An appraisal of the enzyme stability‐activity trade‐off

Rheostatic contributions to protein stability can obscure a position's functional role

Rheostat positions, which can be substituted with various amino acids to tune protein function across a range of outcomes, are a developing area for advancing personalized medicine and bioengineering. Current methods cannot accurately predict which proteins contain rheostat positions or their substitution outcomes. To compare the prevalence of rheostat positions in homologs, we previously investigated their occurrence in two pyruvate kinase (PYK) isozymes. Human liver PYK contained numerous rheostat positions that tuned the apparent affinity for the substrate phosphoenolpyruvate (Kapp-PEP) across a wide range. In contrast, no functional rheostat positions were identified in Zymomonas mobilis PYK (ZmPYK). Further, the set of ZmPYK substitutions included an unusually large number that lacked measurable activity. We hypothesized that the inactive substitution variants had reduced protein stability, precluding detection of Kapp-PEP tuning. Using modified buffers, robust enzymatic activity was obtained for 19 previously-inactive ZmPYK substitution variants at three positions. Surprisingly, both previously-inactive and previously-active substitution variants all had Kapp-PEP values close to wild-type. Thus, none of the three positions were functional rheostat positions, and, unlike human liver PYK, ZmPYK's Kapp-PEP remained poorly tunable by single substitutions. To directly assess effects on stability, we performed thermal denaturation experiments for all ZmPYK substitution variants. Many diminished stability, two enhanced stability, and the three positions showed different thermal sensitivity to substitution, with one position acting as a "stability rheostat." The differences between the two PYK homologs raises interesting questions about the underlying mechanism(s) that permit functional tuning by single substitutions in some proteins but not in others.

Simultaneous enhancement of multiple functional properties using evolution-informed protein design

A major challenge in protein design is to augment existing functional proteins with multiple property enhancements. Altering several properties likely necessitates numerous primary sequence changes, and novel methods are needed to accurately predict combinations of mutations that maintain or enhance function. Models of sequence co-variation (e.g., EVcouplings), which leverage extensive information about various protein properties and activities from homologous protein sequences, have proven effective for many applications including structure determination and mutation effect prediction. We apply EVcouplings to computationally design variants of the model protein TEM-1 β-lactamase. Nearly all the 14 experimentally characterized designs were functional, including one with 84 mutations from the nearest natural homolog. The designs also had large increases in thermostability, increased activity on multiple substrates, and nearly identical structure to the wild type enzyme. This study highlights the efficacy of evolutionary models in guiding large sequence alterations to generate functional diversity for protein design applications.

Models and molecular mechanisms for trade-offs in the context of metabolism

Accumulating evidence for trade-offs involving metabolic traits has demonstrated their importance in the evolution of organisms. Metabolic models with different levels of complexity have already been considered when investigating mechanisms that explain various metabolic trade-offs. Here we provide a systematic review of modelling approaches that have been used to study and explain trade-offs between: (i) the kinetic properties of individual enzymes, (ii) rates of metabolic reactions, (iii) the rate and yield of metabolic pathways and networks, (iv) different metabolic objectives in single organisms and in metabolic communities, and (v) metabolic concentrations. In providing insights into the mechanisms underlying these five types of metabolic trade-offs obtained from constraint-based metabolic modelling, we emphasize the relationship of metabolic trade-offs to the classical black box Y-model that provides a conceptual explanation for resource acquisition-allocation trade-offs. In addition, we identify several pressing concerns and offer a perspective for future research in the identification and manipulation of metabolic trade-offs by relying on the toolbox provided by constraint-based metabolic modelling for single organisms and microbial communities.

Rational engineering S1' substrate binding pocket to enhance substrate specificity and catalytic activity of thermal-stable keratinase for efficient keratin degradation

This study reports the rational engineering of the S1' substrate-binding pocket of a thermally-stable keratinase from Pseudomonas aeruginosa 4-3 (4-3Ker) to improve substrate specificity to typical keratinase (K/C > 0.5) and catalytic activity without compromising thermal stability for efficient keratin degradation. Of 10 chosen mutation hotspots in the S1' substrate-binding pocket, the top three mutations M128R, A138V, and V142I showing the best catalytic activity and substrate specificity were identified. Their double and triple combinatorial mutants synergistically overcame limitations of single mutants, fabricating an excellent M128R/A138V/V142I triple mutant which displayed a 1.21-fold increase in keratin catalytic activity, 1.10-fold enhancement in keratin/casein activity ratio, and a 3.13 °C increase in half-inactivation temperature compared to 4-3Ker. Molecular dynamics simulations revealed enhanced flexibility of critical amino acid residues at the substrate access tunnel, improved global protein rigidity, and heightened hydrophobicity within the active site likely underpinned the increased catalytic activity and substrate specificity. Additionally, the triple mutant improved the feather degradation rate by 32.86 % over the wild-type, far exceeding commercial keratinase in substrate specificity and thermal stability. This study exemplified engineering a typical keratinase with enhanced substrate specificity, catalytic activity, and thermal stability from thermally-stable 4-3Ker, providing a more robust tool for feather degradation.

