Recent advances in rational approaches for enzyme engineering

Development of a HPLC-MS/MS Method to Assess the Pharmacokinetics and Tumour Distribution of the Dimethylarginine Dimethylaminohydrolase 1 Inhibitors ZST316 and L-257 in a Xenograft Model of Triple-Negative Breast Cancer in Mice

We describe the development and validation of an HPLC-MS/MS method to assess the pharmacokinetics and tumour distribution of ZST316, an arginine analogue with inhibitory activity towards dimethylarginine dimethylaminohydrolase 1 (DDAH1) and vasculogenic mimicry, and its active metabolite L-257 in a xenograft model of triple-negative breast cancer (TNBC). The method proved to be reproducible, precise, and highly accurate for the measurement of both compounds in plasma and tumour tissue following acute and chronic (five days) intraperitoneal administration of ZST316 (30 mg/Kg daily) in six-week-old severe combined immunodeficiency disease (SCID) mice inoculated with MDA-MB-231 TNBC cells. ZST316 was detected in tumour tissue and plasma after 1 h (6.47 and 9.01 μM, respectively) and 24 h (0.13 and 0.16 μM, respectively) following acute administration, without accumulation during chronic treatment. Similarly, the metabolite L-257 was found in tumour tissue and plasma after 1 h (15.06 and 8.72 μM, respectively) and 24 h (0.17 and 0.17 μM, respectively) following acute administration of ZST316, without accumulation during chronic treatment. The half-life after acute and chronic treatment ranged between 4.4-7.1 h (plasma) and 4.5-5.0 h (tumour) for ZST316, and 4.2-5.3 h (plasma) and 3.6-4.9 h (tumour) for L-257. The results of our study demonstrate the (a) capacity to accurately measure ZST316 and L-257 concentrations in plasma and tumour tissue in mice using the newly developed HPLC-MS/MS method, (b) rapid conversion of ZST316 into L-257, (c) good intra-tumour penetration of both compounds, and (d) lack of accumulation of both ZST316 and L-257 in plasma and tumour tissue during chronic administration. Compared to a previous method developed by our group to investigate ZST316 in plasma, the main advantages of the new method include a wider range of linearity which reduces the need for dilutions and the combined assessment of ZST316 and L-257 in plasma and tumour tissue which limits the required amount of matrix. The new HPLC-MS/MS method is useful to investigate the in vivo effects of ZST316 and L-257 on vasculogenic mimicry, tumour mass, and metastatic burden in xenograft models of TNBC.

Biosensor-guided discovery and engineering of metabolic enzymes

A variety of chemicals have been produced through metabolic engineering approaches, and enhancing biosynthesis performance can be achieved by using enzymes with high catalytic efficiency. Accordingly, a number of efforts have been made to discover enzymes in nature for various applications. In addition, enzyme engineering approaches have been attempted to suit specific industrial purposes. However, a significant challenge in enzyme discovery and engineering is the efficient screening of enzymes with the desired phenotype from extensive enzyme libraries. To overcome this bottleneck, genetically encoded biosensors have been developed to specifically detect target molecules produced by enzyme activity at the intracellular level. Especially, the biosensors facilitate high-throughput screening (HTS) of targeted enzymes, expanding enzyme discovery and engineering strategies with advances in systems and synthetic biology. This review examines biosensor-guided HTS systems and highlights studies that have utilized these tools to discover enzymes in diverse areas and engineer enzymes to enhance their properties, such as catalytic efficiency, specificity, and stability.

Enhancing luciferase activity and stability through generative modeling of natural enzyme sequences

The availability of natural protein sequences synergized with generative AI provides new paradigms to engineer enzymes. Although active enzyme variants with numerous mutations have been designed using generative models, their performance often falls short of their wild type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze Renilla luciferase (RLuc) homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate to improve either luciferase activity or stability of designed single mutants is ~50%. This finding highlights nature's ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in RLuc toward emitting blue light that holds advantages in terms of water penetration compared to other light spectra. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.

Expression and Biological Evaluation of an Engineered Recombinant L-asparaginase Designed by In Silico Method Based on Sequence of the Enzyme from Escherichia coli

Purpose

Medical usage of L-asparaginase (ASNase), the first-line of acute lymphoblastic leukemia treatment, is linked to allergic responses and toxicities, which necessitates the development of new bio-better ASNases. The aim of the current study was in silico design of a novel ASNase with predicted improved enzymatic properties using strategies encompassing sequence-function analysis of known ASNase mutants. Additionally, current study aimed to show that the new enzyme is active.

Methods

Based on 21 experimentally reported mutations for ASNase, a virtual library of mutated enzymes with all 7546 possible combinations of up to 4 mutations was generated. Three-dimensional models of proposed mutant enzymes were built and their in silico stabilities were calculated. The most promising mutant was selected for preparing a genetic construct suitable for expression of the designed ASNase in bacterial cells.

