Computational library design for increasing haloalkane dehalogenase stability

Unlocking the potential of enzyme engineering via rational computational design strategies

Enzymes play a pivotal role in various industries by enabling efficient, eco-friendly, and sustainable chemical processes. However, the low turnover rates and poor substrate selectivity of enzymes limit their large-scale applications. Rational computational enzyme design, facilitated by computational algorithms, offers a more targeted and less labor-intensive approach. There has been notable advancement in employing rational computational protein engineering strategies to overcome these issues, it has not been comprehensively reviewed so far. This article reviews recent developments in rational computational enzyme design, categorizing them into three types: structure-based, sequence-based, and data-driven machine learning computational design. Case studies are presented to demonstrate successful enhancements in catalytic activity, stability, and substrate selectivity. Lastly, the article provides a thorough analysis of these approaches, highlights existing challenges and potential solutions, and offers insights into future development directions.

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

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

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.

Empowering Protein Engineering through Recombination of Beneficial Substitutions

Directed evolution stands as a seminal technology for generating novel protein functionalities, a cornerstone in biocatalysis, metabolic engineering, and synthetic biology. Today, with the development of various mutagenesis methods and advanced analytical machines, the challenge of diversity generation and high-throughput screening platforms is largely solved, and one of the remaining challenges is: how to empower the potential of single beneficial substitutions with recombination to achieve the epistatic effect. This review overviews experimental and computer-assisted recombination methods in protein engineering campaigns. In addition, integrated and machine learning-guided strategies were highlighted to discuss how these recombination approaches contribute to generating the screening library with better diversity, coverage, and size. A decision tree was finally summarized to guide the further selection of proper recombination strategies in practice, which was beneficial for accelerating protein engineering.

High-Throughput Screening Techniques for the Selection of Thermostable Enzymes

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

Engineering Enzymes for Environmental Sustainability

The development and implementation of sustainable catalytic technologies is key to delivering our net-zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, polyethylene terephthalate (PET). Finally, biocatalytic approaches for accessing petroleum-based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of cleaner and more efficient chemical industry.

Engineering Enzymes for Environmental Sustainability

The development and implementation of sustainable catalytic technologies is key to delivering our net-zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2 ) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, polyethylene terephthalate (PET). Finally, biocatalytic approaches for accessing petroleum-based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of cleaner and more efficient chemical industry.

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.

Impact of organic solvents on the catalytic performance of halohydrin dehalogenase

Biocatalytic transformations in organic synthesis often require the use of organic solvents to improve substrate solubility and promote the product formation. Halohydrin dehalogenases (HHDHs) are enzymes that catalyze the formation and conversion of epoxides, important synthetic class of compounds that are often sparingly soluble in water and prone to hydrolysis. In this study, the activity, stability, and enantioselectivity of HHDH from Agrobacterium radiobacter AD1 (HheC) in form of cell-free extract were evaluated in various aqueous-organic media. A correlation was discovered between the enzyme activity in the ring-closure reaction and logP of the solvent. Knowledge of such a relationship makes biocatalysis with organic solvents more predictable, which may reduce the need to experiment with a variety of solvents in the future. The results revealed a high enzyme compatibility with hydrophobic solvents (e.g., n-heptane) in terms of activity and stability. Regarding the HHDH applicability in an organic medium, inhibitions by a number of solvents (e.g., THF, toluene, chloroform) proved to be a more challenging problem than the protein stability, especially in the ring-opening reaction, thus suggesting which solvents should be avoided. In addition, solvent tolerance of the thermostable variant ISM-4 was also evaluated, revealing increased stability and to a lesser extent enantioselectivity compared to the wild-type. This is the first time such a systematic analysis has been reported, giving insight into the behavior of HHDHs in nonconventional media and opening new opportunities for the future biocatalytic applications. KEY POINTS: • HheC performs better in the presence of hydrophobic than hydrophilic solvents. • Enzyme activity in the PNSHH ring-closure reaction is a function of the logP. • Thermostability of ISM-4 variant is accompanied by superior solvent tolerance.