Understanding activity-stability tradeoffs in biocatalysts by enzyme proximity sequencing

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

Improvement in organic solvent resistance of keratinase BLk by directed evolution

Keratinase, a vital enzyme in hair degradation, requires enhanced stability for industrial applications in the harsh reaction environment used for keratin hydrolysis. Previous studies have focused on improving keratinase thermostability. In this study, directed evolution was applied to enhance the organic solvent stability of the keratinase BLk from Bacillus licheniformis. Three mutants were identified, exhibiting significant enhanced stability in various solvents, although no similar improvements were observed in terms of thermostability. The identified mutations were located on the enzyme surface. The half-lives of the D41A, A24E, and A24Q mutants increased by 47-, 63-, and 61-fold, respectively, in the presence of 50% (v/v) acetonitrile compared to that of the wild type (WT). Similarly, in the presence of 50% (v/v) acetone, the half-lives of these mutants increased by 22-, 27-, and 27-fold compared to that of the WT enzyme. Notably, the proteolytic activity of all the selected mutants was similar to that of the WT enzyme. Furthermore, molecular dynamics simulation was used to assess the possible reasons for enhanced solvent stability. These results suggest that heightened intramolecular interactions, such as hydrogen bonding and hydrophobic interactions, contribute to improved solvent tolerance. The mutants obtained in this study hold significant potential for industrial applications.

Multienzymatic Cascades and Nanomaterial Scaffolding-A Potential Way Forward for the Efficient Biosynthesis of Novel Chemical Products

Synthetic biology is touted as the next industrial revolution as it promises access to greener biocatalytic syntheses to replace many industrial organic chemistries. Here, it is shown to what synthetic biology can offer in the form of multienzyme cascades for the synthesis of the most basic of new materials-chemicals, including especially designer chemical products and their analogs. Since achieving this is predicated on dramatically expanding the chemical space that enzymes access, such chemistry will probably be undertaken in cell-free or minimalist formats to overcome the inherent toxicity of non-natural substrates to living cells. Laying out relevant aspects that need to be considered in the design of multi-enzymatic cascades for these purposes is begun. Representative multienzymatic cascades are critically reviewed, which have been specifically developed for the synthesis of compounds that have either been made only by traditional organic synthesis along with those cascades utilized for novel compound syntheses. Lastly, an overview of strategies that look toward exploiting bio/nanomaterials for accessing channeling and other nanoscale materials phenomena in vitro to direct novel enzymatic biosynthesis and improve catalytic efficiency is provided. Finally, a perspective on what is needed for this field to develop in the short and long term is presented.

Harnessing generative AI to decode enzyme catalysis and evolution for enhanced engineering

Enzymes, as paramount protein catalysts, occupy a central role in fostering remarkable progress across numerous fields. However, the intricacy of sequence-function relationships continues to obscure our grasp of enzyme behaviors and curtails our capabilities in rational enzyme engineering. Generative artificial intelligence (AI), known for its proficiency in handling intricate data distributions, holds the potential to offer novel perspectives in enzyme research. Generative models could discern elusive patterns within the vast sequence space and uncover new functional enzyme sequences. This review highlights the recent advancements in employing generative AI for enzyme sequence analysis. We delve into the impact of generative AI in predicting mutation effects on enzyme fitness, catalytic activity and stability, rationalizing the laboratory evolution of de novo enzymes, and decoding protein sequence semantics and their application in enzyme engineering. Notably, the prediction of catalytic activity and stability of enzymes using natural protein sequences serves as a vital link, indicating how enzyme catalysis shapes enzyme evolution. Overall, we foresee that the integration of generative AI into enzyme studies will remarkably enhance our knowledge of enzymes and expedite the creation of superior biocatalysts.

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.

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.

Improving the Thermostability of Thermomyces lanuginosus Lipase by Restricting the Flexibility of N-Terminus and C-Terminus Simultaneously via the 25-Loop Substitutions

(1) Lipases are catalysts widely applied in industrial fields. To sustain the harsh treatments in industries, optimizing lipase activities and thermal stability is necessary to reduce production loss. (2) The thermostability of Thermomyces lanuginosus lipase (TLL) was evaluated via B-factor analysis and consensus-sequence substitutions. Five single-point variants (K24S, D27N, D27R, P29S, and A30P) with improved thermostability were constructed via site-directed mutagenesis. (3) The optimal reaction temperatures of all the five variants displayed 5 °C improvement compared with TLL. Four variants, except D27N, showed enhanced residual activities at 80 °C. The melting temperatures of three variants (D27R, P29S, and A30P) were significantly increased. The molecular dynamics simulations indicated that the 25-loop (residues 24-30) in the N-terminus of the five variants generated more hydrogen bonds with surrounding amino acids; hydrogen bond pair D254-I255 preserved in the C-terminus of the variants also contributes to the improved thermostability. Furthermore, the newly formed salt-bridge interaction (R27…E56) in D27R was identified as a crucial determinant for thermostability. (4) Our study discovered that substituting residues from the 25-loop will enhance the stability of the N-terminus and C-terminus simultaneously, restrict the most flexible regions of TLL, and result in improved thermostability.

