(1H)-quinolone (PQS) produced by the opportunistic pathogen Pseudomonas aeruginosa and is therefore a potential anti-virulence tool. We have used computational library design to predict stabilizing amino acid replacements in AqdC. While 57 out of 91 tested single substitutions throughout the protein led to stabilization, as judged by increases in T app m of >2 °C, they all impaired catalytic activity. Combining substitutions, the proteins AqdC-G40K-A134L-G220D-Y238W and AqdC-G40K-G220D-Y238W showed extended half-lives and the best trade-off between stability and activity, with increases in T app m of 11.8 and 6.1 °C and relative activities of 22 and 72 %, respectively, compared to AqdC. Molecular dynamics simulations and principal component analysis suggested that stabilized proteins are less flexible than AqdC, and the loss of catalytic activity likely correlates with an inability to effectively open the entrance to the active site.

Simultaneous directed evolution of coupled enzymes for efficient asymmetric synthesis of l-phosphinothricin

The traditional strategy to improve the efficiency of an entire coupled enzyme system relies on separate direction of the evolution of enzymes involved in their respective enzymatic reactions. This strategy can lead to enhanced single-enzyme catalytic efficiency but may also lead to loss of coordination among enzymes. This study aimed to overcome such shortcomings by executing a directed evolution strategy on multiple enzymes in one combined group that catalyzes the asymmetric biosynthesis of l-phosphinothricin. The genes of a glutamate dehydrogenase from Pseudomonas moorei (PmGluDH) and a glucose dehydrogenase from Exiguobacterium sibiricum (EsGDH), along with other gene parts (promoters, ribosomal binding sites (RBSs), and terminators) were simultaneously evolved. The catalytic efficiency of PmGluDH was boosted by introducing the beneficial mutation A164G (from 1.29 s^-1mM^-1 to 183.52 s^-1mM^-1), and the EsGDH expression level was improved by optimizing the linker length between the RBS and the start codon of gdh. The total turnover numbers of the bioreaction increased from 115 (GluDH WT^NADPH) to 5846 (A164G^NADPH coupled with low expression of EsGDH), and to 33950 (A164G^NADPH coupled with high expression of EsGDH). The coupling efficiency was increased from ∼30% (GluDH_WT with low expression of GDH) to 83.3% (GluDH_A164G with high expression of GDH). In the batch production of l-phosphinothricin utilizing whole-cell catalysis, the strongest biocatalytic reaction exhibited a high space-time yield (6410 g·L^-1·d^-1) with strict stereoselectivity (>99% enantiomeric excess).Importance: The traditional strategy to improve multienzyme-catalyzed reaction efficiency may lead to enhanced single-enzyme catalytic efficiency but may also result in loss of coordination among enzymes. We describe a directed evolution strategy of an entire coupled enzyme system to simultaneously enhance enzyme coordination and catalytic efficiency. The simultaneous evolution strategy was applied to a multienzyme-catalyzed reaction for the asymmetric synthesis of l-phosphinothricin, which not only enhanced the catalytic efficiency of GluDH but also improved the coordination between GluDH and GDH. Since this strategy is enzyme-independent, it may be applicable to other coupled enzyme systems for chiral chemical synthesis.

Using Mutability Landscapes To Guide Enzyme Thermostabilization

Thermostabilizing enzymes while retaining their activity and enantioselectivity for applied biocatalysis is an important topic in protein engineering. Rational and computational design strategies as well as directed evolution have been used successfully to thermostabilize enzymes. Herein, we describe an alternative mutability-landscape approach that identified three single mutations (R11Y, R11I and A33D) within the enzyme 4-oxalocrotonate tautomerase (4-OT), which has potential as a biocatalyst for pharmaceutical synthesis, that gave rise to significant increases in apparent melting temperature Tm (up to 20 °C) and in half-life at 80 °C (up to 111-fold). Introduction of these beneficial mutations in an enantioselective but thermolabile 4-OT variant (M45Y/F50A) afforded improved triple-mutant enzyme variants showing an up to 39 °C increase in Tm value, with no reduction in catalytic activity or enantioselectivity. This study illustrates the power of mutability-landscape-guided protein engineering for thermostabilizing enzymes.

