Semi-rational approaches to engineering enzyme activity: combining the benefits of directed evolution and rational design

Transcriptional regulator-based biosensors for biomanufacturing in Corynebacterium glutamicum

Intracellular biosensors based on transcriptional regulators have become essential instruments in biomanufacturing, extensively employed for the semi-quantitative assessment of intracellular metabolites, high-throughput screening of production strains, and the directed evolution of enzymes. Corynebacterium glutamicum serves as an industrial chassis for the production of amino acids and a variety of high-value-added chemicals. This paper discusses the varieties and modes of action of transcriptional regulators employed in the construction of intracellular biosensors in C. glutamicum. It also reviews the design principles and progress in the application of transcriptional regulator-based biosensors. Furthermore, measures designed to improve the efficacy of these biosensors are delineated. The challenges and future prospects of biosensors based on transcriptional regulators in practical applications are analyzed. This review seeks to offer theoretical direction for the systematic design and development of transcriptional regulator-based biosensors and to aid researchers in enhancing the growth and productivity of microbial production strains.

Functional characterization and protein engineering of glycosyltransferase for 2"-O-xylosylation of ginsenoside Rg3

The limited abundance of xylosylated ginsenosides and the lack of efficient biocatalysts hinder their pharmacological exploration. This study identified a 2"-O-xylosyltransferase (PnUGT57) from Panax notoginseng that catalyzes the conversion of ginsenoside Rg3 to notoginsenoside ST4. Wild-type PnUGT57 preferred UDP-xylose over UDP-glucose and UDP-rhamnose and displayed limited thermostability (t1/2 = 6.73 h at 30 °C). To enhance UDP-xylose specificity, sequence-guided mutagenesis generated the C140A variant, which achieved remarkable UDP-xylose specificity (100 % conversion) with a 1.34-fold increase in catalytic efficiency while showing weak activity toward UDP-glucose (8.7 %) and UDP-rhamnose (5.2 %) activity. The F367A mutant possesses only xylosyltransferase activity but with reduced catalytic efficiency (0.3-fold of the WT). Molecular docking revealed that the enhanced UDP-xylose specificity in C140A and F367A resulted from the loss of key hydrogen bonding and hydrophobic interactions. To improve thermostability, computational design produced a triple mutant (P101S/L200C/G255D) with an 8.58-fold longer half-life (57.76 h), attributed to optimized surface charge distribution and improved hydration layer formation, as confirmed by molecular dynamics simulation. The combinatorial mutant C140A/P101S/L200C/G255D synergistically improved UDP-xylose specificity, thermostability, and catalytic efficiency, enabling efficient ST4 biosynthesis. This study elucidates the catalytic mechanism of PnUGT57 and presents engineered variants as promising biocatalysts for sustainable ginsenoside production.

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.

Improving CsOAC Activity in Saccharomyces cerevisiae for Directed Production of Olivetolic Acid through Rational Design

Olivetolic acid (OA) is an essential precursor in the cannabinoid biosynthesis. It is produced through a unique interaction between the two proteins, olivetol synthase (CsOLS) and olivetolic acid cyclase (CsOAC). When the OA biosynthesis is transferred to Saccharomyces cerevisiae, olivetol (OL) is produced as a side product, even with a high enhancement of copy number of CsOAC. In order to increase the OA titer while decreasing the OL titer in S. cerevisiae, rational design was applied to CsOAC using in silico approaches such as protein-ligand docking to find potential protein variants. In vivo screening and also testing different approaches for both proteins was applied to identify the best performing variants of CsOAC. Four variants were identified that gave the desired properties. The best CsOAC variant, G82 A/L92Y, resulted in a 1.7-fold increase in OA production and a shift in the ratio between the two products towards OA.

Advancing sustainable biotechnology through protein engineering

The push for industrial sustainability benefits from the use of enzymes as a replacement for traditional chemistry. Biological catalysts, especially those that have been engineered for increased activity, stability, or novel function, and are often greener than alternative chemical approaches. This Review highlights the role of engineered enzymes (and identifies directions for further engineering efforts) in the application areas of greenhouse gas sequestration, fuel production, bioremediation, and degradation of plastic wastes.

Stereodivergent Total Synthesis of Tacaman Alkaloids

This paper describes a concise, asymmetric and stereodivergent total synthesis of tacaman alkaloids. A key step in this synthesis is the biocatalytic Baeyer-Villiger oxidation of cyclohexanone, which was developed to produce seven-membered lactones and establish the required stereochemistry at the C14 position (92 % yield, 99 % ee, 500 mg scale). Cis- and trans-tetracyclic indoloquinolizidine scaffolds were rapidly synthesized through an acid-triggered, tunable acyl-Pictet-Spengler type cyclization cascade, serving as the pivotal reaction for building the alkaloid skeleton. Computational results revealed that hydrogen bonding was crucial in stabilizing intermediates and inducing different addition reactions during the acyl-Pictet-Spengler cyclization cascade. By strategically using these two reactions and the late-stage diversification of the functionalized indoloquinolizidine core, the asymmetric total syntheses of eight tacaman alkaloids were achieved. This study may potentially advance research related to the medicinal chemistry of tacaman alkaloids.

Semirational Design Strategy To Enhance the Thermostability and Catalytic Activity of Cytochrome P450 105D7 for the Degradation of the Pharmaceutically Active Compounds: Diclofenac

Pharmaceutically active compounds are an important category of emerging pollutants, and their biological transformation processes in the environment are crucial for understanding and evaluating the migration, transformation, and environmental fate of emerging pollutants. The cytochrome P450 105 enzyme family has been proven to play an important role in the degradation of exogenous environmental pollutants. However, its thermostability and catalytic activity still need to be improved to better adapt to complex environmental conditions. This work elucidates the key mechanisms and important residues of the degradation reaction through multiple computational strategies, establishes a mutation library, and obtains 21 single-point mutation designs. Experimental verification showed that 16 single mutants had enhanced thermostability, with the R89F and L197Y mutants showing the highest increases in thermostability at 135 and 119% relative to the wild-type enzyme, respectively. Additionally, as a result of the higher specific activity of D390Q, it was selected for combination mutagenesis, ultimately resulting in three combination mutants (R89F/L197Y, R89F/D390Q, and R89F/L197Y/D390Q) with enhanced thermostability and catalytic activity. This study provides a modification approach for constructing efficient enzyme variants through semirational design and can contribute to the development of control technologies for emerging pollutants.