Harnessing Generative AI to Decode Enzyme Catalysis and Evolution for Enhanced Engineering

Enzymes, as paramount protein catalysts, occupy a central role in fostering remarkable progress across numerous fields. However, the intricacy of sequence-function relationships continues to obscure our grasp of enzyme behaviors and curtails our capabilities in rational enzyme engineering. Generative artificial intelligence (AI), known for its proficiency in handling intricate data distributions, holds the potential to offer novel perspectives in enzyme research. By applying generative models, we could discern elusive patterns within the vast sequence space and uncover new functional enzyme sequences. This review highlights the recent advancements in employing generative AI for enzyme sequence analysis. We delve into the impact of generative AI in predicting mutation effects on enzyme fitness, activity, and stability, rationalizing the laboratory evolution of de novo enzymes, decoding protein sequence semantics, and its applications in enzyme engineering. Notably, the prediction of enzyme activity and stability using natural enzyme sequences serves as a vital link, indicating how enzyme catalysis shapes enzyme evolution. Overall, we foresee that the integration of generative AI into enzyme studies will remarkably enhance our knowledge of enzymes and expedite the creation of superior biocatalysts.

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.

Improving the Thermostability of Serine Protease PB92 from Bacillus alcalophilus via Site-Directed Mutagenesis Based on Semi-Rational Design

Proteases have been widely employed in many industrial processes. In this work, we aimed to improve the thermostability of the serine protease PB92 from Bacillus alcalophilus to meet the high-temperature requirements of biotechnological treatments. Eight mutation sites (N18, S97-S101, E110, and R143) were identified, and 21 mutants were constructed from B-factor comparison and multiple sequence alignment and expressed via Bacillus subtilis. Among them, fifteen mutants exhibited increased half-life (t1/2) values at 65 °C (1.13-31.61 times greater than that of the wild type). Based on the composite score of enzyme activity and thermostability, six complex mutants were implemented. The t1/2 values of these six complex mutants were 2.12-10.05 times greater than that of the wild type at 65 °C. In addition, structural analysis revealed that the increased thermal stability of complex mutants may be related to the formation of additional hydrophobic interactions due to increased hydrophobicity and the decreased flexibility of the structure. In brief, the thermal stability of the complex mutants N18L/R143L/S97A, N18L/R143L/S99L, and N18L/R143L/G100A was increased 4-fold, which reveals application potential in industry.

Simultaneous enhancement of multiple functional properties using evolution-informed protein design

Designing optimized proteins is important for a range of practical applications. Protein design is a rapidly developing field that would benefit from approaches that enable many changes in the amino acid primary sequence, rather than a small number of mutations, while maintaining structure and enhancing function. Homologous protein sequences contain extensive information about various protein properties and activities that have emerged over billions of years of evolution. Evolutionary models of sequence co-variation, derived from a set of homologous sequences, have proven effective in a range of applications including structure determination and mutation effect prediction. In this work we apply one of these models (EVcouplings) to computationally design highly divergent variants of the model protein TEM-1 β-lactamase, and characterize these designs experimentally using multiple biochemical and biophysical assays. Nearly all designed variants were functional, including one with 84 mutations from the nearest natural homolog. Surprisingly, all functional designs had large increases in thermostability and most had a broadening of available substrates. These property enhancements occurred while maintaining a nearly identical structure to the wild type enzyme. Collectively, this work demonstrates that evolutionary models of sequence co-variation (1) are able to capture complex epistatic interactions that successfully guide large sequence departures from natural contexts, and (2) can be applied to generate functional diversity useful for many applications in protein design.

Engineering of a T7 Bacteriophage Endolysin Variant with Enhanced Amidase Activity

The therapeutic use of bacteriophage-encoded endolysins as enzybiotics has increased significantly in recent years due to the emergence of antibiotic resistant bacteria. Phage endolysins lyse the bacteria by targeting their cell wall. Various engineering strategies are commonly used to modulate or enhance the utility of therapeutic enzymes. This study employed a structure-guided mutagenesis approach to engineer a T7 bacteriophage endolysin (T7L) with enhanced amidase activity and lysis potency via replacement of a noncatalytic gating residue (His 37). Two H37 variants (H37A and H37K) were designed and characterized comprehensively using integrated biophysical and biochemical techniques to provide mechanistic insights into their structure-stability-dynamics-activity paradigms. Among the studied proteins, cell lysis data suggested that the obtained H37A variant exhibits amidase activity (∼35%) enhanced compared to that of wild-type T7 endolysin (T7L-WT). In contrast to this, the H37K variant is highly unstable, prone to aggregation, and less active. Comparison of the structure and dynamics of the H37A variant to those of T7L-WT evidenced that the alteration at the site of H37 resulted in long-range structural perturbations, attenuated the conformational heterogeneity, and quenched the microsecond to millisecond time scale motions. Stability analysis confirmed the altered stability of H37A compared to that of its WT counterpart. All of the obtained results established that the H37A variant enhances the lysis activity by regulating the stability-activity trade-off. This study provided deeper atomic level insights into the structure-function relationships of endolysin proteins, thus aiding researchers in the rational design of engineered endolysins with enhanced therapeutic properties.

