Directed enzyme evolution: beyond the low-hanging fruit

Thermophilic β-mannanases from bacteria: production, resources, structural features and bioengineering strategies

β-mannanases are pivotal enzymes that cleave the mannan backbone to release short chain mannooligosaccharides, which have tremendous biotechnological applications including food/feed, prebiotics and biofuel production. Due to the high temperature conditions in many industrial applications, thermophilic mannanases seem to have great potential to overcome the thermal impediments. Thus, structural analysis of thermostable β-mannanases is extremely important, as it could open up new avenues for genetic engineering, and protein engineering of these enzymes with enhanced properties and catalytic efficiencies. Under this scope, the present review provides a state-of-the-art discussion on the thermophilic β-mannanases from bacterial origin, their production, engineering and structural characterization. It covers broad insights into various molecular biology techniques such as gene mutagenesis, heterologous gene expression, and protein engineering, that are employed to improve the catalytic efficiency and thermostability of bacterial mannanases for potential industrial applications. Further, the bottlenecks associated with mannanase production and process optimization are also discussed. Finally, future research related to bioengineering of mannanases with novel protein expression systems for commercial applications are also elaborated.

The 3D Modules of Enzyme Catalysis: Deconstructing Active Sites into Distinct Functional Entities

Enzyme catalysis is governed by a limited toolkit of residues and organic or inorganic co-factors. Therefore, it is expected that recurring residue arrangements will be found across the enzyme space, which perform a defined catalytic function, are structurally similar and occur in unrelated enzymes. Leveraging the integrated information in the Mechanism and Catalytic Site Atlas (M-CSA) (enzyme structure, sequence, catalytic residue annotations, catalysed reaction, detailed mechanism description), 3D templates were derived to represent compact groups of catalytic residues. A fuzzy template-template search, allowed us to identify those recurring motifs, which are conserved or convergent, that we define as the "modules of enzyme catalysis". We show that a large fraction of these modules facilitate binding of metal ions, co-factors and substrates, and are frequently the result of convergent evolution. A smaller number of convergent modules perform a well-defined catalytic role, such as the variants of the catalytic triad (i.e. Ser-His-Asp/Cys-His-Asp) and the saccharide-cleaving Asp/Glu triad. It is also shown that enzymes whose functions have diverged during evolution preserve regions of their active site unaltered, as shown by modules performing similar or identical steps of the catalytic mechanism. We have compiled a comprehensive library of catalytic modules, that characterise a broad spectrum of enzymes. These modules can be used as templates in enzyme design and for better understanding catalysis in 3D.

Conversion and synthesis of chemicals catalyzed by fungal cytochrome P450 monooxygenases: A review

Cytochrome P450s (also called CYPs or P450s) are a superfamily of heme-containing monooxygenases. They are distributed in all biological kingdoms. Most fungi have at least two P450-encoding genes, CYP51 and CYP61, which are housekeeping genes that play important roles in the synthesis of sterols. However, the kingdom fungi is an interesting source of numerous P450s. Here, we review reports on fungal P450s and their applications in the bioconversion and biosynthesis of chemicals. We highlight their history, availability, and versatility. We describe their involvement in hydroxylation, dealkylation, oxygenation, C═C epoxidation, C-C cleavage, C-C ring formation and expansion, C-C ring contraction, and uncommon reactions in bioconversion and/or biosynthesis pathways. The ability of P450s to catalyze these reactions makes them promising enzymes for many applications. Thus, we also discuss future prospects in this field. We hope that this review will stimulate further study and exploitation of fungal P450s for specific reactions and applications.

Enzyme directed evolution using genetically encodable biosensors

Directed evolution has been remarkably successful in identifying enzyme variants with new or improved properties, such as altered substrate scope or novel reactivity. Genetically encodable biosensors (GEBs), which convert the concentration of a small molecule ligand into an easily detectable output signal, have seen increasing application to enzyme directed evolution in the last decade. GEBs enable the use of high-throughput methods to assess enzyme activity of very large libraries, which can accelerate the search for variants with desirable activity. Here, we review different classes of GEBs and their properties in the context of enzyme evolution, how GEBs have been integrated into directed evolution workflows, and recent examples of enzyme evolution efforts utilizing GEBs. Finally, we discuss the advantages, challenges, and opportunities for using GEBs in the directed evolution of enzymes.