Enhancing the catalytic efficiency of M32 carboxypeptidase by semi-rational design and its applications in food taste improvement

BACKGROUND

Carboxypeptidase is an exopeptidase that hydrolyzes amino acids at the C-terminal end of the peptide chain and has a wide range of applications in food. However, in industrial applications, the relatively low catalytic efficiency of carboxypeptidases is one of the main limiting factors for industrialization.

RESULTS

The study has enhanced the catalytic efficiency of Bacillus megaterium M32 carboxypeptidase (BmeCPM32) through semi-rational design. Firstly, the specific activity of the optimal mutant, BmeCPM32-M2, obtained through single-site mutagenesis and combinatorial mutagenesis, was 2.2-fold higher than that of the wild type (187.9 versus 417.8 U mg-1), and the catalytic efficiency was 2.9-fold higher (110.14 versus 325.75 s-1 mmol-1). Secondly, compared to the wild type, BmeCPM32-M2 exhibited a 1.8-fold increase in half-life at 60 °C, with no significant changes in its enzymatic properties (optimal pH, optimal temperature). Finally, BmeCPM32-M2 significantly increased the umami intensity of soy protein isolate hydrolysate by 55% and reduced bitterness by 83%, indicating its potential in developing tasty protein components.

CONCLUSION

Our research has revealed that the strategy based on protein sequence evolution and computational residue mutation energy led to an improved catalytic efficiency of BmeCPM32. Molecular dynamics simulations have revealed that a smaller substrate binding pocket and increased enzyme-substrate affinity are the reasons for the enhanced catalytic efficiency. Furthermore the number of hydrogen bonds and solvent and surface area may contribute to the improvement of thermostability. Finally, the de-bittering effect of BmeCPM32-M2 in soy protein isolate hydrolysate suggests its potential in developing palatable protein components. © 2024 Society of Chemical Industry.

Navigating the landscape of enzyme design: from molecular simulations to machine learning

Global environmental issues and sustainable development call for new technologies for fine chemical synthesis and waste valorization. Biocatalysis has attracted great attention as the alternative to the traditional organic synthesis. However, it is challenging to navigate the vast sequence space to identify those proteins with admirable biocatalytic functions. The recent development of deep-learning based structure prediction methods such as AlphaFold2 reinforced by different computational simulations or multiscale calculations has largely expanded the 3D structure databases and enabled structure-based design. While structure-based approaches shed light on site-specific enzyme engineering, they are not suitable for large-scale screening of potential biocatalysts. Effective utilization of big data using machine learning techniques opens up a new era for accelerated predictions. Here, we review the approaches and applications of structure-based and machine-learning guided enzyme design. We also provide our view on the challenges and perspectives on effectively employing enzyme design approaches integrating traditional molecular simulations and machine learning, and the importance of database construction and algorithm development in attaining predictive ML models to explore the sequence fitness landscape for the design of admirable biocatalysts.

Lipases for targeted industrial applications, focusing on the development of biotechnologically significant aspects: A comprehensive review of recent trends in protein engineering

Lipases are remarkable biocatalysts, adept at catalyzing the breakdown of diverse compounds into glycerol, fatty acids, and mono- and di-glycerides via hydrolysis. Beyond this, they facilitate esterification, transesterification, alcoholysis, acidolysis, and more, making them versatile in industrial applications. In industrial processes, lipases that exhibit high stability are favored as they can withstand harsh conditions. However, most native lipases are unable to endure adverse conditions, making them unsuitable for industrial use. Protein engineering proves to be a potent technology in the development of lipases that can function effectively under challenging conditions and fulfill criteria for various industrial processes. This review concentrated on new trends in protein engineering to enhance the diversity of lipase genes and employed in silico methods for predicting and comprehensively analyzing target mutations in lipases. Additionally, key molecular factors associated with industrial characteristics of lipases, including thermostability, solvent tolerance, catalytic activity, and substrate preference have been elucidated. The present review delved into how industrial traits can be enhanced through directed evolution (epPCR, gene shuffling), rational design (FRESCO, ASR), combined engineering strategies (i.e. CAST, ISM, and FRISM) as protein engineering methodologies in contexts of biodiesel production, food processing, and applications of detergent, pharmaceutics, and plastic degradation.

Engineering of Halide Methyltransferase BxHMT through Dynamic Cross-Correlation Network Analysis

Halide methyltransferases (HMTs) provide an effective way to regenerate S-adenosyl methionine (SAM) from S-adenosyl homocysteine and reactive electrophiles, such as methyl iodide (MeI) and methyl toluene sulfonate (MeOTs). As compared with MeI, the cost-effective unnatural substrate MeOTs can be accessed directly from cheap and abundant alcohols, but shows only limited reactivity in SAM production. In this study, we developed a dynamic cross-correlation network analysis (DCCNA) strategy for quickly identifying hot spots influencing the catalytic efficiency of the enzyme, and applied it to the evolution of HMT from Paraburkholderia xenovorans. Finally, the optimal mutant, M4 (V55T/C125S/L127T/L129P), exhibited remarkable improvement, with a specific activity of 4.08 U/mg towards MeOTs, representing an 82-fold increase as compared to the wild-type (WT) enzyme. Notably, M4 also demonstrated a positive impact on the catalytic ability with other methyl donors. The structural mechanism behind the enhanced enzyme activity was uncovered by molecular dynamics simulations. Our work not only contributes a promising biocatalyst for the regeneration of SAM, but also offers a strategy for efficient enzyme engineering.

The mechanistic insights into different aspects of promiscuity in metalloenzymes

Enzymes are nature's ultimate machinery to catalyze complex reactions. Though enzymes are evolved to catalyze specific reactions, they also show significant promiscuity in reactions and substrate selection. Metalloenzymes contain a metal ion or metal cofactor in their active site, which is crucial in their catalytic activity. Depending on the metal and its coordination environment, the metal ion or cofactor may function as a Lewis acid or base and a redox center and thus can catalyze a plethora of natural reactions. In fact, the versatility in the oxidation state of the metal ions provides metalloenzymes with a high level of catalytic adaptability and promiscuity. In this chapter, we discuss different aspects of promiscuity in metalloenzymes by using several recent experimental and theoretical works as case studies. We start our discussion by introducing the concept of promiscuity and then we delve into the mechanistic insight into promiscuity at the molecular level.