Enhanced Thermostability and Molecular Insights for l-Asparaginase from Bacillus licheniformis via Structure- and Computation-Based Rational Design

l-Asparaginase has gained much attention for effectively treating acute lymphoblastic leukemia (ALL) and mitigating carcinogenic acrylamide in fried foods. Due to high-dose dependence for clinical treatment and low mitigation efficiency for thermal food processes caused by poor thermal stability, a method to achieve thermostable l-asparaginase has become a critical bottleneck. In this study, a rational design including free energy combined with structural and conservative analyses was applied to engineer the thermostability of l-asparaginase from Bacillus licheniformis (BlAsnase). Two enhanced thermostability mutants D172W and E207A were screened out by site-directed saturation mutagenesis. The double mutant D172W/E207A exhibited highly remarkable thermostability with a 65.8-fold longer half-life at 55 °C and 5 °C higher optimum reaction temperature and melting temperature (T_m) than those of wild-type BlAsnase. Further, secondary structure, sequence, molecular dynamics (MD), and 3D-structure analysis revealed that the excellent thermostability of the mutant D172W/E207A was on account of increased hydrophobicity and decreased flexibility, highly rigid structure, hydrophobic interactions, and favorable electrostatic potential. As the first report of rationally designing l-asparaginase with improved thermostability from B. licheniformis, this study offers a facile and efficient process to improve the thermostability of l-asparaginase for industrial applications.

Thermostability Improvement of L-Asparaginase from Acinetobacter soli via Consensus-Designed Cysteine Residue Substitution

To extend the application range of L-asparaginase in food pre-processing, the thermostability improvement of the enzyme is essential. Herein, two non-conserved cysteine residues with easily oxidized free sulfhydryl groups, Cys8 and Cys283, of Acinetobacter soli L-asparaginase (AsA) were screened out via consensus design. After saturation mutagenesis and combinatorial mutation, the mutant C8Y/C283Q with highly improved thermostability was obtained with a half-life of 361.6 min at 40 °C, an over 34-fold increase compared with that of the wild-type. Its melting temperature (T_m) value reaches 62.3 °C, which is 7.1 °C higher than that of the wild-type. Molecular dynamics simulation and structure analysis revealed the formation of new hydrogen bonds of Gln283 and the aromatic interaction of Tyr8 formed with adjacent residues, resulting in enhanced thermostability. The improvement in the thermostability of L-asparaginase could efficiently enhance its effect on acrylamide inhibition; the contents of acrylamide in potato chips were efficiently reduced by 86.50% after a mutant C8Y/C283Q treatment, which was significantly higher than the 59.05% reduction after the AsA wild-type treatment. In addition, the investigation of the mechanism behind the enhanced thermostability of AsA could further direct the modification of L-asparaginases for expanding their clinical and industrial applications.

Molecular Analysis of L-Asparaginases for Clarification of the Mechanism of Action and Optimization of Pharmacological Functions

L-asparaginases (EC 3.5.1.1) are a family of enzymes that catalyze the hydrolysis of L-asparagine to L-aspartic acid and ammonia. These proteins with different biochemical, physicochemical and pharmacological properties are found in many organisms, including bacteria, fungi, algae, plants and mammals. To date, asparaginases from E. coli and Dickeya dadantii (formerly known as Erwinia chrysanthemi) are widely used in hematology for the treatment of lymphoblastic leukemias. However, their medical use is limited by side effects associated with the ability of these enzymes to hydrolyze L-glutamine, as well as the development of immune reactions. To solve these issues, gene-editing methods to introduce amino-acid substitutions of the enzyme are implemented. In this review, we focused on molecular analysis of the mechanism of enzyme action and to optimize the antitumor activity.

Chromohalobacter salixigens Uronate Dehydrogenase: Directed Evolution for Improved Thermal Stability and Mutant CsUDH-inc X-ray Crystal Structure

Chromohalobacter salixigens contains a uronate dehydrogenase termed CsUDH that can convert uronic acids to their corresponding C1,C6-dicarboxy aldaric acids, an important enzyme reaction applicable for biotechnological use of sugar acids. To increase the thermal stability of this enzyme for biotechnological processes, directed evolution using gene family shuffling was applied, and the hits selected from 2-tier screening of a shuffled gene family library contained in total 16 mutations, only some of which when examined individually appreciably increased thermal stability. Most mutations, while having minimal or no effect on thermal stability when tested in isolation, were found to exhibit synergy when combined; CsUDH-inc containing all 16 mutations had ΔK _t ^0.5 +18 °C, such that k _cat was unaffected by incubation for 1 hr at ~70 °C. X-ray crystal structure of CsUDH-inc showed tight packing of the mutated residue side-chains, and comparison of rescaled B-values showed no obvious differences between wild type and mutant structures. Activity of CsUDH-inc was severely depressed on glucuronic and galacturonic acids. Combining select combinations of only three mutations resulted in good or comparable activity on these uronic acids, while maintaining some improved thermostability with ΔK _t ^0.5 ~+ 10 °C, indicating potential to further thermally optimize CsUDH for hyperthermophilic reaction environments.

Therapeutic enzyme engineering using a generative neural network

Enhancing the potency of mRNA therapeutics is an important objective for treating rare diseases, since it may enable lower and less-frequent dosing. Enzyme engineering can increase potency of mRNA therapeutics by improving the expression, half-life, and catalytic efficiency of the mRNA-encoded enzymes. However, sequence space is incomprehensibly vast, and methods to map sequence to function (computationally or experimentally) are inaccurate or time-/labor-intensive. Here, we present a novel, broadly applicable engineering method that combines deep latent variable modelling of sequence co-evolution with automated protein library design and construction to rapidly identify metabolic enzyme variants that are both more thermally stable and more catalytically active. We apply this approach to improve the potency of ornithine transcarbamylase (OTC), a urea cycle enzyme for which loss of catalytic activity causes a rare but serious metabolic disease.

