FireProt: web server for automated design of thermostable proteins

Semi-rational design for enhancing thermostability of Culex pipiens acetylcholinesterase and sensitivity analysis of acephate

Acetylcholinesterase (AChE) has emerged as a significant biological recognition element in the biosensor field, particularly for the detection of insecticides. Nevertheless, the weak thermostability of AChE restricts its utilization due to the complexities associated with production, storage, and application environments. By evaluating the binding affinity between representative AChE and insecticides, an AChE from Culex pipiens was screened out, which displayed a broad-spectrum and high sensitivity to insecticides. The C. pipiens AChE (CpA) was subsequently expressed in Escherichia coli (E. coli) as a soluble active protein. Furthermore, a three-point mutant, M4 (A340P/D390E/S581P), was obtained using a semi-rational design strategy that combined molecular dynamics (MD) simulation and computer-aided design, which exhibited a four-fold increase in half-life at 40 °C compared to the wild-type (WT) enzyme. The mutant M4 also demonstrated an optimal temperature of 50 °C and a melting temperature (Tm) of 51.2 °C. Additionally, the sensitivity of WT and M4 to acephate was examined, revealing a 50-fold decrease in the IC50 value of M4. The mechanism underlying the improvement in thermal performance was elucidated through secondary structure analysis and MD simulations, indicating an increase in the proportion of protein helices and local structural rigidity. MD analysis of the protein-ligand complexes suggested that the enhanced sensitivity of M4 could be attributed to frequent specific contacts between the organophosphorus (OP) group of acephate and the key active site residue Ser327. These findings have expanded the possibilities for the development of more reliable and effective industrial enzyme preparations and biosensors.

Rational design to improve the catalytic efficiency and stability of arginine deiminase

Arginine deiminase (ADI) has garnered significant interest because of its ability to objectively eradicate cancer cells and produce L-citrulline. To meet the production demands, this study focused on enhancing the enzyme activity and thermal stability of ADI. In this study, 24 ADI mutants were obtained through computer aid site-specific mutation in the ADI of Enterobacter faecalis. Notably, the specific enzyme activities of F44W, N163P, E220I, E220L, N318E, A336G, T340I, and N382F increased, reaching 1.33-2.53 times that of the original enzyme. This study confirmed that site-specific mutations are critical for optimizing enzyme function. Additionally, the F44W, N163P, E220I, T340I, and A336G mutants demonstrated good thermal stability. The optimal pH for mutant F44W increased to 8, whereas mutants E220I, I244V, A336G, T340I, and N328F maintained an optimal pH of 7.5. Conversely, the M109L, N163P, E220L, I244L, and N318E mutants shad an optimal pH of 7. This study revealed that mutant enzymes with increased activity were more likely to contain mutation sites situated near the four loops associated with catalytic residues, whereas mutations at the dimer junction sites had a higher tendency to enhance enzyme stability. These findings contribute to the development of ADI industrial applications and its modifications.

The two-step strategy for enhancing the specific activity and thermostability of alginate lyase AlyG2 with mechanism for improved thermostability

To overcome the trade-off challenge encountered in the engineering of alginate lyase AlyG2 from Seonamhaeicola algicola Gy8T and to expand its potential industrial applications, we devised a two-step strategy encompassing activity enhancement followed by thermal stability engineering. To enhance the specific activity of efficient AlyG2, we strategically substituted residues with bulky steric hindrance proximal to the active pocket with glycine or alanine. This led to the generation of three promising positive mutants, with particular emphasis on the T91S mutant, exhibiting a 1.91-fold specific activity compared to the wild type. To mitigate the poor thermal stability of T91S, mutants with negative ΔΔG values in the thermal flexibility region were screened out. Notably, the S72Y⁎ mutant not only displayed 17.96 % further increase in specific activity but also exhibited improved stability compared to T91S, manifesting as a remarkable 30.97 % increase in relative activity following a 1-hour incubation at 42 °C. Furthermore, enhanced kinetic stability was observed. To gain deeper insights into the mechanism underlying the enhanced thermostability of the S72Y⁎ mutant, we conducted molecular dynamics simulations, principal component analysis (PCA), dynamic cross-correlation map (DCCM), and free energy landscape (FEL) analysis. The results unveiled a reduction in the flexibility of the surface loop, a stronger correlation dynamic and a narrower motion subspace in S72Y⁎ system, along with the formation of more stable hydrogen bonds. Collectively, our findings suggest amino acids substitutions resulting in smaller side chains proximate to the active site can positively impact enzyme activity, while reducing the flexibility of surface loops emerges as a pivotal factor in conferring thermal stability. These insights offer valuable guidance and a framework for the engineering of other enzyme types.

Development of a Universal One-Step Purification and Activation Method to Engineer Protein-Glutaminase through Rational Design

Cytotoxic enzymes often exist as zymogens containing prodomains to keep them in an inactive state. Protein-glutaminase (PG), which can enhance various functional characteristics of food proteins, is an enzyme containing pro-PG and mature-PG (mPG). However, poor activity and stability limit its application while tedious purification and activation steps limit its high-throughput engineering. Here, based on structural analysis, we replaced the linker sequence between pro-PG and mPG with the HRV3C protease recognition sequence and then coexpressed it with HRV3C protease in Escherichia coli to develop an efficient one-step purification and activation method for PG. We then used this method to obtain several mutants designed by a combination of computer-aided approach and beneficial point mutations. The specific activity (131.6 U/mg) of the best variant D1 was 4.14-fold that of the wild type, and t1/2 and T5010 increased by 13 min and 7 °C, respectively. D1 could effectively improve the solubility and emulsification of wheat proteins, more than twice the effect of the wild type. We also discussed the mechanism underlying the improved properties of D1. In summary, we not only provide a universal one-step purification and activation method to facilitate zymogen engineering but also obtain an excellent PG mutant.