Results

Computational study predicted that Y176F/S241C double mutation of Escherichia coli ASNase may increase its folding stability. The designed ASNase was expressed in two different E. coli strains (Origami B(DE3) and BL21(DE3)pLysS) and then the soluble fractions prepared from the cell lysates of the host cells were used in enzyme activity assay. Results showed that enzyme activity of soluble fraction from Origami (95.4 ± 7.5 IU/0.1 mL) was four times higher than that of soluble fraction from pLysS (25.8 ± 2.5 IU/0.1 mL).

Conclusion

A novel functional double mutant ASNase with predicted improved enzymatic properties was designed and produced in E. coli. The results of the current study suggest a great commercial potential for the identified enzyme in pharmaceutical and industrial applications.

Enhancing Luciferase Activity and Stability through Generative Modeling of Natural Enzyme Sequences

The availability of natural protein sequences synergized with generative artificial intelligence (AI) provides new paradigms to create enzymes. Although active enzyme variants with numerous mutations have been produced using generative models, their performance often falls short compared to their wild-type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze Renilla luciferase homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate of designed single mutants is ~50% to improve either luciferase activity or stability. These finding highlights nature's ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in Renilla luciferase towards emitting blue light that holds advantages in terms of water penetration compared to other light spectrum. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.

Analyzing Current Trends and Possible Strategies to Improve Sucrose Isomerases' Thermostability

Due to their ability to produce isomaltulose, sucrose isomerases are enzymes that have caught the attention of researchers and entrepreneurs since the 1950s. However, their low activity and stability at temperatures above 40 °C have been a bottleneck for their industrial application. Specifically, the instability of these enzymes has been a challenge when it comes to their use for the synthesis and manufacturing of chemicals on a practical scale. This is because industrial processes often require biocatalysts that can withstand harsh reaction conditions, like high temperatures. Since the 1980s, there have been significant advancements in the thermal stabilization engineering of enzymes. Based on the literature from the past few decades and the latest achievements in protein engineering, this article systematically describes the strategies used to enhance the thermal stability of sucrose isomerases. Additionally, from a theoretical perspective, we discuss other potential mechanisms that could be used for this purpose.

Enabling Broader Adoption of Biocatalysis in Organic Chemistry

Biocatalysis is becoming an increasingly impactful method in contemporary synthetic chemistry for target molecule synthesis. The selectivity imparted by enzymes has been leveraged to complete previously intractable chemical transformations and improve synthetic routes toward complex molecules. However, the implementation of biocatalysis in mainstream organic chemistry has been gradual to this point. This is partly due to a set of historical and technological barriers that have prevented chemists from using biocatalysis as a synthetic tool with utility that parallels alternative modes of catalysis. In this Perspective, we discuss these barriers and how they have hindered the adoption of enzyme catalysts into synthetic strategies. We also summarize tools and resources that already enable organic chemists to use biocatalysts. Furthermore, we discuss ways to further lower the barriers for the adoption of biocatalysis by the broader synthetic organic chemistry community through the dissemination of resources, demystifying biocatalytic reactions, and increasing collaboration across the field.

Recent Advances in Applications of Oxidases and Peroxidases Polymer-Based Enzyme Biocatalysts in Sensing and Wastewater Treatment: A Review

Oxidase and peroxidase enzymes have attracted attention in various biotechnological industries due to their ease of synthesis, wide range of applications, and operation under mild conditions. Their applicability, however, is limited by their poor stability in harsher conditions and their non-reusability. As a result, several approaches such as enzyme engineering, medium engineering, and enzyme immobilization have been used to improve the enzyme properties. Several materials have been used as supports for these enzymes to increase their stability and reusability. This review focusses on the immobilization of oxidase and peroxidase enzymes on metal and metal oxide nanoparticle-polymer composite supports and the different methods used to achieve the immobilization. The application of the enzyme-metal/metal oxide-polymer biocatalysts in biosensing of hydrogen peroxide, glucose, pesticides, and herbicides as well as blood components such as cholesterol, urea, dopamine, and xanthine have been extensively reviewed. The application of the biocatalysts in wastewater treatment through degradation of dyes, pesticides, and other organic compounds has also been discussed.

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.

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

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

A Semi-Rational Mutagenesis Approach For Improved Substrate Activity Of Microbial Transglutaminase

A higher specific activity of microbial transglutaminase (mTGase) is desirable for a broad range of applications ranging from food industry to biotechnology. Three-dimensional docking simulation of mTGase revealed that residues V65, W69, and Y75 were critical for substrate recognition. A semi-rational mutagenesis approach was applied to each residue to generate three separate mini mutant libraries. A high-throughput screening process identified five mutants that demonstrated improved specific activities than the wild type (WT) mTGase were isolated from the Y75 mini mutant library. Mutant Y75L showed approximately 60% increment in specific activity and improved substrate specificity. Conjugation of two heterologous single-chain fragment variable clones to generate a diabody with mutant Y75L was successfully performed and validated. This work demonstrates the successful application of semi-rational mutagenesis coupled with a high-throughput screening approach to identify mTGase mutants with improved specific activities and specificities which are beneficial for protein-protein conjugation.