Insight into the broadened substrate scope of nitrile hydratase by static and dynamic structure analysis

Mutations of two gating residues at the substrate access tunnel entrance direct the substrate scope of NHases.

Engineering of the thermophilic nitrile hydratase from Pseudonocardia thermophila JCM3095 for large-scale nicotinamide production based on sequence-activity relationships

The green biocatalyst nitrile hydratase (NHase) is able to bio-transform 3-cyanopyridine into nicotinamide. As the NHase reaction is exothermic, an enzyme with high activity and stability is needed for nicotinamide production. In this study, we used sequence analysis and site-directed mutagenesis to generate a mutant of thermophilic NHase from Pseudonocardia thermophila JCM3095 with substantially enhanced activity and developed a powerful process for nicotinamide bio-production. The specific activity of αF126Y/αF168Y mutant was successfully increased by 3.98-fold over that of the wild-type enzyme. The half-life of such mutant was longer than 2 h, which was comparable to its parent enzyme. The relative activity of the αF126Y/αF168Y mutant after treatment with 1 M 3-cyanopyridine and 2 M nicotinamide was 73.2% and 63.7%, respectively, showing minor loss of its original stability. Structural analysis demonstrated that hydrogen bonds at the active site and α-β subunit interface of the NHase contribute to the improved activity and the maintenance of stability. Escherichia coli transformant harboring the mutant NHase was used for nicotinamide bio-production, yielding a nicotinamide productivity of 251.1 g/(L·h), which is higher than the productivity obtained using other NHase-containing strains and transformants. The newly established variant is therefore a promising alternative for the industrial production of nicotinamides.

Reconstruction of the glutamate decarboxylase system in Lactococcus lactis for biosynthesis of food-grade γ-aminobutyric acid

Gamma-aminobutyric acid (GABA), an important bioactive compound, is synthesized through the decarboxylation of L-glutamate (L-Glu) by glutamate decarboxylase (GAD). The use of lactic acid bacteria (LAB) as catalysts opens interesting avenues for the biosynthesis of food-grade GABA. However, a key obstacle involved in the improvement of GABA production is how to resolve the discrepancy of optimal pH between the intracellular GAD activity and cell growth. In this work, a potential GAD candidate (LpGadB) from Lactobacillus plantarum was heterologously expressed in Escherichia coli. Recombinant LpGadB existed as a homodimer under the native conditions with a molecular mass of 109.6 kDa and exhibited maximal activity at 40°C and pH 5.0. The K_m value and catalytic efficiency (k_cat/K_m) of LpGadB for L-Glu was 21.33 mM and 1.19 mM^-1s^-1, respectively, with the specific activity of 26.67 μM/min/mg protein. Subsequently, four C-terminally truncated LpGadB mutants (GadB_ΔC10, GadB_ΔC11, GadB_ΔC12, GadB_ΔC13) were constructed based on homology modeling. Among them, the mutant GadB_ΔC11 with highest catalytic activity at near-neutral pH values was selected. In further, the GadB_ΔC11 and Glu/GABA antiporter (GadC) of Lactococcus lactis were co-overexpressed in the host L. lactis NZ3900. Finally, after 48 h of batch fermentation, the engineered strain L. lactis NZ3900/pNZ8149-gadB_ΔC11C yielded GABA concentration up to 33.52 g/L by applying a two-stage pH control strategy. Remarkably, this is the highest yield obtained to date for GABA from fermentation with L. lactis as a microbial cell factory.Key points• The GadB from L. plantarum was heterologously expressed in E. coli and biochemically characterized.• Deletion of the C-plug in GadB shifted its pH-dependent activity toward a higher pH.• Reconstructing the GAD system of L. lactis is an effective approach for improving its GABA production.

Resource uptake and the evolution of moderately efficient enzymes

Enzymes speed up reactions that would otherwise be too slow to sustain the metabolism of selfreplicators. Yet, most enzymes seem only moderately efficient, exhibiting kinetic parameters orders of magnitude lower than their expected physically achievable maxima and spanning over surprisingly large ranges of values. Here, we question how these parameters evolve using a mechanistic model where enzyme efficiency is a key component of individual competition for resources. We show that kinetic parameters are under strong directional selection only up to a point, above which enzymes appear to evolve under near-neutrality, thereby confirming the qualitative observation of other modeling approaches. While the existence of a large fitness plateau could potentially explain the extensive variation in enzyme features reported, we show using a population genetics model that such a widespread distribution is an unlikely outcome of evolution on a common landscape, as mutation–selection–drift balance occupy a narrow area even when very moderate biases towards lower efficiency are considered. Instead, differences in the evolutionary context encountered by each enzyme should be involved, such that each evolves on an individual, unique landscape. Our results point to drift and effective population size playing an important role, along with the kinetics of nutrient transporters, the tolerance to high concentrations of intermediate metabolites, and the reversibility of reactions. Enzyme concentration also shapes selection on kinetic parameters, but we show that the joint evolution of concentration and efficiency does not yield extensive variance in evolutionary outcomes when documented costs to protein expression are applied.