Click, Compute, Create: A Review of Web-based Tools for Enzyme Engineering

Enzyme engineering, though pivotal across various biotechnological domains, is often plagued by its time-consuming and labor-intensive nature. This review aims to offer an overview of supportive in silico methodologies for this demanding endeavor. Starting from methods to predict protein structures, to classification of their activity and even the discovery of new enzymes we continue with describing tools used to increase thermostability and production yields of selected targets. Subsequently, we discuss computational methods to modulate both, the activity as well as selectivity of enzymes. Last, we present recent approaches based on cutting-edge machine learning methods to redesign enzymes. With exception of the last chapter, there is a strong focus on methods easily accessible via web-interfaces or simple Python-scripts, therefore readily useable for a diverse and broad community.

Photocatalytic CO2 Reduction Using CO2-Binding Enzymes

Novel concepts to utilize carbon dioxide are required to reach a circular carbon economy and minimize environmental issues. To achieve these goals, photo-, electro-, thermal-, and biocatalysis are key tools to realize this, preferentially in aqueous solutions. Nevertheless, catalytic systems that operate efficiently in water are scarce. Here, we present a general strategy for the identification of enzymes suitable for CO2 reduction based on structural analysis for potential carbon dioxide binding sites and subsequent mutations. We discovered that the phenolic acid decarboxylase from Bacillus subtilis (BsPAD) promotes the aqueous photocatalytic CO2 reduction selectively to carbon monoxide in the presence of a ruthenium photosensitizer and sodium ascorbate. With engineered variants of BsPAD, TONs of up to 978 and selectivities of up to 93 % (favoring the desired CO over H2 generation) were achieved. Mutating the active site region of BsPAD further improved turnover numbers for CO generation. This also revealed that electron transfer is rate-limiting and occurs via multistep tunneling. The generality of this approach was proven by using eight other enzymes, all showing the desired activity underlining that a range of proteins is capable of photocatalytic CO2 reduction.

Effective synthesis of circRNA via a thermostable T7 RNA polymerase variant as the catalyst

Introduction

Circular RNAs (circRNAs) are endogenous noncoding RNAs (ncRNAs) with transcriptional lengths ranging from hundreds to thousands. circRNAs have attracted attention owing to their stable structure and ability to treat complicated diseases. Our objective was to create a one-step reaction for circRNA synthesis using wild-type T7 RNA polymerase as the catalyst. However, T7 RNA polymerase is thermally unstable, and we streamlined circRNA synthesis via consensus and folding free energy calculations for hotspot selection. Because of the thermal instability, the permuted intron and exon (PIE) method for circRNA synthesis is conducted via tandem catalysis with a transcription reaction at a low temperature and linear RNA precursor cyclization at a high temperature.

Methods

To streamline the process, a multisite mutant T7 RNA polymerase (S430P, N433T, S633P, F849I, F880Y, and G788A) with significantly improved thermostability was constructed, and G788A was used.

Results

The resulting mutant exhibited stable activity at 45°C for over an hour, enabling the implementation of a one-pot transcription and cyclization reaction. The simplified circRNA production process demonstrated an efficiency comparable to that of the conventional two-step reaction, with a cyclization rate exceeding 95% and reduced production of immunostimulatory dsRNA byproducts.

Opportunities and challenges in design and optimization of protein function

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

State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering

Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.

Analysis of Poly(ethylene terephthalate) degradation kinetics of evolved IsPETase variants using a surface crowding model

Poly(ethylene terephthalate) (PET) is a major plastic polymer utilized in the single-use and textile industries. The discovery of PET-degrading enzymes (PETases) has led to an increased interest in the biological recycling of PET in addition to mechanical recycling. IsPETase from Ideonella sakaiensis is a candidate catalyst, but little is understood about its structure-function relationships with regards to PET degradation. To understand the effects of mutations on IsPETase productivity, we develop a directed evolution assay to identify mutations beneficial to PET film degradation at 30 °C. IsPETase also displays enzyme concentration-dependent inhibition effects, and surface crowding has been proposed as a causal phenomenon. Based on total internal reflectance fluorescence microscopy and adsorption experiments, IsPETase is likely experiencing crowded conditions on PET films. Molecular dynamics simulations of IsPETase variants reveal a decrease in active site flexibility in free enzymes and reduced probability of productive active site formation in substrate-bound enzymes under crowding. Hence, we develop a surface crowding model to analyze the biochemical effects of three hit mutations (T116P, S238N, S290P) that enhanced ambient temperature activity and/or thermostability. We find that T116P decreases susceptibility to crowding, resulting in higher PET degradation product accumulation despite no change in intrinsic catalytic rate. In conclusion, we show that a macromolecular crowding-based biochemical model can be used to analyze the effects of mutations on properties of PETases and that crowding behavior is a major property to be targeted for enzyme engineering for improved PET degradation.

FireProt 2.0: web-based platform for the fully automated design of thermostable proteins

Thermostable proteins find their use in numerous biomedical and biotechnological applications. However, the computational design of stable proteins often results in single-point mutations with a limited effect on protein stability. However, the construction of stable multiple-point mutants can prove difficult due to the possibility of antagonistic effects between individual mutations. FireProt protocol enables the automated computational design of highly stable multiple-point mutants. FireProt 2.0 builds on top of the previously published FireProt web, retaining the original functionality and expanding it with several new stabilization strategies. FireProt 2.0 integrates the AlphaFold database and the homology modeling for structure prediction, enabling calculations starting from a sequence. Multiple-point designs are constructed using the Bron-Kerbosch algorithm minimizing the antagonistic effect between the individual mutations. Users can newly limit the FireProt calculation to a set of user-defined mutations, run a saturation mutagenesis of the whole protein or select rigidifying mutations based on B-factors. Evolution-based back-to-consensus strategy is complemented by ancestral sequence reconstruction. FireProt 2.0 is significantly faster and a reworked graphical user interface broadens the tool's availability even to users with older hardware. FireProt 2.0 is freely available at http://loschmidt.chemi.muni.cz/fireprotweb.