Improving the enzymatic activity and stability of N-carbamoyl hydrolase using deep learning approach

BACKGROUND

Optically active D-amino acids are widely used as intermediates in the synthesis of antibiotics, insecticides, and peptide hormones. Currently, the two-enzyme cascade reaction is the most efficient way to produce D-amino acids using enzymes DHdt and DCase, but DCase is susceptible to heat inactivation. Here, to enhance the enzymatic activity and thermal stability of DCase, a rational design software "Feitian" was developed based on kcat prediction using the deep learning approach.

RESULTS

According to empirical design and prediction of "Feitian" software, six single-point mutants with high kcat value were selected and successfully constructed by site-directed mutagenesis. Out of six, three mutants (Q4C, T212S, and A302C) showed higher enzymatic activity than the wild-type. Furthermore, the combined triple-point mutant DCase-M3 (Q4C/T212S/A302C) exhibited a 4.25-fold increase in activity (29.77 ± 4.52 U) and a 2.25-fold increase in thermal stability as compared to the wild-type, respectively. Through the whole-cell reaction, the high titer of D-HPG (2.57 ± 0.43 mM) was produced by the mutant Q4C/T212S/A302C, which was about 2.04-fold of the wild-type. Molecular dynamics simulation results showed that DCase-M3 significantly enhances the rigidity of the catalytic site and thus increases the activity of DCase-M3.

CONCLUSIONS

In this study, an efficient rational design software "Feitian" was successfully developed with a prediction accuracy of about 50% in enzymatic activity. A triple-point mutant DCase-M3 (Q4C/T212S/A302C) with enhanced enzymatic activity and thermostability was successfully obtained, which could be applied to the development of a fully enzymatic process for the industrial production of D-HPG.

Substrate scope expansion of 4-phenol oxidases by rational enzyme selection and sequence-function relations

Enzymes are natures' catalysts and will have a lasting impact on (organic) synthesis as they possess unchallenged regio- and stereo selectivity. On the downside, this high selectivity limits enzymes' substrate range and hampers their universal application. Therefore, substrate scope expansion of enzyme families by either modification of known biocatalysts or identification of new members is a key challenge in enzyme-driven catalysis. Here, we present a streamlined approach to rationally select enzymes with proposed functionalities from the ever-increasing amount of available sequence data. In a case study on 4-phenol oxidoreductases, eight enzymes of the oxidase branch were selected from 292 sequences on basis of the properties of first shell residues of the catalytic pocket, guided by the computational tool A2CA. Correlations between these residues and enzyme activity yielded robust sequence-function relations, which were exploited by site-saturation mutagenesis. Application of a peroxidase-independent oxidase screening resulted in 16 active enzyme variants which were up to 90-times more active than respective wildtype enzymes and up to 6-times more active than the best performing natural variants. The results were supported by kinetic experiments and structural models. The newly introduced amino acids confirmed the correlation studies which overall highlights the successful logic of the presented approach.

High-level production of chitinase by multi-strategy combination optimization in Bacillus licheniformis

In view of the extensive potential applications of chitinase (ChiA) in various fields such as agriculture, environmental protection, medicine, and biotechnology, the development of a high-yielding strain capable of producing chitinase with enhanced activity holds significant importance. The objective of this study was to utilize the extracellular chitinase from Bacillus thuringiensis as the target, and Bacillus licheniformis as the expression host to achieve heterologous expression of ChiA with enhanced activity. Initially, through structural analysis and molecular dynamics simulation, we identified key amino acids to improve the enzymatic performance of chitinase, and the specific activity of chitinase mutant D116N/E118N was 48% higher than that of the natural enzyme, with concomitant enhancements in thermostability and pH stability. Subsequently, the expression elements of ChiA(D116N/E118N) were screened and modified in Bacillus licheniformis, resulting in extracellular ChiA activity reached 89.31 U/mL. Further efforts involved the successful knockout of extracellular protease genes aprE, bprA and epr, along with the gene clusters involved in the synthesis of by-products such as bacitracin and lichenin from Bacillus licheniformis. This led to the development of a recombinant strain, DW2△abelA, which exhibited a remarkable improvement in chitinase activity, reaching 145.56 U/mL. To further improve chitinase activity, a chitinase expression frame was integrated into the genome of DW2△abelA, resulting in a significant increas to 180.26 U/mL. Optimization of fermentation conditions and medium components further boosted shake flask enzyme activity shake flask enzyme activity, achieving 200.28 U/mL, while scale-up fermentation experiments yielded an impressive enzyme activity of 338.79 U/mL. Through host genetic modification, expression optimization and fermentation optimization, a high-yielding ChiA strain was successfully constructed, which will provide a solid foundation for the extracellular production of ChiA.

Automated in vivo enzyme engineering accelerates biocatalyst optimization

Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.

Biosynthesis Progress of High-Energy-Density Liquid Fuels Derived from Terpenes

High-energy-density liquid fuels (HED fuels) are essential for volume-limited aerospace vehicles and could serve as energetic additives for conventional fuels. Terpene-derived HED biofuel is an important research field for green fuel synthesis. The direct extraction of terpenes from natural plants is environmentally unfriendly and costly. Designing efficient synthetic pathways in microorganisms to achieve high yields of terpenes shows great potential for the application of terpene-derived fuels. This review provides an overview of the current research progress of terpene-derived HED fuels, surveying terpene fuel properties and the current status of biosynthesis. Additionally, we systematically summarize the engineering strategies for biosynthesizing terpenes, including mining and engineering terpene synthases, optimizing metabolic pathways and cell-level optimization, such as the subcellular localization of terpene synthesis and adaptive evolution. This article will be helpful in providing insight into better developing terpene-derived HED fuels.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

A circuitous route for in vitro multi-enzyme cascade production of cytidine triphosphate to overcome the thermodynamic bottleneck

Cytidine triphosphate (CTP), as a substance involved in the metabolism of phospholipids, proteins and nucleic acids, has precise drug effects and is a direct precursor for the synthesis of drugs such as citicoline. In this study, we established an in vitro six-enzyme cascade system to generate CTP. To avoid thermodynamic bottlenecks, we employed a circuitous and two-stage reaction strategy. Using cytidine as the key substrate, the final product CTP is obtained via the deamination and uridine phosphorylation pathways, relying on the irreversible reaction of cytidine triphosphate synthase to catalyze the amination of uridine triphosphate. Several extremophilic microbial-derived deaminases were screened and characterized, and a suitable cytidine deaminase was selected to match the first-stage reaction conditions. In addition, directed evolution modification of the rate-limiting enzyme CTP synthetase in the pathway yielded a variant that successfully relieved the product feedback inhibition, along with a 1.7-fold increase in activity over the wild type. After optimizing the reaction conditions, we finally carried out the catalytic reaction at an initial cytidine concentration of 20 mM, and the yield of CTP exceeded 82% within 10.0 h.