Can constraint network analysis guide the identification phase of KnowVolution? A case study on improved thermostability of an endo-β-glucanase

Cellulases are industrially important enzymes, e.g., in the production of bioethanol, in pulp and paper industry, feedstock, and textile. Thermostability is often a prerequisite for high process stability and improving thermostability without affecting specific activities at lower temperatures is challenging and often time-consuming. Protein engineering strategies that combine experimental and computational are emerging in order to reduce experimental screening efforts and speed up enzyme engineering campaigns. Constraint Network Analysis (CNA) is a promising computational method that identifies beneficial positions in enzymes to improve thermostability. In this study, we compare CNA and directed evolution in the identification of beneficial positions in order to evaluate the potential of CNA in protein engineering campaigns (e.g., in the identification phase of KnowVolution). We engineered the industrially relevant endoglucanase EGLII from Penicillium verruculosum towards increased thermostability. From the CNA approach, six variants were obtained with an up to 2-fold improvement in thermostability. The overall experimental burden was reduced to 40% utilizing the CNA method in comparison to directed evolution. On a variant level, the success rate was similar for both strategies, with 0.27% and 0.18% improved variants in the epPCR and CNA-guided library, respectively. In essence, CNA is an effective method for identification of positions that improve thermostability.

Yosshi: a web-server for disulfide engineering by bioinformatic analysis of diverse protein families

Disulfide bonds play a significant role in protein stability, function or regulation but are poorly conserved among evolutionarily related proteins. The Yosshi can help to understand the role of S–S bonds by comparing sequences and structures of homologs with diverse properties and different disulfide connectivity patterns within a common structural fold of a superfamily, and assist to select the most promising hot-spots to improve stability of proteins/enzymes or modulate their functions by introducing naturally occurring crosslinks. The bioinformatic analysis is supported by the integrated Mustguseal web-server to construct large structure-guided sequence alignments of functionally diverse protein families that can include thousands of proteins based on all available information in public databases. The Yosshi+Mustguseal is a new integrated web-tool for a systematic homology-driven analysis and engineering of S–S bonds that facilitates a broader interpretation of disulfides not just as a factor of structural stability, but rather as a mechanism to implement functional diversity within a superfamily. The results can be downloaded as a content-rich PyMol session file or further studied online using the HTML5-based interactive analysis tools. Both web-servers are free and open to all users at https://biokinet.belozersky.msu.ru/yosshi and there is no login requirement.

Approaching boiling point stability of an alcohol dehydrogenase through computationally-guided enzyme engineering

Enzyme instability is an important limitation for the investigation and application of enzymes. Therefore, methods to rapidly and effectively improve enzyme stability are highly appealing. In this study we applied a computational method (FRESCO) to guide the engineering of an alcohol dehydrogenase. Of the 177 selected mutations, 25 mutations brought about a significant increase in apparent melting temperature (ΔTm ≥ +3 °C). By combining mutations, a 10-fold mutant was generated with a Tm of 94 °C (+51 °C relative to wild type), almost reaching water's boiling point, and the highest increase with FRESCO to date. The 10-fold mutant's structure was elucidated, which enabled the identification of an activity-impairing mutation. After reverting this mutation, the enzyme showed no loss in activity compared to wild type, while displaying a Tm of 88 °C (+45 °C relative to wild type). This work demonstrates the value of enzyme stabilization through computational library design.