Using fungible biosensors to evolve improved alkaloid biosyntheses

A key bottleneck in the microbial production of therapeutic plant metabolites is identifying enzymes that can improve yield. The facile identification of genetically encoded biosensors can overcome this limitation and become part of a general method for engineering scaled production. We have developed a combined screening and selection approach that quickly refines the affinities and specificities of generalist transcription factors; using RamR as a starting point, we evolve highly specific (>100-fold preference) and sensitive (half-maximum effective concentration (EC₅₀) < 30 μM) biosensors for the alkaloids tetrahydropapaverine, papaverine, glaucine, rotundine and noscapine. High-resolution structures reveal multiple evolutionary avenues for the malleable effector-binding site and the creation of new pockets for different chemical moieties. These sensors further enabled the evolution of a streamlined pathway for tetrahydropapaverine, a precursor to four modern pharmaceuticals, collapsing multiple methylation steps into a single evolved enzyme. Our methods for evolving biosensors enable the rapid engineering of pathways for therapeutic alkaloids.

Capturing the geometry, function, and evolution of enzymes with 3D templates

Structural templates are 3D signatures representing protein functional sites, such as ligand binding cavities, metal coordination motifs, or catalytic sites. Here we explore methods to generate template libraries and algorithms to query structures for conserved 3D motifs. Applications of templates are discussed, as well as some exemplar cases for examining evolutionary links in enzymes. We also introduce the concept of using more than one template per structure to represent flexible sites, as an approach to better understand catalysis through snapshots captured in enzyme structures. Functional annotation from structure is an important topic that has recently resurfaced due to the new more accurate methods of protein structure prediction. Therefore, we anticipate that template‐based functional site detection will be a powerful tool in the task of characterizing a vast number of new protein models.

Biodegradation of Polymers Used in Oil and Gas Operations: Towards Enzyme Biotechnology Development and Field Application

Linear and crosslinked polymers are commonly used in the oil and gas industry. Guar-derived polymers have been extensively utilized in hydraulic fracturing processes, and recently polyacrylamide and cellulose-based polymers have also found utility. As these polymers are used during various phases of the hydraulic fracturing process, they can accumulate at formation fracture faces, resulting in undesired filter cakes that impede oil and gas recovery. Although acids and chemical oxidizers are often added in the fracturing fluids to degrade or ‘break’ polymer filter cakes, the constant use of these chemicals can be hazardous and can result in formation damage and corrosion of infrastructure. Alternately, the use of enzymes is an attractive and environmentally friendly technology that can be used to treat polymer accumulations. While guar-linkage-specific enzyme breakers isolated from bacteria have been shown to successfully cleave guar-based polymers and decrease their molecular weight and viscosity at reservoir conditions, new enzymes that target a broader range of polymers currently used in hydraulic fracturing operations still require research and development for effective application. This review article describes the current state-of-knowledge on the mechanisms and enzymes involved in biodegradation of guar gum, polyacrylamide (and hydrolyzed polyacrylamide), and carboxymethyl cellulose polymers. In addition, advantages and challenges in the development and application of enzyme breaker technologies are discussed.

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.

Making the cut with protease engineering

Proteases cut with enviable precision and regulate diverse molecular events in biology. Such qualities drive a seemingly inexhaustible appetite for proteases with new activities and capabilities. Comprising 25% of the total industrial enzyme market, proteases appear in consumer goods, such as detergents, textile processing, and numerous foods; additionally, proteases include 25 US Food and Drug Administration-approved medicines and various research tools. Recent advances in protease engineering strategies address target specificity, catalytic efficiency, and stability. This guide to protease engineering surveys best practices and emerging strategies. We further highlight gaps and flexibilities inherent to each system that suggest opportunities for new technology development along with engineered proteases to solve challenges in proteomics, protein sequencing, and synthetic gene circuits.