Computationally guided bioengineering of the active site, substrate access pathway, and water channels of thermostable cytochrome P450, CYP175A1, for catalyzing the alkane hydroxylation reaction

Understanding structure-function relationships in proteins is pivotal in their development as industrial biocatalysts. In this regard, rational engineering of protein active site access pathways and various tunnels and channels plays a central role in designing competent enzymes with high stability and enhanced efficiency. Here, we report the rational evolution of a thermostable cytochrome P450, CYP175A1, to catalyze the C-H activation reaction of longer-chain alkanes. A strategy combining computational tools with experiments has shown that the substrate scope and enzymatic activity can be enhanced by rational engineering of certain important channels such as the substrate entry and water channels along with the active site of the enzyme. The evolved enzymes showed an improved catalytic rate for hexadecane hydroxylation with high regioselectivity. The Q67L/Y68F mutation showed binding of the substrate in the active site, water channel mutation L80F/V220T showed improved catalytic activity through the peroxide shunt pathway and substrate entry channel mutation W269F/I270A showed better substrate accessibility to the active pocket. All-atom MD simulations provided the rationale for the inactivity of the wild-type CYP175A1 for hexadecane hydroxylation and predicted the above hot-spot residues to enhance the activity. The reaction mechanism was studied by QM/MM calculations for enzyme-substrate complexes and reaction intermediates. Detailed thermal and thermodynamic stability of all the mutants were analyzed and the results showed that the evolved enzymes were thermally stable. The present strategy showed promising results, and insights gained from this work can be applied to the general enzymatic system to expand substrate scope and improve catalytic activity.

Sequence- and Structure-Based Mining of Thermostable D-Allulose 3-Epimerase and Computer-Guided Protein Engineering To Improve Enzyme Activity

D-Allulose, a functional sweetener, can be synthesized from fructose using D-allulose 3-epimerase (DAEase). Nevertheless, a majority of the reported DAEases have inadequate stability under harsh industrial reaction conditions, which greatly limits their practical applications. In this study, big data mining combined with a computer-guided free energy calculation strategy was employed to discover a novel DAEase with excellent thermostability. Consensus sequence analysis of flexible regions and comparison of binding energies after substrate docking were performed using phylogeny-guided big data analyses. TtDAE from Thermogutta terrifontis was the most thermostable among 358 candidate enzymes, with a half-life of 32 h at 70 °C. Subsequently, structure-guided virtual screening and a customized strategy based on a combinatorial active-site saturation test/iterative saturation mutagenesis were utilized to engineer TtDAE. Finally, the catalytic activity of the M4 variant (P105A/L14C/T63G/I65A) was increased by 5.12-fold. Steered molecular dynamics simulations indicated that M4 had an enlarged substrate-binding pocket, which enhanced the fit between the enzyme and the substrate. The approach presented here, combining DAEases mining with further rational modification, provides guidance for obtaining promising catalysts for industrial-scale production.

Adapting enzymes to improve their functionality in plants: why and how

Synthetic biology creates new metabolic processes and improves existing ones using engineered or natural enzymes. These enzymes are often sourced from cells that differ from those in the target plant organ with respect to, e.g. redox potential, effector levels, or proteostasis machinery. Non-native enzymes may thus need to be adapted to work well in their new plant context ('plantized') even if their specificity and kinetics in vitro are adequate. Hence there are two distinct ways in which an enzyme destined for use in plants can require improvement: In catalytic properties such as substrate and product specificity, kcat, and KM; and in general compatibility with the milieu of cells that express the enzyme. Continuous directed evolution systems can deliver both types of improvement and are so far the most broadly effective way to deliver the second type. Accordingly, in this review we provide a short account of continuous evolution methods, emphasizing the yeast OrthoRep system because of its suitability for plant applications. We then cover the down-to-earth and increasingly urgent issues of which enzymes and enzyme properties can - or cannot - be improved in theory, and which in practice are the best to target for crop improvement, i.e. those that are realistically improvable and important enough to warrant deploying continuous directed evolution. We take horticultural crops as examples because of the opportunities they present and to sharpen the focus.

EnzyHTP Computational Directed Evolution with Adaptive Resource Allocation

Directed evolution facilitates enzyme engineering via iterative rounds of mutagenesis. Despite the wide applications of high-throughput screening, building "smart libraries" to effectively identify beneficial variants remains a major challenge in the community. Here, we developed a new computational directed evolution protocol based on EnzyHTP, a software that we have previously reported to automate enzyme modeling. To enhance the throughput efficiency, we implemented an adaptive resource allocation strategy that dynamically allocates different types of computing resources (e.g., GPU/CPU) based on the specific need of an enzyme modeling subtask in the workflow. We implemented the strategy as a Python library and tested the library using fluoroacetate dehalogenase as a model enzyme. The results show that compared to fixed resource allocation where both CPU and GPU are on-call for use during the entire workflow, applying adaptive resource allocation can save 87% CPU hours and 14% GPU hours. Furthermore, we constructed a computational directed evolution protocol under the framework of adaptive resource allocation. The workflow was tested against two rounds of mutational screening in the directed evolution experiments of Kemp eliminase (KE07) with a total of 184 mutants. Using folding stability and electrostatic stabilization energy as computational readout, we identified all four experimentally observed target variants. Enabled by the workflow, the entire computation task (i.e., 18.4 μs MD and 18,400 QM single-point calculations) completes in 3 days of wall-clock time using ∼30 GPUs and ∼1000 CPUs.