Rational design of enzyme activity and enantioselectivity

The strategy of rational design to engineer enzymes is to predict the potential mutants based on the understanding of the relationships between protein structure and function, and subsequently introduce the mutations using the site-directed mutagenesis. Rational design methods are universal, relatively fast and have the potential to be developed into algorithms that can quantitatively predict the performance of the designed sequences. Compared to the protein stability, it was more challenging to design an enzyme with improved activity or selectivity, due to the complexity of enzyme molecular structure and inadequate understanding of the relationships between enzyme structures and functions. However, with the development of computational force, advanced algorithm and a deeper understanding of enzyme catalytic mechanisms, rational design could significantly simplify the process of engineering enzyme functions and the number of studies applying rational design strategy has been increasing. Here, we reviewed the recent advances of applying the rational design strategy to engineer enzyme functions including activity and enantioselectivity. Five strategies including multiple sequence alignment, strategy based on steric hindrance, strategy based on remodeling interaction network, strategy based on dynamics modification and computational protein design are discussed and the successful cases using these strategies are introduced.

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.

Single-sequence protein structure prediction using a language model and deep learning

AlphaFold2 and related computational systems predict protein structure using deep learning and co-evolutionary relationships encoded in multiple sequence alignments (MSAs). Despite high prediction accuracy achieved by these systems, challenges remain in (1) prediction of orphan and rapidly evolving proteins for which an MSA cannot be generated; (2) rapid exploration of designed structures; and (3) understanding the rules governing spontaneous polypeptide folding in solution. Here we report development of an end-to-end differentiable recurrent geometric network (RGN) that uses a protein language model (AminoBERT) to learn latent structural information from unaligned proteins. A linked geometric module compactly represents Cα backbone geometry in a translationally and rotationally invariant way. On average, RGN2 outperforms AlphaFold2 and RoseTTAFold on orphan proteins and classes of designed proteins while achieving up to a 106-fold reduction in compute time. These findings demonstrate the practical and theoretical strengths of protein language models relative to MSAs in structure prediction.

Engineered microbes as effective tools for the remediation of polyaromatic aromatic hydrocarbons and heavy metals

Heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) have become a major concern to human health and the environment due to rapid industrialization and urbanization. Traditional treatment measures for removing toxic substances from the environment have largely failed, and thus development and advancement in newer remediation techniques are of utmost importance. Rising environmental pollution with HMs and PAHs prompted the research on microbes and the development of genetically engineered microbes (GEMs) for reducing pollution via the bioremediation process. The enzymes produced from a variety of microbes can effectively treat a range of pollutants, but evolutionary trends revealed that various emerging pollutants are resistant to microbial or enzymatic degradation. Naturally, existing microbes can be engineered using various techniques including, gene engineering, directed evolution, protein engineering, media engineering, strain engineering, cell wall modifications, rationale hybrid design, and encapsulation or immobilization process. The immobilization of microbes and enzymes using a variety of nanomaterials, membranes, and supports with high specificity toward the emerging pollutants is also an effective strategy to capture and treat the pollutants. The current review focuses on successful bioremediation techniques and approaches that make use of GEMs or engineered enzymes. Such engineered microbes are more potent than natural strains and have greater degradative capacities, as well as rapid adaptation to various pollutants as substrates or co-metabolizers. The future for the implementation of genetic engineering to produce such organisms for the benefit of the environment andpublic health is indeed long and valuable.

Carbonic anhydrase to boost CO2 sequestration: Improving carbon capture utilization and storage (CCUS)

CO₂ Capture Utilization and Storage (CCUS) is a fundamental strategy to mitigate climate change, and carbon sequestration, through absorption, can be one of the solutions to achieving this goal. In nature, carbonic anhydrase (CA) catalyzes the CO₂ hydration to bicarbonates. Targeting the development of novel biotechnological routes which can compete with traditional CO₂ absorption methods, CA utilization has presented a potential to expand as a promising catalyst for CCUS applications. Driven by this feature, the search for novel CAs as biocatalysts and the utilization of enzyme improvement techniques, such as protein engineering and immobilization methods, has resulted in suitable variants able to catalyze CO₂ absorption at relevant industrial conditions. Limitations related to enzyme recovery and recyclability are still a concern in the field, affecting cost efficiency. Under different absorption approaches, CA enhances both kinetics and CO₂ absorption yields, besides reduced energy consumption. However, efforts directed to process optimization and demonstrative plants are still limited. A recent topic with great potential for development is the CA utilization in accelerated weathering, where industrial residues could be re-purposed towards becoming carbon sequestrating agents. Furthermore, research of new solvents has identified potential candidates for integration with CA in CO₂ capture, and through techno-economic assessments, CA can be a path to increase the competitiveness of alternative CO₂ absorption systems, offering lower environmental costs. This review provides a favorable scenario combining the enzyme and CO₂ capture, with possibilities in reaching an industrial-like stage in the future.