Computational saturation mutagenesis to explore the effect of pathogenic mutations on extra-cellular domains of TREM2 associated with Alzheimer's and Nasu-Hakola disease

CONTEXT

The specialised family of triggering receptors expressed on myeloid cells (TREMs) plays a pivotal role in causing neurodegenerative disorders and activating microglial anti-inflammatory responses. Nasu-Hakola disease (NHD), a rare autosomal recessive disorder, has been associated with mutations in TREM2, which is also responsible for raising the risk of Alzheimer's disease (AD). Herein, we have made an endeavour to differentiate the confirmed pathogenic variants in TREM2 extra-cellular domain (ECD) linked with NHD and AD using mutation-induced fold stability change (∆∆G), with the computation of 12distinct structure-based methods through saturation mutagenesis. Correlation analysis between relative solvent accessibility (RSA) and ∆∆G expresses the discrete distributive behaviour of mutants associated with TREM2 in AD (R2 = 0.061) and NHD (R2 = 0.601). Our findings put an emphasis on W50 and V126 as major players in maintaining V-like domain in TREM2. Interestingly, we discern that both of them interact with a common residue Y108, which is dissolved upon mutation. This Y108 could have structural or functional role for TREM2 which can be an ideal candidate for further study. Furthermore, the residual interaction network highlights the importance of R47 and R62 in maintaining the CDR loops that are crucial for ligand binding. Future studies using biophysical characterisation of ligand interactions in TREM2-ECD would be helpful for the development of novel therapeutics for AD and NHD.

METHODS

ConSurf algorithm and ENDscript were used to determine the position and conservation of each residue in the wild-type ECD of TREM2. The mutation-induced fold stability change (∆∆G) of confirmed pathogenic mutants associated with NHD and AD was estimated using 12 state-of-the-art structure-based protein stability tools. Furthermore, we also computed the effect of random mutation on these sites using computational saturation mutagenesis. Linear regression analysis was performed using mutants ∆∆G and RSA through GraphPad software. In addition, a comprehensive non-bonded residual interaction network (RIN) of wild type and its mutants of TREM2-ECD was enumerated using RING3.0.

Machine Learning-Guided Protein Engineering

Recent progress in engineering highly promising biocatalysts has increasingly involved machine learning methods. These methods leverage existing experimental and simulation data to aid in the discovery and annotation of promising enzymes, as well as in suggesting beneficial mutations for improving known targets. The field of machine learning for protein engineering is gathering steam, driven by recent success stories and notable progress in other areas. It already encompasses ambitious tasks such as understanding and predicting protein structure and function, catalytic efficiency, enantioselectivity, protein dynamics, stability, solubility, aggregation, and more. Nonetheless, the field is still evolving, with many challenges to overcome and questions to address. In this Perspective, we provide an overview of ongoing trends in this domain, highlight recent case studies, and examine the current limitations of machine learning-based methods. We emphasize the crucial importance of thorough experimental validation of emerging models before their use for rational protein design. We present our opinions on the fundamental problems and outline the potential directions for future research.

Energy- and evolution-based design of inulosucrase for enhanced thermostability and inulin production

Inulosucrase from Lactobacillus reuteri 121 (LrInu) exhibits promise in the synthesis of prebiotic inulin and fructooligosaccharides. However, for its use in industry, LrInu's thermostability is a crucial consideration. In this study, the computational program FireProt was used to predict the thermostable variants of LrInu. Using rational criteria, nine variants were selected for protein expression and characterization. The G237P variant was determined to be the greatest designed candidate due to its greatly enhanced stability and activity in comparison to the wild-type enzyme. The optimum temperature of G237P increased from 50 to 60°C, with an over 5-fold increase in the half-life. Spectroscopy studies revealed that the G237P mutation could prevent the structural change in LrInu caused by heat or urea treatment. Molecular dynamics (MD) simulations showed that the enhanced thermostability of the G237P variant resulted from an increase in structural rigidity and the number of native contacts within the protein molecule. In addition, G237P variant synthesizes inulin with greater efficiency than WT. KEY POINTS: • Thermostable inulosucrase variant(s) were designed by Fireprot server. • G237P variant showed significantly improved thermostability compared to the wild type. • Inulin is synthesized more efficiently by G237P variant.

Rational Redesign of Chitosanase to Enhance Thermostability and Catalytic Activity to Produce Chitooligosaccharides with a Relatively High Degree of Polymerization

Chitooligosaccharides (hdpCOS) with a high degree of polymerization (hdp, DP 4-10) generally have greater biological activities than those of low-DP (ldp, DP 2-3) COS. Chitosanase from Bacillus amyloliquefaciens KCP2 (Csn46) can degrade chitosan to more hdpCOS at high temperature (70 °C), but low thermal stability at this temperature makes it unsuitable for industrial application; the wild-type enzyme can only produce COS (DP 2-4) at lower temperatures. Several thermostable mutants were obtained by modifying chitosanase using a comprehensive strategy based on a computer-aided mutant design. A combination of four beneficial single-point mutations (A129L/T175 V/K70T/D34G) to Csn46 was selected to obtain a markedly improved mutant, Mut4, with a half-life at 60 °C extended from 34.31 to 690.80 min, and the specific activity increased from 1671.73 to 3528.77 U/mg. Mut4 produced COS with DPs of 2-4 and 2-7 at 60 and 70 °C, respectively. Therefore, Mut4 has the potential to be applied to the industrial-scale preparation of hdpCOS with high biological activity.