Robust ω-Transaminases by Computational Stabilization of the Subunit Interface

Transaminases are attractive catalysts for the production of enantiopure amines. However, the poor stability of these enzymes often limits their application in biocatalysis. Here, we used a framework for enzyme stability engineering by computational library design (FRESCO) to stabilize the homodimeric PLP fold type I ω-transaminase from Pseudomonas jessenii. A large number of surface-located point mutations and mutations predicted to stabilize the subunit interface were examined. Experimental screening revealed that 10 surface mutations out of 172 tested were indeed stabilizing (6% success), whereas testing 34 interface mutations gave 19 hits (56% success). Both the extent of stabilization and the spatial distribution of stabilizing mutations showed that the subunit interface was critical for stability. After mutations were combined, 2 very stable variants with 4 and 6 mutations were obtained, which in comparison to wild type (T _m ^app = 62 °C) displayed T _m ^app values of 80 and 85 °C, respectively. These two variants were also 5-fold more active at their optimum temperatures and tolerated high concentrations of isopropylamine and cosolvents. This allowed conversion of 100 mM acetophenone to (S)-1-phenylethylamine (>99% enantiomeric excess) with high yield (92%, in comparison to 24% with the wild-type transaminase). Crystal structures mostly confirmed the expected structural changes and revealed that the most stabilizing mutation, I154V, featured a rarely described stabilization mechanism: namely, removal of steric strain. The results show that computational interface redesign can be a rapid and powerful strategy for transaminase stabilization.

Learning the changes of barnase mutants thermostability from structural fluctuations obtained using anisotropic network modeling

In biotechnology applications, rational design of new proteins with improved physico-chemical properties includes a number of important tasks. One of the greatest practical and fundamental challenges is the design of highly thermostable protein enzymes that maintain catalytic activity at high temperatures. This problem may be solved by introducing mutations into the wild-type enzyme protein. In this work, to predict the impact of such mutations in barnase protein we applied the anisotropic network modeling approach, revealing atomic fluctuations in structural regions that are changed in mutants compared to the wild-type protein. A regression model was constructed based on these structural features that can allow one to predict the thermal stability of new barnase mutants. Moreover, the analysis of regression model provides a mechanistic explanation of how the structural features can contribute to the thermal stability of barnase mutants.

Creating Flavin Reductase Variants with Thermostable and Solvent-Tolerant Properties by Rational-Design Engineering

We have employed computational approaches-FireProt and FRESCO-to predict thermostable variants of the reductase component (C₁ ) of (4-hydroxyphenyl)acetate 3-hydroxylase. With the additional aid of experimental results, two C₁ variants, A166L and A58P, were identified as thermotolerant enzymes, with thermostability improvements of 2.6-5.6 °C and increased catalytic efficiency of 2- to 3.5-fold. After heat treatment at 45 °C, both of the thermostable C₁ variants remain active and generate reduced flavin mononucleotide (FMNH^- ) for reactions catalyzed by bacterial luciferase and by the monooxygenase C₂ more efficiently than the wild type (WT). In addition to thermotolerance, the A166L and A58P variants also exhibited solvent tolerance. Molecular dynamics (MD) simulations (6 ns) at 300-500 K indicated that mutation of A166 to L and of A58 to P resulted in structural changes with increased stabilization of hydrophobic interactions, and thus in improved thermostability. Our findings demonstrated that improvements in the thermostability of C₁ enzyme can lead to broad-spectrum uses of C₁ as a redox biocatalyst for future industrial applications.

Structure-Based Redesign of a Self-Sufficient Flavin-Containing Monooxygenase towards Indigo Production

Indigo is currently produced by a century-old petrochemical-based process, therefore it is highly attractive to develop a more environmentally benign and efficient biotechnological process to produce this timeless dye. Flavin-containing monooxygenases (FMOs) are able to oxidize a wide variety of substrates. In this paper we show that the bacterial mFMO can be adapted to improve its ability to convert indole into indigo. The improvement was achieved by a combination of computational and structure-inspired enzyme redesign. We showed that the thermostability and the k_cat for indole could be improved 1.5-fold by screening a relatively small number of enzyme mutants. This project not only resulted in an improved biocatalyst but also provided an improved understanding of the structural elements that determine the activity of mFMO and provides hints for further improvement of the monooxygenase as biocatalyst.

Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor

Metabolic heterogeneity between individual cells of a population harbors significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence require tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e., the ultimate functional output of metabolic activity, on the single-cell level. Here, combining promoter engineering, computational protein design, biochemical methods, proteomics, and metabolomics, we developed a biosensor to measure glycolytic flux in single yeast cells. Therefore, drawing on the robust cell-intrinsic correlation between glycolytic flux and levels of fructose-1,6-bisphosphate (FBP), we transplanted the B. subtilis FBP-binding transcription factor CggR into yeast. With the developed biosensor, we robustly identified cell subpopulations with different FBP levels in mixed cultures, when subjected to flow cytometry and microscopy. Employing microfluidics, we were also able to assess the temporal FBP/glycolytic flux dynamics during the cell cycle. We anticipate that our biosensor will become a valuable tool to identify and study metabolic heterogeneity in cell populations.