Tuning the Catalytic Activity of Synthetic Enzyme KE15 with DNA

Efficiency improvement of synthetic enzymes through scaffold modifications suffers from limitations in terms of effectiveness, cost, and potential devastating consequences for protein structural stability. Here, we propose an alternative to scaffold modification, within electrostatic preorganization theory, where the enzyme's greater environment is designed to support the evolution of the reaction in the active site. We demonstrate the feasibility of such an approach by placing a (polar) DNA fragment in the surroundings of the Kemp eliminase enzyme KE15 (structure from Houk's group) and computing the resulting change in catalytic activity. We find that the introduction of a DNA fragment magnifies the contribution of protein residues to the stabilization of the transition state, estimated from electric field calculations with polarizable molecular dynamics. Our randomly generated test systems reveal a 2.0 kcal/mol reduction in activation energy, suggesting that even more significant catalytic improvements could be made by optimizing DNA size, sequence, and orientation with respect to the enzyme, validating our approach.

Functional and Structural Roles of the Dimer Interface in the Activity and Stability of Clostridium butyricum 1,3-Propanediol Oxidoreductase

Biosynthesis of 1,3-propanediol (1,3-PD) by 1,3-propanediol oxidoreductase (PDOR) is often limited by the stability issues. To address this issue, the goal of the present study was to engineer the Clostridium butyricum PDOR dimeric interface. The interface exists between the chains and plays a role in the synthesis of 1,3-PD, which is hindered by the increased temperature and pH. Herein, we engineered PDOR by HotSpot Wizard 3.0 and molecular dynamics simulations, improving its thermal stability, pH tolerance, and catalytic properties with respect to the wild-type PDOR activity at 37 °C. Compared to the activity of the wild-type PDOR, the N298C mutant showed 0.5-fold greater activity at pH 8.0, while the P299E mutant showed significantly increased activity of over five fold at pH 4.0. Further structural comparisons between the wild-type and P299E mutant revealed that the extraordinary stability of the P299E mutant could be due to the formation of additional hydrogen bonds and salt bridges. The N298C mutant also exhibits thermal stability at a broad range of temperature at pH 8 with respect to wild-type PDOR and other mutants. The molecular dynamics simulations revealed that stability profiles of P299E mutants at pH 4.0 are attributed to identical root mean square deviation values and stable conformations in the motif region present in the dimer interface of the enzyme. These findings suggest that the dimer interface motifs are essential for the compactness and stability of the PDOR enzyme; therefore, engineering the PDOR using a structure-guided approach could aid in improving its activity and stability under various physiological conditions (pH and temperature).

Effect of Binding Modules Fused to Cutinase on the Enzymatic Synthesis of Polyesters

In relation to the development of environmentally-friendly processing technologies for the continuously growing market of plastics, enzymes play an important role as green and sustainable biocatalysts. The present study reports the use of heterogeneous immobilized biocatalysts in solvent-free systems for the synthesis of aliphatic oligoesters with Mws and monomer conversions up to 1500 Da and 74%, respectively. To improve the accessibility of hydrophilic and hydrophobic substrates to the surface of the biocatalyst and improve the reaction kinetic and the chain elongation, two different binding modules were fused on the surface of cutinase 1 from Thermobifida cellulosilytica. The fusion enzymes were successfully immobilized (>99% of bound protein) via covalent bonding onto epoxy-activated beads. To the best of our knowledge, this is the first example where fused enzymes are used to catalyze transesterification reactions for polymer synthesis purposes.

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.

Synthetic Biology of Thermophiles: Taking Bioengineering to the Extremes?

Synthetic biology applications rely on a well-characterized set of microbial strains, with an established toolbox of molecular biology methods for their genetic manipulation. Since there are no thermophiles with such attributes, most biotechnology and synthetic biology studies use organisms that grow in the mesophilic temperature range. As a result, thermophiles, a heterogenous group of microbes that thrive at high (>50 °C) temperatures, are largely overlooked, with respect to their biotechnological potential, even though they share several favorable traits. Thermophilic bacteria tend to grow at higher rates compared to their mesophilic counterparts, while their growth has lower cooling requirements and is less prone to contamination. Over the last few years, there has been renewed interest in developing tools and methods for thermophile bioengineering. In this perspective, we explain why it is a good idea to invest time and effort into developing a thermophilic synthetic biology direction, which is the state of the art, and why we think that the implementation of a thermophilic synthetic biology platform—a thermochassis—will take synthetic biology to the extremes.

Tailored enzymes as next-generation food-packaging tools

Enzymes have the potential for biotransformation in the food industry. Engineering tools can be used to develop tailored enzymes for food-packaging systems that perform well and retain their activity under adverse conditions. Consequently, novel tailored enzymes have been produced to improve or include new and useful characteristics for intelligent food-packaging systems. This review discusses the protein-engineering tools applied to create new functionality in food-packaging enzymes. The challenges in applications and anticipated directions for future developments are also highlighted. The development and discovery of tailored enzymes for smart food packaging is a promising way to ensure safe and high-quality food products.