Transient binding sites at the surface of haloalkane dehalogenase LinB as locations for fine-tuning enzymatic activity

The haloalkane dehalogenase LinB is a well-known enzyme that contains buried active site and is used for many modelling studies. Using classical molecular dynamics simulations of enzymes and substrates, we searched for transient binding sites on the surface of the LinB protein by calculating maps of enzyme-ligand interactions that were then transformed into sparse matrices. All residues considered as functionally important for enzyme performance (e.g., tunnel entrances) were excluded from the analysis to concentrate rather on non-obvious surface residues. From a set of 130 surface residues, twenty-six were proposed as a promising improvement of enzyme performance. Eventually, based on rational selection and filtering out the potentially unstable mutants, a small library of ten mutants was proposed to validate the possibility of fine-tuning the LinB protein. Nearly half of the predicted mutant structures showed improved activity towards the selected substrates, which demonstrates that the proposed approach could be applied to identify non-obvious yet beneficial mutations for enzyme performance especially when obvious locations have already been explored.

Improving Both the Thermostability and Catalytic Efficiency of Phospholipase D from Moritella sp. JT01 through Disulfide Bond Engineering Strategy

Mining of Phospholipase D (PLD) with high activity and stability has attracted strong interest for investigation. A novel PLD from marine Moritella sp. JT01 (MsPLD) was biochemically and structurally characterized in our previous study; however, the short half-life time (t_1/2) under its optimum reaction temperature seriously hampered its further applications. Herein, the disulfide bond engineering strategy was applied to improve its thermostability. Compared with wild-type MsPLD, mutant S148C-T206C/D225C-A328C with the addition of two disulfide bonds exhibited a 3.1-fold t_1/2 at 35 °C and a 5.7 °C increase in melting temperature (T_m). Unexpectedly, its specific activity and catalytic efficiency (k_cat/K_m) also increased by 22.7% and 36.5%, respectively. The enhanced activity might be attributed to an increase in the activation entropy by displacing more water molecules by the transition state. The results of molecular dynamics simulations (MD) revealed that the introduction of double disulfide bonds rigidified the global structure of the mutant, which might cause the enhanced thermostability. Finally, the synthesis capacity of the mutant to synthesize phosphatidic acid (PA) was evaluated. The conversion rate of PA reached about 80% after 6 h reaction with wild-type MsPLD but reached 78% after 2 h with mutant S148C-T206C/D225C-A328C, which significantly reduced the time needed for the reaction to reach equilibrium. The present results pave the way for further application of MsPLD in the food and pharmaceutical industries.

Bioprospecting of microbial enzymes: current trends in industry and healthcare

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

Structural-Based Modeling in Protein Engineering. A Must Do

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

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

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

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

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

Robust ω-Transaminases by Computational Stabilization of the Subunit Interface

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

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

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

Interference with Pseudomonas aeruginosa Quorum Sensing and Virulence by the Mycobacterial Pseudomonas Quinolone Signal Dioxygenase AqdC in Combination with the N-Acylhomoserine Lactone Lactonase QsdA

The nosocomial pathogen Pseudomonas aeruginosa regulates its virulence via a complex quorum sensing network, which, besides N-acylhomoserine lactones, includes the alkylquinolone signal molecules 2-heptyl-3-hydroxy-4(1H)-quinolone (Pseudomonas quinolone signal [PQS]) and 2-heptyl-4(1H)-quinolone (HHQ). Mycobacteroides abscessus subsp. abscessus, an emerging pathogen, is capable of degrading the PQS and also HHQ. Here, we show that although M. abscessus subsp. abscessus reduced PQS levels in coculture with P. aeruginosa PAO1, this did not suffice for quenching the production of the virulence factors pyocyanin, pyoverdine, and rhamnolipids. However, the levels of these virulence factors were reduced in cocultures of P. aeruginosa PAO1 with recombinant M. abscessus subsp. massiliense overexpressing the PQS dioxygenase gene aqdC of M. abscessus subsp. abscessus, corroborating the potential of AqdC as a quorum quenching enzyme. When added extracellularly to P. aeruginosa cultures, AqdC quenched alkylquinolone and pyocyanin production but induced an increase in elastase levels. When supplementing P. aeruginosa cultures with QsdA, an enzyme from Rhodococcus erythropolis which inactivates N-acylhomoserine lactone signals, rhamnolipid and elastase levels were quenched, but HHQ and pyocyanin synthesis was promoted. Thus, single quorum quenching enzymes, targeting individual circuits within a complex quorum sensing network, may also elicit undesirable regulatory effects. Supernatants of P. aeruginosa cultures grown in the presence of AqdC, QsdA, or both enzymes were less cytotoxic to human epithelial lung cells than supernatants of untreated cultures. Furthermore, the combination of both aqdC and qsdA in P. aeruginosa resulted in a decline of Caenorhabditis elegans mortality under P. aeruginosa exposure.