Advancing Enzyme's Stability and Catalytic Efficiency through Synergy of Force-Field Calculations, Evolutionary Analysis, and Machine Learning

Thermostability is an essential requirement for the use of enzymes in the bioindustry. Here, we compare different protein stabilization strategies using a challenging target, a stable haloalkane dehalogenase DhaA115. We observe better performance of automated stabilization platforms FireProt and PROSS in designing multiple-point mutations over the introduction of disulfide bonds and strengthening the intra- and the inter-domain contacts by in silico saturation mutagenesis. We reveal that the performance of automated stabilization platforms was still compromised due to the introduction of some destabilizing mutations. Notably, we show that their prediction accuracy can be improved by applying manual curation or machine learning for the removal of potentially destabilizing mutations, yielding highly stable haloalkane dehalogenases with enhanced catalytic properties. A comparison of crystallographic structures revealed that current stabilization rounds were not accompanied by large backbone re-arrangements previously observed during the engineering stability of DhaA115. Stabilization was achieved by improving local contacts including protein-water interactions. Our study provides guidance for further improvement of automated structure-based computational tools for protein stabilization.

Improving the thermostability of a novel PL-6 family alginate lyase by rational design engineering for industrial preparation of alginate oligosaccharides

Alginate is degraded into alginate oligosaccharides with various biological activities by enzymes. However, the thermostability of the enzyme limits its industrial application. In this study, a novel PL-6 alginate lyase, AlyRm6A from Rhodothermus marinus 4252 was expressed and characterized. In addition, an efficient comprehensive strategy was proposed, including automatic design of heat-resistant mutants, multiple computer-aided ΔΔGfold value calculation, and conservative analysis of mutation sites. AlyRm6A has naturally high thermostability. Compared with the WT, T43I and Q216I kept their original activities, and their half-lives were increased from 3.68 h to 4.29 h and 4.54 h, melting point temperatures increased from 61.5 °C to 62.9 °C and 63.5 °C, respectively. The results of circular dichroism showed that both the mutants and the wild type had the characteristic peaks of β-sheet at 195 nm and 216 nm, which indicated that there was no significant effect on the secondary structure of the protein. Molecular dynamics simulation (MD) analyses suggest that the enhancement of the hydrophobic interaction network, improvement of molecular rigidity, and denser structure could improve the stability of AlyRm6A. To the best of our knowledge, our findings indicate that AlyRm6A mutants exhibit the highest thermostability among the characterized PL-6 alginate lyases, making them potential candidates for industrial production of alginate oligosaccharides.

Computer-Aided Lipase Engineering for Improving Their Stability and Activity in the Food Industry: State of the Art

As some of the most widely used biocatalysts, lipases have exhibited extreme advantages in many processes, such as esterification, amidation, and transesterification reactions, which causes them to be widely used in food industrial production. However, natural lipases have drawbacks in terms of organic solvent resistance, thermostability, selectivity, etc., which limits some of their applications in the field of foods. In this systematic review, the application of lipases in various food processes was summarized. Moreover, the general structure of lipases is discussed in-depth, and the engineering strategies that can be used in lipase engineering are also summarized. The protocols of some classical methods are compared and discussed, which can provide some information about how to choose methods of lipase engineering. Thermostability engineering and solvent tolerance engineering are highlighted in this review, and the basic principles for improving thermostability and solvent tolerance are summarized. In the future, comput er-aided technology should be more emphasized in the investigation of the mechanisms of reactions catalyzed by lipases and guide the engineering of lipases. The engineering of lipase tunnels to improve the diffusion of substrates is also a promising prospect for further enhanced lipase activity and selectivity.

Improving the soluble expression of difficult-to-express proteins in prokaryotic expression system via protein engineering and synthetic biology strategies

Solubility and folding stability are key concerns for difficult-to-express proteins (DEPs) restricted by amino acid sequences and superarchitecture, resolved by the precise distribution of amino acids and molecular interactions as well as the assistance of the expression system. Therefore, an increasing number of tools are available to achieve efficient expression of DEPs, including directed evolution, solubilization partners, chaperones, and affluent expression hosts, among others. Furthermore, genome editing tools, such as transposons and CRISPR Cas9/dCas9, have been developed and expanded to construct engineered expression hosts capable of efficient expression ability of soluble proteins. Accounting for the accumulated knowledge of the pivotal factors in the solubility and folding stability of proteins, this review focuses on advanced technologies and tools of protein engineering, protein quality control systems, and the redesign of expression platforms in prokaryotic expression systems, as well as advances of the cell-free expression technologies for membrane proteins production.

Engineering the thermostability of d-lyxose isomerase from Caldanaerobius polysaccharolyticus via multiple computer-aided rational design for efficient synthesis of d-mannose

d-Mannose is an attractive functional sugar that exhibits many physiological benefits on human health. The demand for low-calorie sugars and sweeteners in foods are increasingly available on the market. Some sugar isomerases, such as d-lyxose isomerase (d-LIase), can achieve an isomerization reaction between d-mannose and d-fructose. However, the weak thermostability of d-LIase limits its efficient conversion from d-fructose to d-mannose. Nonetheless, few studies are available that have investigated the molecular modification of d-LIase to improve its thermal stability. In this study, computer-aided tools including FireProt, PROSS, and Consensus Finder were employed to jointly design d-LIase mutants with improved thermostability for the first time. Finally, the obtained five-point mutant M5 (N21G/E78P/V58Y/C119Y/K170P) showed high thermal stability and catalytic activity. The half-life of M5 at 65 °C was 10.22 fold, and the catalytic efficiency towards 600 g/L of d-fructose was 2.6 times to that of the wild type enzyme, respectively. Molecular dynamics simulation and intramolecular forces analysis revealed a thermostability mechanism of highly rigidity conformation, newly formed hydrogen bonds and π-cation interaction between and within protein domains, and redistributed surface electrostatic charges for the mutant M5. This research provided a promising d-LIase mutant for the industrial production of d-mannose from d-fructose.