A Review of Advanced Molecular Engineering Approaches to Enhance the Thermostability of Enzyme Breakers: From Prospective of Upstream Oil and Gas Industry

During the fracture stimulation of oil and gas wells, fracturing fluids are used to create fractures and transport the proppant into the fractured reservoirs. The fracturing fluid viscosity is responsible for proppant suspension, the viscosity can be increased through the incorporation of guar polymer and cross-linkers. After the fracturing operation, the fluid viscosity is decreased by breakers for efficient oil and gas recovery. Different types of enzyme breakers have been engineered and employed to reduce the fracturing fluid′s viscosity, but thermal stability remains the major constraint for the use of enzymes. The latest enzyme engineering approaches such as direct evolution and rational design, have great potential to increase the enzyme breakers’ thermostability against high temperatures of reservoirs. In this review article, we have reviewed recently advanced enzyme molecular engineering technologies and how these strategies could be used to enhance the thermostability of enzyme breakers in the upstream oil and gas industry.

Residue-Specific Incorporation of the Non-Canonical Amino Acid Norleucine Improves Lipase Activity on Synthetic Polyesters

Environmentally friendly functionalization and recycling processes for synthetic polymers have recently gained momentum, and enzymes play a central role in these procedures. However, natural enzymes must be engineered to accept synthetic polymers as substrates. To enhance the activity on synthetic polyesters, the canonical amino acid methionine in Thermoanaerobacter thermohydrosulfuricus lipase (TTL) was exchanged by the residue-specific incorporation method for the more hydrophobic non-canonical norleucine (Nle). Strutural modelling of TTL revealed that residues Met-114 and Met-142 are in close vicinity of the active site and their replacement by the norleucine could modulate the catalytic activity of the enzyme. Indeed, hydrolysis of the polyethylene terephthalate model substrate by the Nle variant resulted in significantly higher amounts of release products than the Met variant. A similar trend was observed for an ionic phthalic polyester containing a short alkyl diol (C5). Interestingly, a 50% increased activity was found for TTL [Nle] towards ionic phthalic polyesters containing different ether diols compared to the parent enzyme TTL [Met]. These findings clearly demonstrate the high potential of non-canonical amino acids for enzyme engineering.

Enhancing thermostabilization of a newly discovered α-amylase from Bacillus cereus GL96 by combining computer-aided directed evolution and site-directed mutagenesis

This study has described the characterization of a new a-amylase from the recently isolated Bacillus cereus GL96. Subsequently, an in-silico approach was taken into account to redesign the enzyme to meet higher thermal stability. Finally, the engineered enzyme was constructed experimentally using side-directed mutagenesis (SDM) and characterized accordingly. The enzyme was stable over pH 4-11, with the highest activity at 9.5. The temperature profile of the wild-type enzyme showed optimum activity at 50 °C plus 40% of stability at temperatures up to 70 °C. The in-silico result was indicated D162W, D162R, and D162K as the three stabilizing mutations. Among them, D162K showed better results, especially in the molecular dynamics simulation, and therefore, it was constructed by SDM. This variant was shown 5 °C higher optimum temperature (55 °C) with increasing activity than the native enzyme. In addition, it was significantly more stable than the native form. For example, while the latter almost wholly lost its function at a temperature above 70 °C, the D162K can retain more than 40% of its initial activity up to 80 °C. Considering the promising properties that the mutant enzyme showed, it can be considered for further investigation to meet the industrial requirement completely.

Challenges and Recent Advances in Enzyme-Mediated Wastewater Remediation-A Review

Different classes of artificial pollutants, collectively called emerging pollutants, are detected in various water bodies, including lakes, rivers, and seas. Multiple studies have shown the devastating effects these emerging pollutants can have on human and aquatic life. The main reason for these emerging pollutants in the aquatic environment is their incomplete removal in the existing wastewater treatment plants (WWTPs). Several additional treatments that could potentially supplement existing WWTPs to eliminate these pollutants include a range of physicochemical and biological methods. The use of enzymes, specifically, oxidoreductases, are increasingly being studied for their ability to degrade different classes of organic compounds. These enzymes have been immobilized on different supports to promote their adoption as a cost-effective and recyclable remediation approach. Unfortunately, some of these techniques have shown a negative effect on the enzyme, including denaturation and loss of catalytic activity. This review focuses on the major challenges facing researchers working on the immobilization of peroxidases and the recent progress that has been made in this area. It focuses on four major areas: (1) stability of enzymes upon immobilization, enzyme engineering, and evolution; (2) recyclability and reusability, including immobilization on membranes and solid supports; (3) cost associated with enzyme-based remediation; and (4) scaling-up and bioreactors.