Enabling technology and core theory of synthetic biology

Synthetic biology provides a new paradigm for life science research ("build to learn") and opens the future journey of biotechnology ("build to use"). Here, we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology, including synthesis and assembly of a genome, DNA storage, gene editing, molecular evolution and de novo design of function proteins, cell and gene circuit engineering, cell-free synthetic biology, artificial intelligence (AI)-aided synthetic biology, as well as biofoundries. We also introduce the concept of quantitative synthetic biology, which is guiding synthetic biology towards increased accuracy and predictability or the real rational design. We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

Improving the cellobiose hydrolysis activity of glucose-stimulating β-glucosidase Bgl2A

β-Glucosidases with high catalytic activity and glucose tolerant properties possess promising applications in lignocellulose-based industries. To obtain enzymes possessing these properties, a semi-rational strategy was employed to engineer the glucose-stimulating β-glucosidase Bgl2A for high cellobiose hydrolysis activity. A total of 18 mutants were constructed. A22S, V224D, and A22S/V224D exhibited high specific activities of 272.06, 237.60, and 239.29 U/mg toward cellobiose, which were 2.5- to 2.8-fold of Bgl2A. A22S, V224D, and A22S/V224D exhibited increased k_cat values, which were 2.7- to 3.1-fold of Bgl2A. A22S and V224D maintained glucose-stimulating property, whereas A22S/V224D lost it. Using 150 g/L cellobiose as the substrate, the amount of glucose produced by A22S was the highest, yielding 129.70 g/L glucose after 3 h reaction at 35 °C. The synergistic effects of the engineered enzymes with commercial cellulase on hydrolyzing cellulose were investigated. Supplemented with the commercial cellulase and A22S, the highest glucose amount of 23.30 g/L was yielded from cellulose with hydrolysis rate of 21.02 %. Given its high cellobiose hydrolysis activity and glucose-stimulating properties, A22S can be used as a component of enzyme cocktail to match mesophilic cellulases for efficient cellulose hydrolysis.

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.

Designing artificial pathways for improving chemical production

Metabolic engineering exploits manipulation of catalytic and regulatory elements to improve a specific function of the host cell, often the synthesis of interesting chemicals. Although naturally occurring pathways are significant resources for metabolic engineering, these pathways are frequently inefficient and suffer from a series of inherent drawbacks. Designing artificial pathways in a rational manner provides a promising alternative for chemicals production. However, the entry barrier of designing artificial pathway is relatively high, which requires researchers a comprehensive and deep understanding of physical, chemical and biological principles. On the other hand, the designed artificial pathways frequently suffer from low efficiencies, which impair their further applications in host cells. Here, we illustrate the concept and basic workflow of retrobiosynthesis in designing artificial pathways, as well as the most currently used methods including the knowledge- and computer-based approaches. Then, we discuss how to obtain desired enzymes for novel biochemistries, and how to trim the initially designed artificial pathways for further improving their functionalities. Finally, we summarize the current applications of artificial pathways from feedstocks utilization to various products synthesis, as well as our future perspectives on designing artificial pathways.

Alleviating the unwanted effects of oxidative stress on Aβ clearance: a review of related concepts and strategies for the development of computational modelling

Treatment for Alzheimer's disease (AD) can be more effective in the early stages. Although we do not completely understand the aetiology of the early stages of AD, potential pathological factors (amyloid beta [Aβ] and tau) and other co-factors have been identified as causes of AD, which may indicate some of the mechanism at work in the early stages of AD. Today, one of the primary techniques used to help delay or prevent AD in the early stages involves alleviating the unwanted effects of oxidative stress on Aβ clearance. 4-Hydroxynonenal (HNE), a product of lipid peroxidation caused by oxidative stress, plays a key role in the adduction of the degrading proteases. This HNE employs a mechanism which decreases catalytic activity. This process ultimately impairs Aβ clearance. The degradation of HNE-modified proteins helps to alleviate the unwanted effects of oxidative stress. Having a clear understanding of the mechanisms associated with the degradation of the HNE-modified proteins is essential for the development of strategies and for alleviating the unwanted effects of oxidative stress. The strategies which could be employed to decrease the effects of oxidative stress include enhancing antioxidant activity, as well as the use of nanozymes and/or specific inhibitors. One area which shows promise in reducing oxidative stress is protein design. However, more research is needed to improve the effectiveness and accuracy of this technique. This paper discusses the interplay of potential pathological factors and AD. In particular, it focuses on the effect of oxidative stress on the expression of the Aβ-degrading proteases through adduction of the degrading proteases caused by HNE. The paper also elucidates other strategies that can be used to alleviate the unwanted effects of oxidative stress on Aβ clearance. To improve the effectiveness and accuracy of protein design, we explain the application of quantum mechanical/molecular mechanical approach.

The community-function landscape of microbial consortia

Quantitatively linking the composition and function of microbial communities is a major aspiration of microbial ecology. Microbial community functions emerge from a complex web of molecular interactions between cells, which give rise to population-level interactions among strains and species. Incorporating this complexity into predictive models is highly challenging. Inspired by a similar problem in genetics of predicting quantitative phenotypes from genotypes, an ecological community-function (or structure-function) landscape could be defined that maps community composition and function. In this piece, we present an overview of our current understanding of these community landscapes, their uses, limitations, and open questions. We argue that exploiting the parallels between both landscapes could bring powerful predictive methodologies from evolution and genetics into ecology, providing a boost to our ability to engineer and optimize microbial consortia.

Strategies for tailoring pH performances of glycoside hydrolases

Glycoside hydrolases (GHs) exhibit high activity and stability under harsh conditions, such as high temperatures and extreme pHs, given their wide use in industrial biotechnology. However, strategies for improving the acidophilic and alkalophilic adaptations of GHs are poorly summarized due to the complexity of the mechanisms of these adaptations. This review not only highlights the adaptation mechanisms of acidophilic and alkalophilic GHs under extreme pH conditions, but also summarizes the recent advances in engineering the pH performances of GHs with a focus on four strategies of protein engineering, enzyme immobilization, chemical modification, and medium engineering (additives). The examples described here summarize the methods used in modulating the pH performances of GHs and indicate that methods integrated in different protein engineering techniques or methods are efficient to generate industrial biocatalysts with the desired pH performance and other adapted enzyme properties.

Biomanufacturing by In Vitro Biotransformation (ivBT) Using Purified Cascade Multi-enzymes

In vitro biotransformation (ivBT) refers to the use of an artificial biological reaction system that employs purified enzymes for the one-pot conversion of low-cost materials into biocommodities such as ethanol, organic acids, and amino acids. Unshackled from cell growth and metabolism, ivBT exhibits distinct advantages compared with metabolic engineering, including but not limited to high engineering flexibility, ease of operation, fast reaction rate, high product yields, and good scalability. These characteristics position ivBT as a promising next-generation biomanufacturing platform. Nevertheless, challenges persist in the enhancement of bulk enzyme preparation methods, the acquisition of enzymes with superior catalytic properties, and the development of sophisticated approaches for pathway design and system optimization. In alignment with the workflow of ivBT development, this chapter presents a systematic introduction to pathway design, enzyme mining and engineering, system construction, and system optimization. The chapter also proffers perspectives on ivBT development.