Stabilization of cyclohexanone monooxygenase by computational and experimental library design

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

FireProt: web server for automated design of thermostable proteins

There is a continuous interest in increasing proteins stability to enhance their usability in numerous biomedical and biotechnological applications. A number of in silico tools for the prediction of the effect of mutations on protein stability have been developed recently. However, only single-point mutations with a small effect on protein stability are typically predicted with the existing tools and have to be followed by laborious protein expression, purification, and characterization. Here, we present FireProt, a web server for the automated design of multiple-point thermostable mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen tools and three protein engineering strategies for making reliable protein designs. The server is complemented with interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable mutants. FireProt is freely available at http://loschmidt.chemi.muni.cz/fireprot.

Experimental Protocols for Generating Focused Mutant Libraries and Screening for Thermostable Proteins

Many proteins are rapidly deactivated when exposed to high or even ambient temperatures. This cannot only impede the study of a particular protein, but also is one of the major reasons why enzyme catalysis is still widely unable to compete with established chemical processes. Furthermore, differences in protein stability are a challenge in synthetic biology, when individual modules prove to be incompatible. The targeted stabilization of proteins can overcome these hurdles, and protein engineering techniques are more and more reliably supported by computational chemistry tools. Accordingly, algorithms to predict the differences in folding energy of a mutant compared to the wild-type, ΔΔG^fold, are used in the highly successful FRESCO workflow. The resulting single mutant prediction library consists typically of a few hundred amino acid exchanges, and after combining the most successful hits we so far obtained stabilized mutants which exhibited increases in apparent melting temperature of 20-35°C and showed vastly increased half-lives, as well as resistance to cosolvents. Here, we report a detailed protocol to generate these mutant libraries experimentally, covering the entire workflow from primer design, through mutagenesis, protein production and screening, to mutation combination strategies. The individual parts of the method are furthermore applicable to many other scenarios besides protein stabilization, and these protocols are valuable for any project requiring individual or semi high-throughput site-directed mutagenesis, protein expression and purification, or generation of mutant combination libraries.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

FoldX as Protein Engineering Tool: Better Than Random Based Approaches?

Improving protein stability is an important goal for basic research as well as for clinical and industrial applications but no commonly accepted and widely used strategy for efficient engineering is known. Beside random approaches like error prone PCR or physical techniques to stabilize proteins, e.g. by immobilization, in silico approaches are gaining more attention to apply target-oriented mutagenesis. In this review different algorithms for the prediction of beneficial mutation sites to enhance protein stability are summarized and the advantages and disadvantages of FoldX are highlighted. The question whether the prediction of mutation sites by the algorithm FoldX is more accurate than random based approaches is addressed.

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

The ability to stabilize enzymes and other proteins has wide-ranging applications. Most protocols for enhancing enzyme stability require multiple rounds of high-throughput screening of mutant libraries and provide only modest improvements of stability. Here, we describe a computational library design protocol that can increase enzyme stability by 20-35 °C with little experimental screening, typically fewer than 200 variants. This protocol, termed FRESCO, scans the entire protein structure to identify stabilizing disulfide bonds and point mutations, explores their effect by molecular dynamics simulations, and provides mutant libraries with variants that have a good chance (>10%) to exhibit enhanced stability. After experimental verification, the most effective mutations are combined to produce highly robust enzymes.

Engineering more stable proteins

The dynamic native, functional folded forms of proteins are unstable mainly because they readily unfold into flexible unstructured forms.

Protein Engineering: Past, Present, and Future

The last decade has seen a dramatic increase in the utilization of enzymes as green and sustainable (bio)catalysts in pharmaceutical and industrial applications. This trend has to a significant degree been fueled by advances in scientists' and engineers' ability to customize native enzymes by protein engineering. A review of the literature quickly reveals the tremendous success of this approach; protein engineering has generated enzyme variants with improved catalytic activity, broadened or altered substrate specificity, as well as raised or reversed stereoselectivity. Enzymes have been tailored to retain activity at elevated temperatures and to function in the presence of organic solvents, salts and pH values far from physiological conditions. However, readers unfamiliar with the field will soon encounter the confusingly large number of experimental techniques that have been employed to accomplish these engineering feats. Herein, we use history to guide a brief overview of the major strategies for protein engineering-past, present, and future.