Improving thermostability of a PL 5 family alginate lyase with combination of rational design strategies

Alginate lyases with strict substrate specificity possess potential in directed production of alginate oligosaccharides with specific composition. However, their poor thermostability hampered their applications in industry. In this study, an efficient comprehensive strategy including sequence-based analysis, structure-based analysis, and computer-aid ΔΔGfold value calculation was proposed. It was successfully performed on alginate lyase (PMD) with strict poly-β-D-mannuronic acid substrate specificity. Four single-point variants A74V, G75V, A240V, and D250G with increased T_m of 3.94 °C, 5.21 °C, 2.56 °C, and 4.80 °C, respectively, were selected out. After ordered combined mutations, a four-point mutant (M4) was finally generated which displayed remarkable increase on thermostability. The T_m of M4 increased from 42.25 °C to 51.59 °C and its half-life at 50 °C was about 58.9-fold of PMD. Meanwhile, there was no obvious loss of enzyme activity (more than 90% retained). Molecular dynamics simulation analysis insisted that the improvement of thermostability might be attribute to the rigidified region A which might be caused by the newly formed hydrogen bonds and salt bridges introduced by mutations, the lower distance of original hydrogen bonds, and the more compact overall structures.

Counteraction of stability-activity trade-off of Nattokinase through flexible region shifting

The widespread trade-off between stability and activity severely limits enzyme evolution. Although some progresses have been made to overcome this limitation, the counteraction mechanism for enzyme stability-activity trade-off remains obscure. Here, we clarified the counteraction mechanism of the Nattokinase stability-activity trade-off. A combinatorial mutant M4 was obtained by multi-strategy engineering, exhibiting a 20.7-fold improved half-life; meanwhile, the catalytic efficiency was doubled. Molecular dynamics simulation revealed that an obvious flexible region shifting in the structure of mutant M4 was occurred. The flexible region shifting which contributed to maintain the global structural flexibility, was considered to be the key factor for counteracting the stability-activity trade-off. Further analysis illustrated that the flexible region shifting was driven by region dynamical networks reshaping. This work provided deep insight into the counteraction mechanism of enzyme stability-activity trade-off, suggesting that flexible region shifting would be an effective strategy for enzyme evolution through computational protein engineering.

Enhanced Thermostability and Catalytic Activity of Streptomyces mobaraenesis Transglutaminase by Rationally Engineering Its Flexible Regions

Streptomyces mobaraenesis transglutaminase can catalyze the cross-linking of proteins, which has been widely used in food processing. In this study, we rationally modified flexible regions to further improve the thermostability of FRAPD-TGm2 (S2P-S23V-Y24N-E28T-S199A-A265P-A287P-K294L), a stable mutant of the transglutaminase constructed in our previous study. First, five flexible regions of FRAPD-TGm2 were identified by molecular dynamics simulations at 330 and 360 K. Second, a script based on Rosetta Cartesian_ddg was developed for virtual saturation mutagenesis within the flexible regions far from the substrate binding pocket, generating the top 18 mutants with remarkable decreases in folding free energy. Third, from the top 18 mutants, we identified two mutants (S116A and S179L) with increased thermostability and activity. Finally, the above favorable mutations were combined to obtain FRAPD-TGm2-S116A-S179L (FRAPD-TGm2A), exhibiting a half-life of 132.38 min at 60 °C (t_1/2(60 °C)) and a specific activity of 79.15 U/mg, 84 and 21% higher than those of FRAPD-TGm2, respectively. Therefore, the current result may benefit the application of S. mobaraenesis transglutaminase at high temperatures.

Automated optimisation of solubility and conformational stability of antibodies and proteins

Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.

Simultaneously optimizing multiple properties of β-glucosidase Bgl6 using combined (semi-)rational design strategies and investigation of the underlying mechanisms

The performance of β-glucosidase during cellulose saccharification is determined by thermostability, activity and glucose tolerance. However, conflicts between them make it challenging to simultaneously optimize three properties. In this work, such a case was reported using Bgl6-M3 as a starting point. Firstly, four thermostability-enhancing mutations were obtained using computer-aided engineering strategies (mutant M7). Secondly, substrate binding pocket of M7 was reshaped, generating two mutations that increased activity but decreased glucose tolerance (mutant M9). Then a key region lining active site cavity was redesigned, resulting in three mutations that boosted glucose tolerance and activity. Finally, mutant M12 with simultaneously improved thermostability (half-life of 20-fold), activity (k_cat/K_m of 5.6-fold) and glucose tolerance (ΔIC₅₀ of 200 mM) was obtained. Mechanisms for property improvement were elucidated by structural analysis and molecular dynamics simulations. Overall, the strategies used here and new insights into the underlying mechanisms may provide guidance for multi-property engineering of other enzymes.

A high-throughput expression and screening platform for applications-driven PETase engineering

The environmental consequences of plastic waste have impacted all kingdoms of life in terrestrial and aquatic ecosystems. However, as the burden of plastic pollution has increased, microbes have evolved to utilize anthropogenic polymers as nutrient sources. Of depolymerase enzymes, the best characterized is PETase, which hydrolyzes aromatic polyesters. PETase engineering has made impressive progress in recent years; however, further optimization of engineered PETase toward industrial application has been limited by lower throughput techniques used in protein purification and activity detection. Here, we address these deficiencies through development of a higher-throughput PETase engineering platform. Secretory expression via YebF tagging eliminates lysis and purification steps, facilitating production of large mutant libraries. Fluorescent detection of degradation products permits rapid screening of depolymerase activity in microplates as opposed to serial chromatographic methods. This approach enabled development of more stable PETase, semi-rational (SR) PETase variant containing previously unpublished mutations. SR-PETase releases 1.9-fold more degradation products and has up to 7.4-fold higher activity than wild-type PETase over 10 days at 40°C. These methods can be adapted to a variety of chemical environments, enabling screening of PETase mutants in applications-relevant conditions. Overall, this work promises to facilitate advancements in PETase engineering toward industrial depolymerization of plastic waste.