Highly thermostable carboxylic acid reductases generated by ancestral sequence reconstruction

Carboxylic acid reductases (CARs) are biocatalysts of industrial importance. Their properties, especially their poor stability, render them sub-optimal for use in a bioindustrial pipeline. Here, we employed ancestral sequence reconstruction (ASR) - a burgeoning engineering tool that can identify stabilizing but enzymatically neutral mutations throughout a protein. We used a three-algorithm approach to reconstruct functional ancestors of the Mycobacterial and Nocardial CAR1 orthologues. Ancestral CARs (AncCARs) were confirmed to be CAR enzymes with a preference for aromatic carboxylic acids. Ancestors also showed varied tolerances to solvents, pH and in vivo-like salt concentrations. Compared to well-studied extant CARs, AncCARs had a Tm up to 35 °C higher, with half-lives up to nine times longer than the greatest previously observed. Using ancestral reconstruction we have expanded the existing CAR toolbox with three new thermostable CAR enzymes, providing access to the high temperature biosynthesis of aldehydes to drive new applications in biocatalysis.

Stabilization of cyclohexanone monooxygenase by computational and experimental library design

Enzymes often by far exceed the activity, selectivity, and sustainability achieved with chemical catalysts. One of the main reasons for the lack of biocatalysis in the chemical industry is the poor stability exhibited by many enzymes when exposed to process conditions. This dilemma is exemplified in the usually very temperature‐sensitive enzymes catalyzing the Baeyer–Villiger reaction, which display excellent stereo‐ and regioselectivity and offer a green alternative to the commonly used, explosive peracids. Here we describe a protein engineering approach applied to cyclohexanone monooxygenase from Rhodococcus sp. HI‐31, a substrate‐promiscuous enzyme that efficiently catalyzes the production of the nylon‐6 precursor ε‐caprolactone. We used a framework for rapid enzyme stabilization by computational libraries (FRESCO), which predicts protein‐stabilizing mutations. From 128 screened point mutants, approximately half had a stabilizing effect, albeit mostly to a small degree. To overcome incompatibility effects observed upon combining the best hits, an easy shuffled library design strategy was devised. The most stable and highly active mutant displayed an increase in unfolding temperature of 13°C and an approximately 33x increase in half‐life at 30°C. In contrast to the wild‐type enzyme, this thermostable 8x mutant is an attractive biocatalyst for biotechnological applications.

Creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design

BACKGROUND

HMF oxidase (HMFO) from Methylovorus sp. is a recently characterized flavoprotein oxidase. HMFO is a remarkable enzyme as it is able to oxidize 5-hydroxymethylfurfural (HMF) into 2,5-furandicarboxylic acid (FDCA): a catalytic cascade of three oxidation steps. Because HMF can be formed from fructose or other sugars and FDCA is a polymer building block, this enzyme has gained interest as an industrially relevant biocatalyst.

RESULTS

To increase the robustness of HMFO, a requirement for biotechnological applications, we decided to enhance its thermostability using the recently developed FRESCO method: a computational approach to identify thermostabilizing mutations in a protein structure. To make this approach even more effective, we now developed a new and facile gene shuffling approach to rapidly combine stabilizing mutations in a one-pot reaction. This allowed the identification of the optimal combination of seven beneficial mutations. The created thermostable HMFO mutant was further studied as a biocatalyst for the production of FDCA from HMF and was shown to perform significantly better than the original HMFO.

CONCLUSIONS

The described new gene shuffling approach quickly discriminates stable and active multi-site variants. This makes it a very useful addition to FRESCO. The resulting thermostable HMFO variant tolerates the presence of cosolvents and also remained thermotolerant after introduction of additional mutations aimed at improving the catalytic activity. Due to its stability and catalytic efficiency, the final HMFO variant appears to be a promising candidate for industrial scale production of FDCA from HMF.