Circumventing the side effects of L-asparaginase

L-asparaginase is an enzyme that catalyzes the degradation of asparagine and successfully used in the treatment of acute lymphoblastic leukemia. L-asparaginase toxicity is either related to hypersensitivity to the foreign protein or to a secondary L-glutaminase activity that causes inhibition of protein synthesis. PEGylated versions have been incorporated into the treatment protocols to reduce immunogenicity and an alternative L-asparaginase derived from Dickeya chrysanthemi is used in patients with anaphylactic reactions to the E. coli L-asparaginase. Alternative approaches commonly explore new sources of the enzyme as well as the use of protein engineering techniques to create less immunogenic, more stable variants with lower L-glutaminase activity. This article reviews the main strategies used to overcome L-asparaginase shortcomings and introduces recent tools that can be used to create therapeutic enzymes with improved features.

An anchoring residue adjacent to the substrate access tunnel entrance of a nitrile hydratase directs its catalytic activity towards 3-cyanopyridine

The residue βGlu50 located adjacent to the substrate access tunnel entrance of the nitrile hydratase from Pseudonocardia thermophila JCM3095 acts as an anchoring residue that directs the enzymatic activity.

Ancestral sequence reconstruction produces thermally stable enzymes with mesophilic enzyme-like catalytic properties

Enzymes have high catalytic efficiency and low environmental impact, and are therefore potentially useful tools for various industrial processes. Crucially, however, natural enzymes do not always have the properties required for specific processes. It may be necessary, therefore, to design, engineer, and evolve enzymes with properties that are not found in natural enzymes. In particular, the creation of enzymes that are thermally stable and catalytically active at low temperature is desirable for processes involving both high and low temperatures. In the current study, we designed two ancestral sequences of 3-isopropylmalate dehydrogenase by an ancestral sequence reconstruction technique based on a phylogenetic analysis of extant homologous amino acid sequences. Genes encoding the designed sequences were artificially synthesized and expressed in Escherichia coli. The reconstructed enzymes were found to be slightly more thermally stable than the extant thermophilic homologue from Thermus thermophilus. Moreover, they had considerably higher low-temperature catalytic activity as compared with the T. thermophilus enzyme. Detailed analyses of their temperature-dependent specific activities and kinetic properties showed that the reconstructed enzymes have catalytic properties similar to those of mesophilic homologues. Collectively, our study demonstrates that ancestral sequence reconstruction can produce a thermally stable enzyme with catalytic properties adapted to low-temperature reactions.

Single Residue Substitution at N-Terminal Affects Temperature Stability and Activity of L2 Lipase

Rational design is widely employed in protein engineering to tailor wild-type enzymes for industrial applications. The typical target region for mutation is a functional region like the catalytic site to improve stability and activity. However, few have explored the role of other regions which, in principle, have no evident functionality such as the N-terminal region. In this study, stability prediction software was used to identify the critical point in the non-functional N-terminal region of L2 lipase and the effects of the substitution towards temperature stability and activity were determined. The results showed 3 mutant lipases: A8V, A8P and A8E with 29% better thermostability, 4 h increase in half-life and 6.6 °C higher thermal denaturation point, respectively. A8V showed 1.6-fold enhancement in activity compared to wild-type. To conclude, the improvement in temperature stability upon substitution showed that the N-terminal region plays a role in temperature stability and activity of L2 lipase.

Criticality in the conformational phase transition among self-similar groups in intrinsically disordered proteins: Probed by salt-bridge dynamics

Intrinsically disordered proteins (IDP) serve as one of the key components in the global proteome. In contrast to globular proteins, they harbor an enormous amount of physical flexibility enforcing them to be retained in conformational ensembles rather than stable folds. Previous studies in an aligned direction have revealed the importance of transient dynamical phenomena like that of salt-bridge formation in IDPs to support their physical flexibility and have further highlighted their functional relevance. For this characteristic flexibility, IDPs remain amenable and accessible to different ordered binding partners, supporting their potential multi-functionality. The current study further addresses this complex structure-functional interplay in IDPs using phase transition dynamics to conceptualize the underlying (avalanche type) mechanism of their being distributed across and hopping around degenerate structural states (conformational ensembles). For this purpose, extensive molecular dynamics simulations have been done and the data analyzed from a statistical physics perspective. Investigation of the plausible scope of 'self-organized criticality' (SOC) to fit into the complex dynamics of IDPs was found to be assertive, relating the conformational degeneracy of these proteins to their functional multiplicity. In accordance with the transient nature of 'salt-bridge dynamics', the study further uses it as a probe to explain the structural basis of the proposed criticality in the conformational phase transition among self-similar groups in IDPs. The analysis reveal scale-invariant self-similar fractal geometries in the structural conformations of different IDPs. The insights from the study has the potential to be extended further to benefit structural tinkering of IDPs in their functional characterization and drugging.