Thermostable Cellulases / Xylanases From Thermophilic and Hyperthermophilic Microorganisms: Current Perspective

The bioconversion of lignocellulose into monosaccharides is critical for ensuring the continual manufacturing of biofuels and value-added bioproducts. Enzymatic degradation, which has a high yield, low energy consumption, and enhanced selectivity, could be the most efficient and environmentally friendly technique for converting complex lignocellulose polymers to fermentable monosaccharides, and it is expected to make cellulases and xylanases the most demanded industrial enzymes. The widespread nature of thermophilic microorganisms allows them to proliferate on a variety of substrates and release substantial quantities of cellulases and xylanases, which makes them a great source of thermostable enzymes. The most significant breakthrough of lignocellulolytic enzymes lies in lignocellulose-deconstruction by enzymatic depolymerization of holocellulose into simple monosaccharides. However, commercially valuable thermostable cellulases and xylanases are challenging to produce in high enough quantities. Thus, the present review aims at giving an overview of the most recent thermostable cellulases and xylanases isolated from thermophilic and hyperthermophilic microbes. The emphasis is on recent advancements in manufacturing these enzymes in other mesophilic host and enhancement of catalytic activity as well as thermostability of thermophilic cellulases and xylanases, using genetic engineering as a promising and efficient technology for its economic production. Additionally, the biotechnological applications of thermostable cellulases and xylanases of thermophiles were also discussed.

Current and emerging tools of computational biology to improve the detoxification of mycotoxins

Biological organisms carry a rich potential for removing toxins from our environment, but identifying suitable candidates and improving them remain challenging. We explore the use of computational tools to discover strains and enzymes that detoxify harmful compounds. In particular, we will focus on mycotoxins-fungi-produced toxins that contaminate food and feed-and biological enzymes that are capable of rendering them less harmful. We discuss the use of established and novel computational tools to complement existing empirical data in three directions: discovering the prospect of detoxification among underexplored organisms, finding important cellular processes that contribute to detoxification, and improving the performance of detoxifying enzymes. We hope to create a synergistic conversation between researchers in computational biology and those in the bioremediation field. We showcase open bioremediation questions where computational researchers can contribute and highlight relevant existing and emerging computational tools that could benefit bioremediation researchers.

A hierarchy of coupling free energies underlie the thermodynamic and functional architecture of protein structures

Protein sequences and structures evolve by satisfying varied physical and biochemical constraints. This multi-level selection is enabled not just by the patterning of amino acids on the sequence, but also via coupling between residues in the native structure. Here, we employ an energetically detailed statistical mechanical model with millions of microstates to extract such long-range structural correlations, i.e. thermodynamic coupling free energies, from a diverse family of protein structures. We find that despite the intricate and anisotropic distribution of coupling patterns, the majority of residues (>70%) are only marginally coupled contributing to functional motions and catalysis. Physical origins of ‘sectors’, determinants of native ensemble heterogeneity in extant, ancient and designed proteins, and the basis for allostery emerge naturally from coupling free energies. The statistical framework highlights how evolutionary selection and optimization occur at the level of global interaction network for a given protein fold impacting folding, function, and allosteric outputs.

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Evolution of protein structures occurs at the level of global interaction network.

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More than 70% of the protein residues are weakly or marginally coupled.

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Functional ‘sector’ regions are a manifestation of marginal coupling.

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Coupling indices vary across the entire proteins in extant-ancient and natural-designed pairs.

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The proposed methodology can be used to understand allostery and epistasis.

Climbing Up and Down Binding Landscapes through Deep Mutational Scanning of Three Homologous Protein-Protein Complexes

Protein-protein interactions (PPIs) have evolved to display binding affinities that can support their function. As such, cognate and noncognate PPIs could be highly similar structurally but exhibit huge differences in binding affinities. To understand this phenomenon, we study three homologous protease-inhibitor PPIs that span 9 orders of magnitude in binding affinity. Using state-of-the-art methodology that combines protein randomization, affinity sorting, deep sequencing, and data normalization, we report quantitative binding landscapes consisting of ΔΔG_bind values for the three PPIs, gleaned from tens of thousands of single and double mutations. We show that binding landscapes of the three complexes are strikingly different and depend on the PPI evolutionary optimality. We observe different patterns of couplings between mutations for the three PPIs with negative and positive epistasis appearing most frequently at hot-spot and cold-spot positions, respectively. The evolutionary trends observed here are likely to be universal to other biological complexes in the cell.

Methods for enzyme library creation: Which one will you choose?: A guide for novices and experts to introduce genetic diversity

Enzyme engineering allows to explore sequence diversity in search for new properties. The scientific literature is populated with methods to create enzyme libraries for engineering purposes, however, choosing a suitable method for the creation of mutant libraries can be daunting, in particular for the novices. Here, we address both novices and experts: how can one enter the arena of enzyme library design and what guidelines can advanced users apply to select strategies best suited to their purpose? Section I is dedicated to the novices and presents an overview of established and standard methods for library creation, as well as available commercial solutions. The expert will discover an up-to-date tool to freshen up their repertoire (Section I) and learn of the newest methods that are likely to become a mainstay (Section II). We focus primarily on in vitro methods, presenting the advantages of each method. Our ultimate aim is to offer a selection of methods/strategies that we believe to be most useful to the enzyme engineer, whether a first-timer or a seasoned user.