Development of aldolase-based catalysts for the synthesis of organic chemicals

Aldol chemicals are synthesized by condensation reactions between the carbon units of ketones and aldehydes using aldolases. The efficient synthesis of diverse organic chemicals requires intrinsic modification of aldolases via engineering and design, as well as extrinsic modification through immobilization or combination with other catalysts. This review describes the development of aldolases, including their engineering and design, and the selection of desired aldolases using high-throughput screening, to enhance their catalytic properties and perform novel reactions. Aldolase-containing catalysts, which catalyze the aldol reaction combined with other enzymatic and/or chemical reactions, can efficiently synthesize diverse complex organic chemicals using inexpensive and simple materials as substrates. We also discuss the current challenges and emerging solutions for aldolase-based catalysts.

New Trends in Bioremediation Technologies Toward Environment-Friendly Society: A Mini-Review

Today's environmental balance has been compromised by the unreasonable and sometimes dangerous actions committed by humans to maintain their dominance over the Earth's natural resources. As a result, oceans are contaminated by the different types of plastic trash, crude oil coming from mismanagement of transporting ships spilling it in the water, and air pollution due to increasing production of greenhouse gases, such as CO₂ and CH₄ etc., into the atmosphere. The lands, agricultural fields, and groundwater are also contaminated by the infamous chemicals viz., polycyclic aromatic hydrocarbons, pyrethroids pesticides, bisphenol-A, and dioxanes. Therefore, bioremediation might function as a convenient alternative to restore a clean environment. However, at present, the majority of bioremediation reports are limited to the natural capabilities of microbial enzymes. Synthetic biology with uncompromised supervision of ethical standards could help to outsmart nature's engineering, such as the CETCH cycle for improved CO₂ fixation. Additionally, a blend of synthetic biology with machine learning algorithms could expand the possibilities of bioengineering. This review summarized current state-of-the-art knowledge of the data-assisted enzyme redesigning to actively promote new research on important enzymes to ameliorate the environment.

Revolutionizing enzyme engineering through artificial intelligence and machine learning

The combinatorial space of an enzyme sequence has astronomical possibilities and exploring it with contemporary experimental techniques is arduous and often ineffective. Multi-target objectives such as concomitantly achieving improved selectivity, solubility and activity of an enzyme have narrow plausibility under approaches of restricted mutagenesis and combinatorial search. Traditional enzyme engineering approaches have a limited scope for complex optimization due to the requirement of a priori knowledge or experimental burden of screening huge protein libraries. The recent surge in high-throughput experimental methods including Next Generation Sequencing and automated screening has flooded the field of molecular biology with big-data, which requires us to re-think our concurrent approaches towards enzyme engineering. Artificial Intelligence (AI) and Machine Learning (ML) have great potential to revolutionize smart enzyme engineering without the explicit need for a complete understanding of the underlying molecular system. Here, we portray the role and position of AI techniques in the field of enzyme engineering along with their scope and limitations. In addition, we explain how the traditional approaches of directed evolution and rational design can be extended through AI tools. Recent successful examples of AI-assisted enzyme engineering projects and their deviation from traditional approaches are highlighted. A comprehensive picture of current challenges and future avenues for AI in enzyme engineering are also discussed.

Structural Insights into a Novel Esterase from the East Pacific Rise and Its Improved Thermostability by a Semirational Design

Lipolytic enzymes are essential biocatalysts in food processing as well as pharmaceutical and pesticide industries, catalyzing the cleavage of ester bonds in a variety of acyl chain substrates. Here, we report the crystal structure of an esterase from the deep-sea hydrothermal vent of the East Pacific Rise (EprEst). The X-ray structure of EprEst in complex with the ligand, acetate, has been determined at 2.03 Å resolution. The structure reveals a unique spatial arrangement and orientation of the helix cap domain and α/β hydrolase domain, which form a substrate pocket with preference for short-chain acyl groups. Molecular docking analysis further demonstrated that the active site pocket could accommodate p-nitrophenyl (pNP) carboxyl ligands of varying lengths (≤6 C atoms), with pNP-butyrate ester predicted to have the highest binding affinity. Additionally, the semirational design was conducted to improve the thermostability of EprEst by enzyme engineering based on the established structure and multiple sequence alignment. A mutation, K114P, introduced in the hinge region of the esterase, which displayed increased thermostability and enzyme activity. Collectively, the structural and functional data obtained herein could be used as basis for further protein engineering to ultimately expand the scope of industrial applications of marine-derived lipolytic enzymes.

Preparation and application of solvent-free liquid proteins with enhanced thermal and anhydrous stabilities

This perspective details a robust chemical modification strategy to protect proteins from temperature, aggregation, and non-aqueous environments.

Tuning of adsorption of enzymes to polymer

In the past years, several serine hydrolases such as cutinases, esterases and lipases have shown the ability to degrade not only natural polymers but also synthetic polyesters, even aromatic representatives like polyethylene terephthalate (PET). Hence, cutinases and related ester hydrolases have become very important to be applied in the biocatalytic plastic recycling as green alternative to chemical recycling as well as to the functionalization of polyester surfaces in order to change superficial properties like hydrophobicity or hydrophilicity. Sorption characteristics of the enzymes to the polymers have turned out to be a crucial process for efficient polymer hydrolysis. Hence, special attention was paid on tuning the sorption of the enzymes to the hydrophobic polymers. Engineering of the enzyme surface, fusion of hydrophobic substrate-binding domains or truncation of domains hindering the access of the polymer to the enzyme has led to significant improvement of sorption processes and consequently increased activity on the bulky substrate. Finally, the combination of engineering approaches has proved that they can bring additional advantages in improving the enzyme activity when used in a synergistic manner.