Evolutionary redesign of the lysosomal enzyme arylsulfatase A increases efficacy of enzyme replacement therapy for metachromatic leukodystrophy

Protein engineering is a means to optimize protein therapeutics developed for the treatment of so far incurable diseases including cancers and genetic disorders. Here we report on an engineering approach in which we successfully increased the catalytic rate constant of an enzyme that is presently evaluated in enzyme replacement therapies (ERT) of a lysosomal storage disease (LSD). Although ERT is a treatment option for many LSDs, outcomes are lagging far behind expectations for most of them. This has been ascribed to insufficient enzyme activities accumulating in tissues difficult to target such as brain and peripheral nerves. We show for human arylsulfatase A (hARSA) that the activity of a therapeutic enzyme can be substantially increased by reversing activity-diminishing and by inserting activity-promoting amino acid substitutions that had occurred in the evolution of hominids and non-human mammals, respectively. The potential of this approach, here designated as evolutionary redesign, was highlighted by the observation that murinization of only 1 or 3 amino acid positions increased the hARSA activity 3- and 5-fold, with little impact on stability, respectively. The two kinetically optimized hARSA variants showed no immunogenic potential in ERT of a humanized ARSA knockout mouse model of metachromatic leukodystrophy (MLD) and reduced lysosomal storage of kidney, peripheral and central nervous system up to 3-fold more efficiently than wild-type hARSA. Due to their safety profile and higher therapeutic potential the engineered hARSA variants might represent major advances for future enzyme-based therapies of MLD and stimulate analogous approaches for other enzyme therapeutics.

Exploring the therapeutic potential of modern and ancestral phenylalanine/tyrosine ammonia-lyases as supplementary treatment of hereditary tyrosinemia

Phenylalanine/tyrosine ammonia-lyases (PAL/TALs) have been approved by the FDA for treatment of phenylketonuria and may harbour potential for complementary treatment of hereditary tyrosinemia Type I. Herein, we explore ancestral sequence reconstruction as an enzyme engineering tool to enhance the therapeutic potential of PAL/TALs. We reconstructed putative ancestors from fungi and compared their catalytic activity and stability to two modern fungal PAL/TALs. Surprisingly, most putative ancestors could be expressed as functional tetramers in Escherichia coli and thus retained their ability to oligomerize. All ancestral enzymes displayed increased thermostability compared to both modern enzymes, however, the increase in thermostability was accompanied by a loss in catalytic turnover. One reconstructed ancestral enzyme in particular could be interesting for further drug development, as its ratio of specific activities is more favourable towards tyrosine and it is more thermostable than both modern enzymes. Moreover, long-term stability assessment showed that this variant retained substantially more activity after prolonged incubation at 25 °C and 37 °C, as well as an increased resistance to incubation at 60 °C. Both of these factors are indicative of an extended shelf-life of biopharmaceuticals. We believe that ancestral sequence reconstruction has potential for enhancing the properties of enzyme therapeutics, especially with respect to stability. This work further illustrates that resurrection of putative ancestral oligomeric proteins is feasible and provides insight into the extent of conservation of a functional oligomerization surface area from ancestor to modern enzyme.

Insulin fibrillation: toward strategies for attenuating the process

The environmental factors affecting the rate of insulin fibrillation. The factors are representative.

Distinct roles of an ionic interaction holding an alpha-helix with catalytic Asp and a beta-strand with catalytic His in a hyperthermophilic esterase EstE1 and a mesophilic esterase rPPE

An ionic interaction that holds an α-helix and a β-strand on which catalytic Asp and His residues are located, respectively, is conserved in a hyperthermophilic esterase EstE1 (optimum temperature 70 °C) and a mesophilic esterase rPPE (optimum temperature 50 °C). We investigated the role of an ionic interaction between E258 and R275 in EstE1 and that between E263 and R280 in rPPE in active-site stability of serine esterases adapted to different temperatures. Ala substitutions caused a 5-10 °C decrease in the optimum temperature of both EstE1 and rPPE mutants. Surprisingly, disruption of the ionic interaction caused larger effects on the conformational flexibility of EstE1 mutants despite their rigid structures, whereas the disruption had fewer effects on the thermal stability of EstE1 mutants at 60-70 °C, as the structure of EstE1 was adapted to high temperatures. In contrast, mesophilic rPPE mutants showed dramatic decreases in thermal stability at 40-50 °C, but less changes in conformational flexibility because of their inherently flexible structures. The results of this study suggest that the ionic interaction between the α-helix with catalytic Asp and the β-strand with catalytic His plays an important role in the active-site conformation of EstE1 and rPPE, with larger effects on the conformational flexibility of hyperthermophilic EstE1 and the thermal stability of mesophilic rPPE.

Establishment of mesophilic-like catalytic properties in a thermophilic enzyme without affecting its thermal stability

Thermophilic enzymes are generally more thermally stable but are less active at moderate temperatures than are their mesophilic counterparts. Thermophilic enzymes with improved low-temperature activity that retain their high stability would serve as useful tools for industrial processes especially when robust biocatalysts are required. Here we show an effective way to explore amino acid substitutions that enhance the low-temperature catalytic activity of a thermophilic enzyme, based on a pairwise sequence comparison of thermophilic/mesophilic enzymes. One or a combination of amino acid(s) in 3-isopropylmalate dehydrogenase from the extreme thermophile Thermus thermophilus was/were substituted by a residue(s) found in the Escherichia coli enzyme at the same position(s). The best mutant, which contained three amino acid substitutions, showed a 17-fold higher specific activity at 25 °C compared to the original wild-type enzyme while retaining high thermal stability. The kinetic and thermodynamic parameters of the mutant showed similar patterns along the reaction coordinate to those of the mesophilic enzyme. We also analyzed the residues at the substitution sites from a structural and phylogenetic point of view.