Comparison of Five Protein Engineering Strategies for Stabilizing an α/β-Hydrolase

A review of the previous stabilization of α/β-hydrolase fold enzymes revealed many different strategies, but no comparison of strategies on the same enzyme. For this reason, we compared five strategies to identify stabilizing mutations in a model α/β-hydrolase fold enzyme, salicylic acid binding protein 2, to reversible denaturation by urea and to irreversible denaturation by heat. The five strategies included one location agnostic approach (random mutagenesis using error-prone polymerase chain reaction), two structure-based approaches [computational design (Rosetta, FoldX) and mutation of flexible regions], and two sequence-based approaches (addition of proline at locations where a more stable homologue has proline and mutation to consensus). All strategies identified stabilizing mutations, but the best balance of success rate, degree of stabilization, and ease of implementation was mutation to consensus. A web-based automated program that predicts substitutions needed to mutate to consensus is available at http://kazlab.umn.edu .

Computational tools help improve protein stability but with a solubility tradeoff

Accurately predicting changes in protein stability upon amino acid substitution is a much sought after goal. Destabilizing mutations are often implicated in disease, whereas stabilizing mutations are of great value for industrial and therapeutic biotechnology. Increasing protein stability is an especially challenging task, with random substitution yielding stabilizing mutations in only ∼2% of cases. To overcome this bottleneck, computational tools that aim to predict the effect of mutations have been developed; however, achieving accuracy and consistency remains challenging. Here, we combined 11 freely available tools into a meta-predictor (meieringlab.uwaterloo.ca/stabilitypredict/). Validation against ∼600 experimental mutations indicated that our meta-predictor has improved performance over any of the individual tools. The meta-predictor was then used to recommend 10 mutations in a previously designed protein of moderate thermodynamic stability, ThreeFoil. Experimental characterization showed that four mutations increased protein stability and could be amplified through ThreeFoil's structural symmetry to yield several multiple mutants with >2-kcal/mol stabilization. By avoiding residues within functional ties, we could maintain ThreeFoil's glycan-binding capacity. Despite successfully achieving substantial stabilization, however, almost all mutations decreased protein solubility, the most common cause of protein design failure. Examination of the 600-mutation data set revealed that stabilizing mutations on the protein surface tend to increase hydrophobicity and that the individual tools favor this approach to gain stability. Thus, whereas currently available tools can increase protein stability and combining them into a meta-predictor yields enhanced reliability, improvements to the potentials/force fields underlying these tools are needed to avoid gaining protein stability at the cost of solubility.

Ancestral Haloalkane Dehalogenases Show Robustness and Unique Substrate Specificity

Ancestral sequence reconstruction (ASR) represents a powerful approach for empirical testing structure-function relationships of diverse proteins. We employed ASR to predict sequences of five ancestral haloalkane dehalogenases (HLDs) from the HLD-II subfamily. Genes encoding the inferred ancestral sequences were synthesized and expressed in Escherichia coli, and the resurrected ancestral enzymes (AncHLD1-5) were experimentally characterized. Strikingly, the ancestral HLDs exhibited significantly enhanced thermodynamic stability compared to extant enzymes (ΔT_m up to 24 °C), as well as higher specific activities with preference for short multi-substituted halogenated substrates. Moreover, multivariate statistical analysis revealed a shift in the substrate specificity profiles of AncHLD1 and AncHLD2. This is extremely difficult to achieve by rational protein engineering. The study highlights that ASR is an efficient approach for the development of novel biocatalysts and robust templates for directed evolution.