Recent advances in simultaneous thermostability-activity improvement of industrial enzymes through structure modification

Engineered thermostable microbial enzymes are widely employed to catalyze chemical reactions in numerous industrial sectors. Although high thermostability is a prerequisite of industrial applications, enzyme activity is usually sacrificed during thermostability improvement. Therefore, it is vital to select the common and compatible strategies between thermostability and activity improvement to reduce mutants̕ libraries and screening time. Three functional protein engineering approaches, including directed evolution, rational design, and semi-rational design, are employed to manipulate protein structure on a genetic basis. From a structural standpoint, integrative strategies such as increasing substrate affinity; introducing electrostatic interaction; removing steric hindrance; increasing flexibility of the active site; N- and C-terminal engineering; and increasing intramolecular and intermolecular hydrophobic interactions are well-known to improve simultaneous activity and thermostability. The current review aims to analyze relevant strategies to improve thermostability and activity simultaneously to circumvent the thermostability and activity trade-off of industrial enzymes.

Mining and Characterization of Thermophilic Glucose Isomerase Based on Virtual Probe Technology

Fructose, which is produced by the isomerization of glucose isomerase, is a crucial precursor for the biosynthesis of rare sugars. In this study, thermophilic glucose isomerases (GI) from Caldicellulosiruptor acetigenus (CAGI), Thermoanaerobacter thermocopriae (TTGI), and Thermotoga petrophila (TPGI) were screened from GenBank database by a virtual probe and were successfully expressed in Escherichia coli BL21(DE3). The results of characterization demonstrated that the optimal pH for CAGI and TTGI were 8.0 and were maintained at 80% in a slightly acidic environment. The relative residual activities of CAGI and TTGI were found to be 40.6% and 52.6%, respectively, following an incubation period of 24 h at 90 ℃. Furthermore, CAGI and TTGI exhibited superior catalytic performance that their reaction equilibrium both reached only after an hour at 85 ℃ with 200 g/L glucose, and the highest conversion rates were 54.2% and 54.1%, respectively. This study identifies competitive enzyme candidates for fructose production in the industry with appreciable cost reduction.

Efficient Exploration of Sequence Space by Sequence-Guided Protein Engineering and Design

The rapid growth of sequence databases over the past two decades means that protein engineers faced with optimizing a protein for any given task will often have immediate access to a vast number of related protein sequences. These sequences encode information about the evolutionary history of the protein and the underlying sequence requirements to produce folded, stable, and functional protein variants. Methods that can take advantage of this information are an increasingly important part of the protein engineering tool kit. In this Perspective, we discuss the utility of sequence data in protein engineering and design, focusing on recent advances in three main areas: the use of ancestral sequence reconstruction as an engineering tool to generate thermostable and multifunctional proteins, the use of sequence data to guide engineering of multipoint mutants by structure-based computational protein design, and the use of unlabeled sequence data for unsupervised and semisupervised machine learning, allowing the generation of diverse and functional protein sequences in unexplored regions of sequence space. Altogether, these methods enable the rapid exploration of sequence space within regions enriched with functional proteins and therefore have great potential for accelerating the engineering of stable, functional, and diverse proteins for industrial and biomedical applications.

Enhancing the Thermal Stability of Glutathione Bifunctional Synthase by B-Factor Strategy and Un/Folding Free Energy Calculation

Glutathione is of great significance in pharmaceutical and health fields, and one-step synthesis of reduced glutathione by glutathione bifunctional synthase has become a focus of research. The stability of glutathione bifunctional synthase is generally poor and urgently needs to be modified. The B-factor strategy and un/folding free energy calculation were both applied to enhance the thermal stability of glutathione bifunctional synthase from Streptococcus agalactiae (GshFSA). Based on the concept of B-factor strategy, we calculated the B-factor by molecular dynamics simulation to find flexible residues, performed point saturation mutations and high-throughput screening. At the same time, we also calculated the un/folding free energy of GshFSA and performed the point mutations. The optimal mutant from the B-factor strategy was R270S, which had a 2.62-fold increase in half-life period compared to the wild type, and the Q406M was the optimal mutant from the un/folding free energy calculation, with a 3.02-fold increase in half-life period. Both of them have provided a mechanistic explanation.

Feruloyl Esterases Protein Engineering to Enhance Their Performance as Biocatalysts: A Review

Feruloyl esterases (FAEs) are versatile enzymes able to release hydroxycinnamic acids or synthesize their ester derivatives, both molecules with interesting biological activities such as: antioxidants, antifungals, antivirals, antifibrotic, anti-inflammatory, among others. The importance of these molecules in medicine, food or cosmetic industries provides FAEs with several biotechnological applications as key industrial biocatalysts. However, FAEs have some operational limitations that must be overcome, which can be addressed through different protein engineering approaches to enhance their thermal stability, catalytic efficiencies, and selectivity. This review aims to present a brief historical tour through the mutagenesis strategies employed to improve enzymes performance and analyze the current protein engineering strategies applied to FAEs as interesting biocatalysts. Finally, an outlook of the future of FAEs protein engineering approaches to achieve successful industrial biocatalysts is given.

Stabilizing proteins, simplified: A Rosetta-based webtool for predicting favorable mutations

Many proteins have low thermodynamic stability, which can lead to low expression yields and limit functionality in research, industrial and clinical settings. This article introduces two, web-based tools that use the high-resolution structure of a protein along with the Rosetta molecular modeling program to predict stabilizing mutations. The protocols were recently applied to three genetically and structurally distinct proteins and successfully predicted mutations that improved thermal stability and/or protein yield. In all three cases, combining the stabilizing mutations raised the protein unfolding temperatures by more than 20°C. The first protocol evaluates point mutations and can generate a site saturation mutagenesis heatmap. The second identifies mutation clusters around user-defined positions. Both applications only require a protein structure and are particularly valuable when a deep multiple sequence alignment is not available. These tools were created to simplify protein engineering and enable research that would otherwise be infeasible due to poor expression and stability of the native molecule.