Low-N protein engineering with data-efficient deep learning

Protein engineering has enormous academic and industrial potential. However, it is limited by the lack of experimental assays that are consistent with the design goal and sufficiently high throughput to find rare, enhanced variants. Here we introduce a machine learning-guided paradigm that can use as few as 24 functionally assayed mutant sequences to build an accurate virtual fitness landscape and screen ten million sequences via in silico directed evolution. As demonstrated in two dissimilar proteins, GFP from Aequorea victoria (avGFP) and E. coli strain TEM-1 β-lactamase, top candidates from a single round are diverse and as active as engineered mutants obtained from previous high-throughput efforts. By distilling information from natural protein sequence landscapes, our model learns a latent representation of 'unnaturalness', which helps to guide search away from nonfunctional sequence neighborhoods. Subsequent low-N supervision then identifies improvements to the activity of interest. In sum, our approach enables efficient use of resource-intensive high-fidelity assays without sacrificing throughput, and helps to accelerate engineered proteins into the fermenter, field and clinic.

Quantitative mapping of binding specificity landscapes for homologous targets by using a high-throughput method

To facilitate investigations of protein-protein interactions (PPIs), we developed a novel platform for quantitative mapping of protein binding specificity landscapes, which combines the multi-target screening of a mutagenesis library into high- and low-affinity populations with sophisticated next-generation sequencing analysis. Importantly, this method generates accurate models to predict affinity and specificity values for any mutation within a protein complex, and requires only a few experimental binding affinity measurements using purified proteins for calibration. We demonstrated the utility of the approach by mapping quantitative landscapes for interactions between the N-terminal domain of the tissue inhibitor of metalloproteinase 2 (N-TIMP2) and three matrix metalloproteinases (MMPs) having homologous structures but different affinities (MMP-1, MMP-3, and MMP-14). The binding landscapes for N-TIMP2/MMP-1 and N-TIMP2/MMP-3 showed the PPIs to be almost fully optimized, with most single mutations giving a loss of affinity. In contrast, the non-optimized PPI for N-TIMP2/MMP-14 was reflected in a wide range of binding affinities, where single mutations exhibited a far more attenuated effect on the PPI. Our new platform reliably and comprehensively identified not only hot- and cold-spot residues, but also specificity-switch mutations that shape target affinity and specificity. Thus, our approach provides a methodology giving an unprecedentedly rich quantitative analysis of the binding specificity landscape, which will broaden the understanding of the mechanisms and evolutionary origins of specific PPIs and facilitate the rational design of specific inhibitors for structurally similar target proteins.

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

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

Bioengineered Polyhydroxyalkanoates as Immobilized Enzyme Scaffolds for Industrial Applications

Enzymes function as biocatalysts and are extensively exploited in industrial applications. Immobilization of enzymes using support materials has been shown to improve enzyme properties, including stability and functionality in extreme conditions and recyclability in biocatalytic processing. This review focuses on the recent advances utilizing the design space of in vivo self-assembled polyhydroxyalkanoate (PHA) particles as biocatalyst immobilization scaffolds. Self-assembly of biologically active enzyme-coated PHA particles is a one-step in vivo production process, which avoids the costly and laborious in vitro chemical cross-linking of purified enzymes to separately produced support materials. The homogeneous orientation of enzymes densely coating PHA particles enhances the accessibility of catalytic sites, improving enzyme function. The PHA particle technology has been developed into a remarkable scaffolding platform for the design of cost-effective designer biocatalysts amenable toward robust industrial bioprocessing. In this review, the PHA particle technology will be compared to other biological supramolecular assembly-based technologies suitable for in vivo enzyme immobilization. Recent progress in the fabrication of biological particulate scaffolds using enzymes of industrial interest will be summarized. Additionally, we outline innovative approaches to overcome limitations of in vivo assembled PHA particles to enable fine-tuned immobilization of multiple enzymes to enhance performance in multi-step cascade reactions, such as those used in continuous flow bioprocessing.