Molecular engineering to improve lignocellulosic biomass based applications using filamentous fungi

Lignocellulosic biomass is an abundant and renewable resource, and its utilization has become the focus of research and biotechnology applications as a very promising raw material for the production of value-added compounds. Filamentous fungi play an important role in the production of various lignocellulolytic enzymes, while some of them have also been used for the production of important metabolites. However, wild type strains have limited efficiency in enzyme production or metabolic conversion, and therefore many efforts have been made to engineer improved strains. Examples of this are the manipulation of transcriptional regulators and/or promoters of enzyme-encoding genes to increase gene expression, and protein engineering to improve the biochemical characteristics of specific enzymes. This review provides and overview of the applications of filamentous fungi in lignocellulosic biomass based processes and the development and current status of various molecular engineering strategies to improve these processes.

Phylogeny and Structure of Fatty Acid Photodecarboxylases and Glucose-Methanol-Choline Oxidoreductases

Glucose-methanol-choline (GMC) oxidoreductases are a large and diverse family of flavin-binding enzymes found in all kingdoms of life. Recently, a new related family of proteins has been discovered in algae named fatty acid photodecarboxylases (FAPs). These enzymes use the energy of light to convert fatty acids to the corresponding Cn-1 alkanes or alkenes, and hold great potential for biotechnological application. In this work, we aimed at uncovering the natural diversity of FAPs and their relations with other GMC oxidoreductases. We reviewed the available GMC structures, assembled a large dataset of GMC sequences, and found that one active site amino acid, a histidine, is extremely well conserved among the GMC proteins but not among FAPs, where it is replaced with alanine. Using this criterion, we found several new potential FAP genes, both in genomic and metagenomic databases, and showed that related bacterial, archaeal and fungal genes are unlikely to be FAPs. We also identified several uncharacterized clusters of GMC-like proteins as well as subfamilies of proteins that lack the conserved histidine but are not FAPs. Finally, the analysis of the collected dataset of potential photodecarboxylase sequences revealed the key active site residues that are strictly conserved, whereas other residues in the vicinity of the flavin adenine dinucleotide (FAD) cofactor and in the fatty acid-binding pocket are more variable. The identified variants may have different FAP activity and selectivity and consequently may prove useful for new biotechnological applications, thereby fostering the transition from a fossil carbon-based economy to a bio-economy by enabling the sustainable production of hydrocarbon fuels.

Sortase mutants with improved protein thermostability and enzymatic activity obtained by consensus design

Staphylococcus aureus sortase A (SaSrtA) is an enzyme that anchors proteins to the cell surface of Gram-positive bacteria. During the transpeptidation reaction performed by SaSrtA, proteins containing an N-terminal glycine can be covalently linked to another protein with a C-terminal LPXTG motif (X being any amino acid). Since the sortase reaction can be performed in vitro as well, it has found many applications in biotechnology. Although sortase-mediated ligation has many advantages, SaSrtA is limited by its low enzymatic activity and dependence on Ca2+. In our study, we evaluated the thermodynamic stability of the SaSrtA wild type and found the enzyme to be stable. We applied consensus analysis to further improve the enzyme's stability while at the same time enhancing the enzyme's activity. As a result, we found thermodynamically improved, more active and Ca2+-independent mutants. We envision that these new variants can be applied in conjugation reactions in low Ca2+ environments.

One Pot Use of Combilipases for Full Modification of Oils and Fats: Multifunctional and Heterogeneous Substrates

Lipases are among the most utilized enzymes in biocatalysis. In many instances, the main reason for their use is their high specificity or selectivity. However, when full modification of a multifunctional and heterogeneous substrate is pursued, enzyme selectivity and specificity become a problem. This is the case of hydrolysis of oils and fats to produce free fatty acids or their alcoholysis to produce biodiesel, which can be considered cascade reactions. In these cases, to the original heterogeneity of the substrate, the presence of intermediate products, such as diglycerides or monoglycerides, can be an additional drawback. Using these heterogeneous substrates, enzyme specificity can promote that some substrates (initial substrates or intermediate products) may not be recognized as such (in the worst case scenario they may be acting as inhibitors) by the enzyme, causing yields and reaction rates to drop. To solve this situation, a mixture of lipases with different specificity, selectivity and differently affected by the reaction conditions can offer much better results than the use of a single lipase exhibiting a very high initial activity or even the best global reaction course. This mixture of lipases from different sources has been called “combilipases” and is becoming increasingly popular. They include the use of liquid lipase formulations or immobilized lipases. In some instances, the lipases have been coimmobilized. Some discussion is offered regarding the problems that this coimmobilization may give rise to, and some strategies to solve some of these problems are proposed. The use of combilipases in the future may be extended to other processes and enzymes.