Thermostability engineering of industrial enzymes through structure modification

Thermostability is an essential requirement of enzymes in the industrial processes to catalyze the reactions at high temperatures; thus, enzyme engineering through directed evolution, semi-rational design and rational design are commonly employed to construct desired thermostable mutants. Several strategies are implemented to fulfill enzymes' thermostability demand including decreasing the entropy of the unfolded state through substitutions Gly → Xxx or Xxx → Pro, hydrogen bond, salt bridge, introducing two different simultaneous interactions through single mutant, hydrophobic interaction, filling the hydrophobic cavity core, decreasing surface hydrophobicity, truncating loop, aromatic-aromatic interaction and introducing positively charged residues to enzyme surface. In the current review, horizons about compatibility between secondary structures and substitutions at preferable structural positions to generate the most desirable thermostability in industrial enzymes are broadened. KEY POINTS: • Protein engineering is a powerful tool for generating thermostable industrial enzymes. • Directed evolution and rational design are practical approaches in enzyme engineering. • Substitutions in preferable structural positions can increase thermostability.

Structural Analysis and Construction of a Thermostable Antifungal Chitinase

Chitin is a biopolymer of N-acetyl-d-glucosamine with β-1,4-bond and is the main component of arthropod exoskeletons and the cell walls of many fungi. Chitinase (EC 3.2.1.14) is an enzyme that hydrolyzes the β-1,4-bond in chitin and degrades chitin into oligomers. It has been found in a wide range of organisms. Chitinase from Gazyumaru (Ficus microcarpa) latex exhibits antifungal activity by degrading chitin in the cell wall of fungi and is expected to be used in medical and agricultural fields. However, the enzyme's thermostability is an important factor; chitinase is not thermostable enough to maintain its activity under the actual application conditions. In addition to the fact that thermostable chitinases exhibiting antifungal activity can be used under various conditions, they have some advantages for the production process and long-term preservation, which are highly demanded in industrial use. We solved the crystal structure of chitinase to explore the target sites to improve its thermostability. We rationally introduced proline residues, a disulfide bond, and salt bridges in the chitinase using protein-engineering methods based on the crystal structure and sequence alignment among other chitinases. As a result, we successfully constructed the thermostable mutant chitinases rationally with high antifungal and specific activities. The results provide a useful strategy to enhance the thermostability of this enzyme family. IMPORTANCE We solved the crystal structure of the chitinase from Gazyumaru (Ficus microcarpa) latex exhibiting antifungal activity. Furthermore, we demonstrated that the thermostable mutant enzyme with a melting temperature (T_m) 6.9°C higher than wild type (WT) and a half-life at 60°C that is 15 times longer than WT was constructed through 10 amino acid substitutions, including 5 proline residues substitutions, making disulfide bonding, and building a salt bridge network in the enzyme. These mutations do not affect its high antifungal activity and chitinase activity, and the principle for the construction of the thermostable chitinase was well explained by its crystal structure. Our results provide a useful strategy to enhance the thermostability of this enzyme family and to use the thermostable mutant as a seed for antifungal agents for practical use.

Structure-based interface engineering methodology in designing a thermostable amylose-forming transglucosylase

Many drugs and prebiotics derive their activities from sugar substituents. Due to the prevalence and complexity of these biologically active compounds, enzymatic glycodiversification that facilitates easier access to these compounds can make profound contributions to the pharmaceutical, food, and feed industries. Amylosucrases (ASases) are attractive tools for glycodiversification because of their broad acceptor substrate specificity, but the lack of structural information and their poor thermostability limit their industrial applications. Herein, we reported the crystal structure of ASase from Calidithermus timidus, which displays a homotetrameric quaternary organization not previously observed for other ASases. We employed a workflow composed of five common strategies, including interface engineering, folding energy calculations, consensus sequence, hydrophobic effects enhancement, and B-factor analysis, to enhance the thermostability of C. timidus ASase. As a result, we obtained a quadruple-point mutant M31 ASase with a half-life at 65 °C increased from 22.91 h to 52.93 h, which could facilitate biosynthesis of glucans with a degree of polymerization of more than 20 using sucrose as a substrate at 50 °C. In conclusion, this study provides a structural basis for understanding the multifunctional biocatalyst ASase and presents a powerful methodology to effectively and systematically enhance protein thermostability.

Protposer: the web server that readily proposes protein stabilizing mutations with high PPV

Protein stability is a requisite for most biotechnological and medical applications of proteins. As natural proteins tend to suffer from a low conformational stability ex vivo, great efforts have been devoted toward increasing their stability through rational design and engineering of appropriate mutations. Unfortunately, even the best currently used predictors fail to compute the stability of protein variants with sufficient accuracy and their usefulness as tools to guide the rational stabilisation of proteins is limited. We present here Protposer, a protein stabilising tool based on a different approach. Instead of quantifying changes in stability, Protposer uses structure- and sequence-based screening modules to nominate candidate mutations for subsequent evaluation by a logistic regression model, carefully trained to avoid overfitting. Thus, Protposer analyses PDB files in search for stabilization opportunities and provides a ranked list of promising mutations with their estimated success rates (eSR), their probabilities of being stabilising by at least 0.5 kcal/mol. The agreement between eSRs and actual positive predictive values (PPV) on external datasets of mutations is excellent. When Protposer is used with its Optimal kappa selection threshold, its PPV is above 0.7. Even with less stringent thresholds, Protposer largely outperforms FoldX, Rosetta and PoPMusiC. Indicating the PDB file of the protein suffices to obtain a ranked list of mutations, their eSRs and hints on the likely source of the stabilization expected. Protposer is a distinct, straightforward and highly successful tool to design protein stabilising mutations, and it is freely available for academic use at http://webapps.bifi.es/the-protposer.