A robust cosolvent-compatible halohydrin dehalogenase by computational library design

To improve the applicability of halohydrin dehalogenase as a catalyst for reactions in the presence of organic cosolvents, we explored a computational library design strategy (Framework for Rapid Enzyme Stabilization by Computational libraries) that involves discovery and in silico evaluation of stabilizing mutations. Energy calculations, disulfide bond predictions and molecular dynamics simulations identified 218 point mutations and 35 disulfide bonds with predicted stabilizing effects. Experiments confirmed 29 stabilizing point mutations, most of which were located in two distinct regions, whereas introduction of disulfide bonds was not effective. Combining the best mutations resulted in a 12-fold mutant (HheC-H12) with a 28°C higher apparent melting temperature and a remarkable increase in resistance to cosolvents. This variant also showed a higher optimum temperature for catalysis while activity at low temperature was preserved. Mutant H12 was used as a template for the introduction of mutations that enhance enantioselectivity or activity. Crystal structures showed that the structural changes in the H12 mutant mostly agreed with the computational predictions and that the enhanced stability was mainly due to mutations that redistributed surface charges and improved interactions between subunits, the latter including better interactions of water molecules at the subunit interfaces.

Increasing thermal stability and catalytic activity of glutamate decarboxylase in E. coli: An in silico study

Glutamate decarboxylase (GAD) is an enzyme that converts l-glutamate to gamma amino butyric acid (GABA) that is a widely used drug to treat mental disorders like Alzheimer's disease. In this study for the first time point mutation was performed virtually in the active site of the E. coli GAD in order to increase thermal stability and catalytic activity of the enzyme. Energy minimization and addition of water box were performed using GROMACS 5.4.6 package. PoPMuSiC 2.1 web server was used to predict potential spots for point mutation and Modeller software was used to perform point mutation on three dimensional model. Molegro virtual docker software was used for cavity detection and stimulated docking study. Results indicate that performing mutation separately at positions 164, 302, 304, 393, 396, 398 and 410 increase binding affinity to substrate. The enzyme is predicted to be more thermo- stable in all 7 mutants based on ΔΔG value.

Toward rational thermostabilization of Aspergillus oryzae cutinase: Insights into catalytic and structural stability

Cutinases are powerful hydrolases that can cleave ester bonds of polyesters such as poly(ethylene terephthalate) (PET), opening up new options for enzymatic routes for polymer recycling and surface modification reactions. Cutinase from Aspergillus oryzae (AoC) is promising owing to the presence of an extended groove near the catalytic triad which is important for the orientation of polymeric chains. However, the catalytic efficiency of AoC on rigid polymers like PET is limited by its low thermostability; as it is essential to work at or over the glass transition temperature (Tg) of PET, that is, 70 °C. Consequently, in this study we worked toward the thermostabilization of AoC. Use of Rosetta computational protein design software in conjunction with rational design led to a 6 °C improvement in the thermal unfolding temperature (Tm) and a 10-fold increase in the half-life of the enzyme activity at 60 °C. Surprisingly, thermostabilization did not improve the rate or temperature optimum of enzyme activity. Three notable findings are presented as steps toward designing more thermophilic cutinase: (a) surface salt bridge optimization produced enthalpic stabilization, (b) mutations to proline reduced the entropy loss upon folding, and (c) the lack of a correlative increase in the temperature optimum of catalytic activity with thermodynamic stability suggests that the active site is locally denatured at a temperature below the Tm of the global structure.

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants

There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

X-ray crystallographic validation of structure predictions used in computational design for protein stabilization

Protein engineering aimed at enhancing enzyme stability is increasingly supported by computational methods for calculation of mutant folding energies and for the design of disulfide bonds. To examine the accuracy of mutant structure predictions underlying these computational methods, crystal structures of thermostable limonene epoxide hydrolase variants obtained by computational library design were determined. Four different predicted effects indeed contributed to the obtained stabilization: (i) enhanced interactions between a flexible loop close to the N-terminus and the rest of the protein; (ii) improved interactions at the dimer interface; (iii) removal of unsatisfied hydrogen bonding groups; and (iv) introduction of additional positively charged groups at the surface. The structures of an eightfold and an elevenfold mutant showed that most mutations introduced the intended stabilizing interactions, and side-chain conformations were correctly predicted for 72-88% of the point mutations. However, mutations that introduced a disulfide bond in a flexible region had a larger influence on the backbone conformation than predicted. The enzyme active sites were unaltered, in agreement with the observed preservation of catalytic activities. The structures also revealed how a c-Myc tag, which was introduced for facile detection and purification, can reduce access to the active site and thereby lower the catalytic activity. Finally, sequence analysis showed that comprehensive mutant energy calculations discovered stabilizing mutations that are not proposed by the consensus or B-FIT methods.