Protein engineering strategies for microbial production of isoprenoids

Isoprenoids comprise one of the most chemically diverse family of natural products with high commercial interest. The structural diversity of isoprenoids is mainly due to the modular activity of three distinct classes of enzymes, including prenyl diphosphate synthases, terpene synthases, and cytochrome P450s. The heterologous expression of these enzymes in microbial systems is suggested to be a promising sustainable way for the production of isoprenoids. Several limitations are associated with native enzymes, such as low stability, activity, and expression profiles. To address these challenges, protein engineering has been applied to improve the catalytic activity, selectivity, and substrate turnover of enzymes. In addition, the natural promiscuity and modular fashion of isoprenoid enzymes render them excellent targets for combinatorial studies and the production of new-to-nature metabolites. In this review, we discuss key individual and multienzyme level strategies for the successful implementation of enzyme engineering towards efficient microbial production of high-value isoprenoids. Challenges and future directions of protein engineering as a complementary strategy to metabolic engineering are likewise outlined.

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Isoprenoid enzymes are attractive biocatalysts for protein engineering.

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Isoprenoid enzymes can be engineered for broader substrate promiscuity.

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Protein engineering can lead to the production of non-natural isoprenoids.

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Protein engineering can promote co-localization of isoprenoid pathway enzymes.

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Protein engineering supplements combinatorial biosynthesis for isoprenoid synthesis.

Deletion and Randomization of Structurally Variable Regions in B. subtilis Lipase A (BSLA) Alter Its Stability and Hydrolytic Performance Against Long Chain Fatty Acid Esters

The continuous search for novel enzyme backbones and the engineering of already well studied enzymes for biotechnological applications has become an increasing challenge, especially by the increasing potential diversity space provided by directed enzyme evolution approaches and the demands of experimental data generated by rational design of enzymes. In this work, we propose a semi-rational mutational strategy focused on introducing diversity in structurally variable regions in enzymes. The identified sequences are subjected to a progressive deletion of two amino acids and the joining residues are subjected to saturation mutagenesis using NNK degenerate codons. This strategy offers a novel library diversity approach while simultaneously decreasing enzyme size in the variable regions. In this way, we intend to identify and reduce variable regions found in enzymes, probably resulting from neutral drift evolution, and simultaneously studying the functional effect of said regions. This strategy was applied to Bacillus. subtilis lipase A (BSLA), by selecting and deleting six variable enzyme regions (named regions 1 to 6) by the deletion of two amino acids and additionally randomizing the joining amino acid residues. After screening, no active variants were found in libraries 1% and 4%, 15% active variants were found in libraries 2% and 3%, and 25% for libraries 5 and 6 (n = 3000 per library, activity detected using tributyrin agar plates). Active variants were assessed for activity in microtiter plate assay (pNP-butyrate), thermal stability, substrate preference (pNP-butyrate, -palmitate), and compared to wildtype BSLA. From these analyses, variant P5F3 (F41L-ΔW42-ΔD43-K44P), from library 3 was identified, showing increased activity towards longer chain p-nitrophenyl fatty acid esters, when compared to BSLA. This study allowed to propose the targeted region 3 (positions 40-46) as a potential modulator for substrate specificity (fatty acid chain length) in BSLA, which can be further studied to increase its substrate spectrum and selectivity. Additionally, this variant showed a decreased thermal resistance but interestingly, higher isopropanol and Triton X-100 resistance. This deletion-randomization strategy could help to expand and explore sequence diversity, even in already well studied and characterized enzyme backbones such as BSLA. In addition, this strategy can contribute to investigate and identify important non-conserved regions in classic and novel enzymes, as well as generating novel biocatalysts with increased performance in specific processes, such as enzyme immobilization.

Computational Design of Enantiocomplementary Epoxide Hydrolases for Asymmetric Synthesis of Aliphatic and Aromatic Diols

The use of enzymes in preparative biocatalysis often requires tailoring enzyme selectivity by protein engineering. Herein we explore the use of computational library design and molecular dynamics simulations to create variants of limonene epoxide hydrolase that produce enantiomeric diols from meso‐epoxides. Three substrates of different sizes were targeted: cis‐2,3‐butene oxide, cyclopentene oxide, and cis‐stilbene oxide. Most of the 28 designs tested were active and showed the predicted enantioselectivity. Excellent enantioselectivities were obtained for the bulky substrate cis‐stilbene oxide, and enantiocomplementary mutants produced (S,S)‐ and (R,R)‐stilbene diol with >97 % enantiomeric excess. An (R,R)‐selective mutant was used to prepare (R,R)‐stilbene diol with high enantiopurity (98 % conversion into diol, >99 % ee). Some variants displayed higher catalytic rates (k_cat) than the original enzyme, but in most cases K_M values increased as well. The results demonstrate the feasibility of computational design and screening to engineer enantioselective epoxide hydrolase variants with very limited laboratory screening.

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.