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.

Making Enzymes Suitable for Organic Chemistry by Rational Protein Design

This review outlines recent developments in protein engineering of stereo‐ and regioselective enzymes, which are of prime interest in organic and pharmaceutical chemistry as well as biotechnology. The widespread application of enzymes was hampered for decades due to limited enantio‐, diastereo‐ and regioselectivity, which was the reason why most organic chemists were not interested in biocatalysis. This attitude began to change with the advent of semi‐rational directed evolution methods based on focused saturation mutagenesis at sites lining the binding pocket. Screening constitutes the labor‐intensive step (bottleneck), which is the reason why various research groups are continuing to develop techniques for the generation of small and smart mutant libraries. Rational enzyme design, traditionally an alternative to directed evolution, provides small collections of mutants which require minimal screening. This approach first focused on thermostabilization, and did not enter the field of stereoselectivity until later. Computational guides such as the Rosetta algorithms, HotSpot Wizard metric, and machine learning (ML) contribute significantly to decision making. The newest advancements show that semi‐rational directed evolution such as CAST/ISM and rational enzyme design no longer develop on separate tracks, instead, they have started to merge. Indeed, researchers utilizing the two approaches have learned from each other. Today, the toolbox of organic chemists includes enzymes, primarily because the possibility of controlling stereoselectivity by protein engineering has ensured reliability when facing synthetic challenges. This review was also written with the hope that undergraduate and graduate education will include enzymes more so than in the past.

Tools for computational design and high-throughput screening of therapeutic enzymes

Therapeutic enzymes are valuable biopharmaceuticals in various biomedical applications. They have been successfully applied for fibrinolysis, cancer treatment, enzyme replacement therapies, and the treatment of rare diseases. Still, there is a permanent demand to find new or better therapeutic enzymes, which would be sufficiently soluble, stable, and active to meet specific medical needs. Here, we highlight the benefits of coupling computational approaches with high-throughput experimental technologies, which significantly accelerate the identification and engineering of catalytic therapeutic agents. New enzymes can be identified in genomic and metagenomic databases, which grow thanks to next-generation sequencing technologies exponentially. Computational design and machine learning methods are being developed to improve catalytically potent enzymes and predict their properties to guide the selection of target enzymes. High-throughput experimental pipelines, increasingly relying on microfluidics, ensure functional screening and biochemical characterization of target enzymes to reach efficient therapeutic enzymes.

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

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

Computer-Aided Targeted Mutagenesis of Thermoclostridium caenicola d-Allulose 3-Epimerase for Improved Thermostability

d-Allulose 3-epimerase (DAEase) is a key enzyme in d-allulose bioproduction. DAEase from Thermoclostridium caenicola suffers from poor thermostability, hampering its large-scale applications in industry. In this study, mutants A70P, G107P, F155Y, and D162T with increased melting point temperature (T_m) were obtained by targeted mutagenesis based on the calculation of the free energy of folding. The optimal single-point mutant G107P showed 11.08 h, 5, and 5.70 °C increases in the values of half-life (t_1/2) at 60 °C, the optimum temperature (T_opt), and T_m, respectively. Beneficial mutations were combined by ordered recombination mutagenesis, and the combinational mutant Var3 (G107P/F155Y/D162T/A70P) was generated with ΔT_opt of 10 °C and ΔT_m of 12.25 °C. Its t_1/2 value at 65 °C was more than 140 times higher than that of the wild-type enzyme. Molecular dynamics simulations and homology modeling analysis indicated that the enhanced overall rigidity, increased hydrogen bonds between subunits, and redistributed surface electrostatic charges might be responsible for the improved thermostability of the mutant Var3.

Rational-Design Engineering to Improve Enzyme Thermostability

The fundamentals of thermostability engineering need to be carried out for proteins with low thermal stability to expand their utilization. Thus, comprehension of the thermal stability regulating factors of proteins is needful for the engineering of their thermostability. Protein engineering aims to overcome their natural limitations in tough conditions by refining protein stability and activity. Rational-design approach requires a crystal structure dataset along with the biophysical information, protein function, and sequence-based data, especially consensus sequence that is favorable for the protein folding during natural evolution. It can be attained by either single- or multiple-point mutation, by which amino acids are changed. In fact, these mutation approaches show several benefits. For example, the offered mutations are produced after an evaluation and design, which raise the chance to acquire favorable mutations. The rational-design engineering can improve the biochemical properties of enzymes, including the kinetic behaviors, substrate specificity, thermostability, and organic solvent tolerance. Moreover, this approach considerably reduces the library size, so less effort and time can be employed. Here, we apply the computational algorithms and programs with experiments to create thermostable enzymes that will be beneficial for future applications.

Thermogenetics: Applications come of age

Temperature is a ubiquitous physical cue that is non-invasive, penetrative and easy to apply. In the growing field of thermogenetics, through beneficial repurposing of natural thermosensing mechanisms, synthetic biology is bringing new opportunities to design and build robust temperature-sensitive (TS) sensors which forms a thermogenetic toolbox of well characterised biological parts. Recent advancements in technological platforms available have expedited the discovery of novel or de novo thermosensors which are increasingly deployed in many practical temperature-dependent biomedical, industrial and biosafety applications. In all, the review aims to convey both the exhilarating recent technological developments underlying the advancement of thermosensors and the exciting opportunities the nascent thermogenetic field holds for biomedical and biotechnology applications.

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.

Enhancing Thermostability of Lipase from Pseudomonas alcaligenes for producing L-menthol by the CREATE Strategy

The Lipase from Pseudomonas alcaligenes (PaL) catalyzes the hydrolysis of racemic menthol propionate to produce L-menthol, one of the most important flavoring agents in food, cosmetics and pharmaceuticals industries. However,...