Enzymatic preparation and potential applications of agar oligosaccharides: a review

Oligosaccharides derived from agar, that is, agarooligosaccharides and neoagarooligosaccharides, have demonstrated various kinds of bioactivities which have been utilized in a variety of fields. Enzymatic hydrolysis is a feasible approach that principally allows for obtaining specific agar oligosaccharides in a sustainable way at an industrial scale. This review summarizes recent technologies employed to improve the properties of agarase. Additionally, the relationship between the degree of polymerization, bioactivities, and potential applications of agar-derived oligosaccharides for pharmaceutical, food, cosmetic, and agricultural industries are discussed. Engineered agarase exhibited general improvement of enzymatic performance, which is mostly achieved by truncation. Rational and semi-rational design assisted by computational methods present the latest strategy for agarase improvement with greatest potential to satisfy future industrial needs. Agarase immobilized on magnetic Fe3O4 nanoparticles via covalent bond formation showed characteristics well suited for industry. Additionally, albeit with the relationship between the degree of polymerization and versatile bioactivities like anti-oxidants, anti-inflammatory, anti-microbial agents, prebiotics and in skin care of agar-derived oligosaccharides are discussed here, further researches are still needed to unravel the complicated relationship between bioactivity and structure of the different oligosaccharides.

Expanding the Substrate Scope of a Bacterial Nucleotidyltransferase via Allosteric Mutations

Bacterial glycoconjugates, such as cell surface polysaccharides and glycoproteins, play important roles in cellular interactions and survival. Enzymes called nucleotidyltransferases use sugar-1-phosphates and nucleoside triphosphates (NTPs) to produce nucleoside diphosphate sugars (NDP-sugars), which serve as building blocks for most glycoconjugates. Research spanning several decades has shown that some bacterial nucleotidyltransferases have broad substrate tolerance and can be exploited to produce a variety of NDP-sugars in vitro. While these enzymes are known to be allosterically regulated by NDP-sugars and their fragments, much work has focused on the effect of active site mutations alone. Here, we show that rational mutations in the allosteric site of the nucleotidyltransferase RmlA lead to expanded substrate tolerance and improvements in catalytic activity that can be explained by subtle changes in quaternary structure and interactions with ligands. These observations will help inform future studies on the directed biosynthesis of diverse bacterial NDP-sugars and downstream glycoconjugates.

Cell-free production of the bifunctional glycoside hydrolase GH78 from Xylaria polymorpha

The ability to catalyze diverse reactions with relevance for chemical and pharmaceutical research and industry has led to an increasing interest in fungal enzymes. There is still an enormous potential considering the sheer amount of new enzymes from the huge diversity of fungi. Most of these fungal enzymes have not been characterized yet due to the lack of high throughput synthesis and analysis methods. This bottleneck could be overcome by means of cell-free protein synthesis. In this study, cell-free protein synthesis based on eukaryotic cell lysates was utilized to produce a functional glycoside hydrolase (GH78) from the soft-rot fungus Xylaria polymorpha (Ascomycota). The enzyme was successfully synthesized under different reaction conditions. We characterized its enzymatic activities and immobilized the protein via FLAG-Tag interaction. Alteration of several conditions including reaction temperature, template design and lysate supplementation had an influence on the activity of cell-free synthesized GH78. Consequently this led to a production of purified GH78 with a specific activity of 15.4 U mg^- 1. The results of this study may be foundational for future high throughput fungal enzyme screenings, including substrate spectra analysis and mutant screenings.

Insertions and deletions in protein evolution and engineering

Protein evolution or engineering studies are traditionally focused on amino acid substitutions and the way these contribute to fitness. Meanwhile, the insertion and deletion of amino acids is often overlooked, despite being one of the most common sources of genetic variation. Recent methodological advances and successful engineering stories have demonstrated that the time is ripe for greater emphasis on these mutations and their understudied effects. This review highlights the evolutionary importance and biotechnological relevance of insertions and deletions (indels). We provide a comprehensive overview of approaches that can be employed to include indels in random, (semi)-rational or computational protein engineering pipelines. Furthermore, we discuss the tolerance to indels at the structural level, address how domain indels can link the function of unrelated proteins, and feature studies that illustrate the surprising and intriguing potential of frameshift mutations.

Sequence and Structure-Guided Engineering of Urethanase from Agrobacterium tumefaciens d3 for Improved Catalytic Activity

The amidase from Agrobacterium tumefaciens d3 (AmdA) degrades the carcinogenic ethyl carbamate (EC) in alcoholic beverages. However, its limited catalytic activity hinders practical applications. Here, multiple sequence alignment was first used to predict single variants with improved activity. Afterward, AlphaFold 2 was applied to predict the three-dimensional structure of AmdA and 21 amino acids near the catalytic triad were randomized by saturation mutagenesis. Each of the mutation libraries was then screened, and the improved single variants were combined to obtain the best double variant I97L/G195A that showed a 3.1-fold increase in the urethanase activity and a 1.5-fold increase in ethanol tolerance. MD simulations revealed that the mutations shortened the distance between catalytic residues and the substrate and enhanced the occurrence of a critical hydrogen bond in the catalytic pocket. This study displayed a useful strategy to engineer an amidase for the improvement of urethanase activity, and the variant obtained provided a good candidate for applications in the food industry.

Catalytic roles, immobilization and management of recalcitrant environmental pollutants by laccases: Significance in sustainable green chemistry

We are facing a high risk of exposure to emerging contaminants and increasing environmental pollution with the concomitant growth of industries. Persistence of these pollutants is a major concern to the ecosystem. Laccases, also known as "green catalysts" are multi-copper oxidases which offers an eco-friendly solution for the degradation of these hazardous pollutants to less or non-toxic compounds. Although various other biological methods exist for the treatment of pollutants, the fact that laccases catalyze the oxidation of broad range of substrates in the presence of molecular oxygen without any additional cofactor and releases water as the by-product makes them exceptional. They have a good possibility of utilization in various industries, especially for the purpose of bioremediation. Besides this, they have also been used in medical/health care, food industry, bio-bleaching, wine stabilization, organic synthesis and biosensors. This review covers the catalytic behaviour of laccases, their immobilization strategies, potential applications in bioremediation of recalcitrant environmental pollutants and their engineering. It provides a comprehensive summary of most factors to consider while working with laccases in an industrial setting. It compares the benefits and drawbacks of the current techniques. Immobilization and mediators, two of the most significant aspects in working with laccases, have been meticulously discussed.