Enhancing the Thermostability of Highly Active and Glucose-Tolerant β-Glucosidase Ks5A7 by Directed Evolution for Good Performance of Three Properties

A high-performance β-glucosidase for efficient cellulose hydrolysis needs to excel in thermostability, catalytic efficiency, and resistance to glucose inhibition. However, it is challenging to achieve superb properties in all three aspects in a single enzyme. In this study, a hyperactive and glucose-tolerant β-glucosidase Ks5A7 was employed as the starting point. Four rounds of random mutagenesis were then performed, giving rise to a thermostable mutant 4R1 with five amino acid substitutions. The half-life of 4R1 at 50 °C is 8640-fold that of Ks5A7 (144 h vs 1 min). Meanwhile, 4R1 had a higher specific activity (374.26 vs 243.18 units·mg^-1) than the wild type with a similar glucose tolerance. When supplemented to Celluclast 1.5L, the mutant significantly enhanced the hydrolysis of pretreated sugar cane bagasse, improving the released glucose concentration by 44%. With excellent performance in thermostability, activity, and glucose tolerance, 4R1 will serve as an exceptional catalyst for industrial applications.

In silico-designed lignin peroxidase from Phanerochaete chrysosporium shows enhanced acid stability for depolymerization of lignin

BACKGROUND

The lignin peroxidase isozyme H8 from the white-rot fungus Phanerochaete chrysosporium (LiPH8) demonstrates a high redox potential and can efficiently catalyze the oxidation of veratryl alcohol, as well as the degradation of recalcitrant lignin. However, native LiPH8 is unstable under acidic pH conditions. This characteristic is a barrier to lignin depolymerization, as repolymerization of phenolic products occurs simultaneously at neutral pH. Because repolymerization of phenolics is repressed at acidic pH, a highly acid-stable LiPH8 could accelerate the selective depolymerization of recalcitrant lignin.

RESULTS

The engineered LiPH8 was in silico designed through the structural superimposition of surface-active site-harboring LiPH8 from Phanerochaete chrysosporium and acid-stable manganese peroxidase isozyme 6 (MnP6) from Ceriporiopsis subvermispora. Effective salt bridges were probed by molecular dynamics simulation and changes to Gibbs free energy following mutagenesis were predicted, suggesting promising variants with higher stability under extremely acidic conditions. The rationally designed variant, A55R/N156E-H239E, demonstrated a 12.5-fold increased half-life under extremely acidic conditions, 9.9-fold increased catalytic efficiency toward veratryl alcohol, and a 7.8-fold enhanced lignin model dimer conversion efficiency compared to those of native LiPH8. Furthermore, the two constructed salt bridges in the variant A55R/N156E-H239E were experimentally confirmed to be identical to the intentionally designed LiPH8 variant using X-ray crystallography (PDB ID: 6A6Q).

CONCLUSION

Introduction of strong ionic salt bridges based on computational design resulted in a LiPH8 variant with markedly improved stability, as well as higher activity under acidic pH conditions. Thus, LiPH8, showing high acid stability, will be a crucial player in biomass valorization using selective depolymerization of lignin.

Coevolution of both Thermostability and Activity of Polyphosphate Glucokinase from Thermobifida fusca YX

Thermostability and specific activity of enzymes are two of the most important properties for industrial biocatalysts. Here, we developed a petri dish-based double-layer high-throughput screening (HTS) strategy for rapid identification of desired mutants of polyphosphate glucokinase (PPGK) from a thermophilic actinobacterium, Thermobifida fusca YX, with both enhanced thermostability and activity. Escherichia coli colonies representing a PPGK mutant library were grown on the first-layer Phytagel-based plates, which can remain solid for 1 h, even at heat treatment temperatures of more than 100°C. The second layer that was poured on the first layer contained agarose, substrates, glucose 6-phosphate dehydrogenase (G6PDH), the redox dye tetranitroblue tetrazolium (TNBT), and phenazine methosulfate. G6PDH was able to oxidize the product from the PPGK-catalyzed reaction and generate NADH, which can be easily examined by a TNBT-based colorimetric assay. The best mutant obtained after four rounds of directed evolution had a 7,200-fold longer half-life at 55°C, 19.8°C higher midpoint of unfolding temperature (T_m ), and a nearly 3-fold enhancement in specific activities compared to those of the wild-type PPGK. The best mutant was used to produce 9.98 g/liter myo-inositol from 10 g/liter glucose, with a theoretical yield of 99.8%, along with two other hyperthermophilic enzymes at 70°C. This PPGK mutant featuring both great thermostability and high activity would be useful for ATP-free production of glucose 6-phosphate or its derived products.IMPORTANCE Polyphosphate glucokinase (PPGK) is an enzyme that transfers a terminal phosphate group from polyphosphate to glucose, producing glucose 6-phosphate. A petri dish-based double-layer high-throughput screening strategy was developed by using ultrathermostable Phytagel as the first layer instead of agar or agarose, followed by a redox dye-based assay for rapid identification of ultrathermostable PPGK mutants. The best mutant featuring both great thermostability and high activity could produce glucose 6-phosphate from glucose and polyphosphate without in vitro ATP regeneration.