Experimental and computational studies of cellulases as bioethanol enzymes

Bioethanol industries and bioprocesses have many challenges that constantly impede commercialization of the end product. One of the bottlenecks in the bioethanol industry is the challenge of discovering highly efficient catalysts that can improve biomass conversion. The current promising bioethanol conversion catalysts are microorganism-based cellulolytic enzymes, but lack optimization for high bioethanol conversion, due to biological and other factors. A better understanding of molecular underpinnings of cellulolytic enzyme mechanisms and significant ways to improve them can accelerate the bioethanol commercial production process. In order to do this, experimental methods are the primary choice to evaluate and characterize cellulase’s properties, but they are time-consuming and expensive. A time-saving, complementary approach involves computational methods that evaluate the same properties and improves our atomistic-level understanding of enzymatic mechanism of action. Theoretical methods in many cases have proposed research routes for subsequent experimental testing and validation, reducing the overall research cost. Having a plethora of tools to evaluate cellulases and the yield of the enzymatic process will aid in planning more optimized experimental setups. Thus, there is a need to connect the computational evaluation methods with the experimental methods to overcome the bottlenecks in the bioethanol industry. This review discusses various experimental and computational methods and their use in evaluating the multiple properties of cellulases.

Improving Thermostability and Catalytic Activity of Glycosyltransferase From Panax ginseng by Semi-Rational Design for Rebaudioside D Synthesis

As a natural sweetener and sucrose substitute, the biosynthesis and application of steviol glycosides containing the component rebaudioside D have attracted worldwide attention. Here, a glycosyltransferase PgUGT from Panax ginseng was first reported for the biosynthesis of rebaudioside D. With the three-dimensional structures built by homology modeling and deep-learning–based modeling, PgUGT was semi-rationally designed by FireProt. After detecting 16 site-directed variants, eight of them were combined in a mutant Mut8 with both improved enzyme activity and thermostability. The enzyme activity of Mut8 was 3.2-fold higher than that of the wild type, with an increased optimum reaction temperature from 35 to 40°C. The activity of this mutant remained over 93% when incubated at 35°C for 2 h, which was 2.42 times higher than that of the wild type. Meanwhile, when the enzymes were incubated at 40°C, where the wild type was completely inactivated after 1 h, the residual activity of Mut8 retained 59.0% after 2 h. This study would provide a novel glycosyltransferase with great potential for the industrial production of rebaudioside D and other steviol glycosides.

Bioprospecting of microbial enzymes: current trends in industry and healthcare

Microbial enzymes have an indispensable role in producing foods, pharmaceuticals, and other commercial goods. Many novel enzymes have been reported from all domains of life, such as plants, microbes, and animals. Nonetheless, industrially desirable enzymes of microbial origin are limited. This review article discusses the classifications, applications, sources, and challenges of most demanded industrial enzymes such as pectinases, cellulase, lipase, and protease. In addition, the production of novel enzymes through protein engineering technologies such as directed evolution, rational, and de novo design, for the improvement of existing industrial enzymes is also explored. We have also explored the role of metagenomics, nanotechnology, OMICs, and machine learning approaches in the bioprospecting of novel enzymes. Overall, this review covers the basics of biocatalysts in industrial and healthcare applications and provides an overview of existing microbial enzyme optimization tools. KEY POINTS: • Microbial bioactive molecules are vital for therapeutic and industrial applications. • High-throughput OMIC is the most proficient approach for novel enzyme discovery. • Comprehensive databases and efficient machine learning models are the need of the hour to fast forward de novo enzyme design and discovery.

Engineering the 2-Oxoglutarate Dehydrogenase Complex to Understand Catalysis and Alter Substrate Recognition

The E. coli 2-oxoglutarate dehydrogenase complex (OGDHc) is a multienzyme complex in the tricarboxylic acid cycle, consisting of multiple copies of three components, 2-oxoglutarate dehydrogenase (E1o), dihydrolipoamide succinyltransferase (E2o) and dihydrolipoamide dehydrogenase (E3), which catalyze the formation of succinyl-CoA and NADH (+H+) from 2-oxoglutarate. This review summarizes applications of the site saturation mutagenesis (SSM) to engineer E. coli OGDHc with mechanistic and chemoenzymatic synthetic goals. First, E1o was engineered by creating SSM libraries at positions His260 and His298.Variants were identified that: (a) lead to acceptance of substrate analogues lacking the 5-carboxyl group and (b) performed carboligation reactions producing acetoin-like compounds with good enantioselectivity. Engineering the E2o catalytic (core) domain enabled (a) assignment of roles for pivotal residues involved in catalysis, (b) re-construction of the substrate-binding pocket to accept substrates other than succinyllysyldihydrolipoamide and (c) elucidation of the mechanism of trans-thioesterification to involve stabilization of a tetrahedral oxyanionic intermediate with hydrogen bonds by His375 and Asp374, rather than general acid–base catalysis which has been misunderstood for decades. The E. coli OGDHc is the first example of a 2-oxo acid dehydrogenase complex which was evolved to a 2-oxo aliphatic acid dehydrogenase complex by engineering two consecutive E1o and E2o components.

Directed Evolution of a Nonheme Diiron N-oxygenase AzoC for Improving Its Catalytic Efficiency toward Nitrogen Heterocycle Substrates

The azoxy compounds with an intriguing chemical bond [-N=N⁺(-O⁻)-] are known to have broad applications in many industries. Our previous work revealed that a nonheme diiron N-oxygenase AzoC catalyzed the oxidization of amino-group to its nitroso analogue in the formation of azoxy bond in azoxymycins biosynthesis. However, except for the reported pyridine alkaloid azoxy compounds, most azoxy bonds of nitrogen heterocycles have not been biosynthesized so far, and the substrate scope of AzoC is limited to p-aminobenzene-type compounds. Therefore, it is very meaningful to use AzoC to realize the biosynthesis of azoxy nitrogen heterocycles compounds. In this work, we further studied the catalytic potential of AzoC toward nitrogen heterocycle substrates including 5-aminopyrimidine and 5-aminopyridine compounds to form new azoxy compounds through directed evolution. We constructed a double mutant L101I/Q104R via molecular engineering with improved catalytic efficiency toward 2-methoxypyrimidin-5-amine. These mutations also proved to be beneficial for N-oxygenation of methyl 5-aminopyrimidine-2-carboxylate. The structural analysis showed that relatively shorter distance between the substrate and the diiron center and amino acid residues of the active center may be responsible for the improvement of catalytic efficiency in L101I/Q104R. Our results provide a molecular basis for broadening the AzoC catalytic activity and its application in the biosynthesis of azoxy six-membered nitrogen catenation compounds.

Single-Molecule Sampling of Dihydrofolate Reductase Shows Kinetic Pauses and an Endosteric Effect Linked to Catalysis

The ability to sample multiple reactions on the same single enzyme is important to link rare intermediates with catalysis and to unravel the role of conformational changes. Despite decades of efforts, however, the single-molecule characterization of nonfluorogenic enzymes during multiple catalytic turnovers has been elusive. Here, we show that nanopore currents allow sampling the dynamic exchange between five structural intermediates during E. coli dihydrofolate reductase (DHFR) catalysis. We found that an endosteric effect promotes the binding of the substrate to the enzyme with a specific hierarchy. The chemical step then switched the enzyme from the closed to the occluded conformation, which in turn promotes the release of the reduced cofactor NADP⁺. Unexpectedly, only a few reactive complexes lead to catalysis. Furthermore, second-long catalytic pauses were observed, possibly reflecting an off-path conformation generated during the reaction. Finally, the free energy from multiple cofactor binding events were required to release the product and switch DHFR back to the reactive conformer. This catalytic fueled concerted mechanism is likely to have evolved to improve the catalytic efficiency of DHFR under the high concentrations of NADP⁺ in E. coli and might be a general feature for complex enzymatic reactions where the binding and release of the products must be tightly controlled.

Microbial Cell Factory of Baccatin III Preparation in Escherichia coli by Increasing DBAT Thermostability and in vivo Acetyl-CoA Supply

Given the rapid development of genome mining in this decade, the substrate channel of paclitaxel might be identified in the near future. A robust microbial cell factory with gene dbat, encoding a key rate-limiting enzyme 10-deacetylbaccatin III-10-O-transferase (DBAT) in paclitaxel biosynthesis to synthesize the precursor baccatin III, will lay out a promising foundation for paclitaxel de novo synthesis. Here, we integrated gene dbat into the wild-type Escherichia coli BW25113 to construct strain BWD01. Yet, it was relatively unstable in baccatin III synthesis. Mutant gene dbat S189V with improved thermostability was screened out from a semi-rational mutation library of DBAT. When it was over-expressed in an engineered strain N05 with improved acetyl-CoA generation, combined with carbon source optimization of fermentation engineering, the production level of baccatin III was significantly increased. Using this combination, integrated strain N05S01 with mutant dbat S189V achieved a 10.50-fold increase in baccatin III production compared with original strain BWD01. Our findings suggest that the combination of protein engineering and metabolic engineering will become a promising strategy for paclitaxel production.

Computational Enzyme Design at Zymvol

Directed evolution is the most recognized methodology for enzyme engineering. The main drawback resides in its random nature and in the limited sequence exploration; both require screening of thousands (if not millions) of variants to achieve a target function. Computer-driven approaches can limit laboratorial screening to a few hundred candidates, enabling and accelerating the development of industrial enzymes. In this book chapter, the technology adopted at Zymvol is described. An overview of the current development and future directions in the company is also provided.

Significantly Improving the Thermostability and Catalytic Efficiency of Streptomyces mobaraenesis Transglutaminase through Combined Rational Design

Streptomyces mobaraenesis transglutaminase has been widely used in food processing. We here significantly improved the catalytic properties of S2P-S23V-Y24N-S199A-K294L (TGm1), a highly stabilized variant of the transglutaminase. First, a virtual proline scan was performed based on folding free energy changes to obtain TGm1 variants with enhanced thermostability. Second, the residues within 15 Å of Cys64 in the enzyme-substrate complex of TGm1 were subjected to virtual saturation mutagenesis to generate the variants with reduced binding free energy and increased activity. After combining the favorable mutations, we obtained the variant FRAPD-TGm1-E28T-A265P-A287P (FRAPD-TGm2), exhibiting 66.9 min of half-life at 60 °C (t_1/2(60 °C)), 67.8 °C of melting temperature (T_m), and 71.8 U/mg of specific activity, which are 2-fold, 2.6 °C, and 43.8% higher than those of FRAPD-TGm1, respectively. At last, to increase the surface negative net charge of FRAPD-TGm2, we introduced the mutations N96E-S144E-N163D-R183E-R208E-K325E, yielding FRAPD-TGm3. The latter's t_1/2(60 °C), T_m, and specific activity were 122.9 min, 68.6 °C, and 83.7 U/mg, which are 83.8%, 0.8 °C, and 16.6% higher than the former, respectively. FRAPD-TGm3 is thus a robust candidate for transglutaminase application.

Enabling biocatalysis in high-concentration organic cosolvent by enzyme gate engineering

Biocatalysis in high-concentration organic solvents (OSs) offers many advantages, but realizing this process remains a huge challenge. An R-selective ω-amine transaminase variant (AcATA_M2 ) exhibited high activity toward 50 g/L pro-sitagliptin ketone 1-[1-piperidinyl]-4-[2,4,5-trifluorophenyl]-1,3-butanedione (PTfpB). However, AcATA_M2 displayed unsatisfactory organic-cosolvent resistance against high-concentration dimethyl sulfoxide (DMSO), which is required to enhance the solubility of the hydrophobic substrate PTfpB. Located in the substrate-binding tunnel, enzyme gates are structural elements that undergo reversible conformational transitions, thus affecting the accessibility of the binding pocket to solvent molecules. Depending on the conformation of the enzyme gates, one can define an open or closed conformation on which the enzyme activity in OSs may depend. To enhance the DMSO resistance of AcATA_M2 , we identified the beneficial residues at the "enzyme gate" region via computational analysis, alanine scanning, and site-saturation mutagenesis. Two beneficial variants, namely, AcATA_M2 ^F56D and AcATA_M2 ^F56V , not only displayed improved enzyme activity but also exhibited enhanced DMSO resistance (the half-life value increased from 25.71 to 42.49 h under 60% DMSO). Molecular dynamic simulations revealed that the increase in DMSO resistance was mainly caused by the decrease in the number of DMSO molecules in the substrate-binding pocket. Moreover, in the kilogram-scale experiment, the conversion of 80 g/L substrate was increased from 50% (AcATA_M2 ) to 85% (M2^F56D in 40% DMSO) with a high e.e. of >99% within 24 h.