Geometry and Flexibility of Optimal Catalysts in a Minimal Elastic Model

We have general knowledge of the principles by which catalysts accelerate the rate of chemical reactions but no precise understanding of the geometrical and physical constraints to which their design is subject. To analyze these constraints, we introduce a minimal model of catalysis based on elastic networks where the implications of the geometry and flexibility of a catalyst can be studied systematically. The model demonstrates the relevance and limitations of the principle of transition-state stabilization: optimal catalysts are found to have a geometry complementary to the transition state but a degree of flexibility that nontrivially depends on the parameters of the reaction as well as on external parameters such as the concentrations of reactants and products. The results illustrate how simple physical models can provide valuable insights into the design of catalysts.

Structure-based directed evolution improves S. cerevisiae growth on xylose by influencing in vivo enzyme performance

BACKGROUND

Efficient bioethanol production from hemicellulose feedstocks by Saccharomyces cerevisiae requires xylose utilization. Whereas S. cerevisiae does not metabolize xylose, engineered strains that express xylose isomerase can metabolize xylose by converting it to xylulose. For this, the type II xylose isomerase from Piromyces (PirXI) is used but the in vivo activity is rather low and very high levels of the enzyme are needed for xylose metabolism. In this study, we explore the use of protein engineering and in vivo selection to improve the performance of PirXI. Recently solved crystal structures were used to focus mutagenesis efforts.

RESULTS

We constructed focused mutant libraries of Piromyces xylose isomerase by substitution of second shell residues around the substrate- and metal-binding sites. Following library transfer to S. cerevisiae and selection for enhanced xylose-supported growth under aerobic and anaerobic conditions, two novel xylose isomerase mutants were obtained, which were purified and subjected to biochemical and structural analysis. Apart from a small difference in response to metal availability, neither the new mutants nor mutants described earlier showed significant changes in catalytic performance under various in vitro assay conditions. Yet, in vivo performance was clearly improved. The enzymes appeared to function suboptimally in vivo due to enzyme loading with calcium, which gives poor xylose conversion kinetics. The results show that better in vivo enzyme performance is poorly reflected in kinetic parameters for xylose isomerization determined in vitro with a single type of added metal.

CONCLUSION

This study shows that in vivo selection can identify xylose isomerase mutants with only minor changes in catalytic properties measured under standard conditions. Metal loading of xylose isomerase expressed in yeast is suboptimal and strongly influences kinetic properties. Metal uptake, distribution and binding to xylose isomerase are highly relevant for rapid xylose conversion and may be an important target for optimizing yeast xylose metabolism.

Strategies for Increasing Protein Stability

The stability of wild-type proteins is often a hurdle to their practical use in research, industry, and medicine. The route to engineering stability of a protein of interest lies largely with the available data. Where high-resolution structural data is available, rational design, based on fundamental principles of protein chemistry, can improve protein stability. Recent advances in computational biology and the use of nonnatural amino acids have also provided novel rational methods for improving protein stability. Likewise, the explosion of sequence and structural data available in public databases, in combination with improvements in freely available computational tools, has produced accessible phylogenetic approaches. Trawling modern sequence databases can identify the thermostable homologs of a target protein, and evolutionary data can be quickly generated using available phylogenetic tools. Grafting features from those thermostable homologs or ancestors provides stability improvement through a semi-rational approach. Further, molecular techniques such as directed evolution have shown great promise in delivering designer proteins. These strategies are well documented and newly accessible to the molecular biologist, allowing for rapid enhancements of protein stability.

Controlling Structure and Dimensions of a Disordered Protein via Mutations

The dimensions of intrinsically disordered proteins (IDPs) are sensitive to small energetic-entropic differences between intramolecular and protein–solvent interactions. This is commonly observed on modulating solvent composition and temperature. However, the inherently heterogeneous conformational landscape of IDPs is also expected to be influenced by mutations that can (de)stabilize pockets of local and even global structure, native and non-native, and hence the average dimensions. Here, we show experimental evidence for the remarkably tunable landscape of IDPs by employing the DNA-binding domain of CytR, a high-sequence-complexity IDP, as a model system. CytR exhibits a range of structure and compactness upon introducing specific mutations that modulate microscopic terms, including main-chain entropy, hydrophobicity, and electrostatics. The degree of secondary structure, as monitored by far-UV circular dichroism (CD), is strongly correlated to average ensemble dimensions for 14 different mutants of CytR and is consistent with the Uversky–Fink relation. Our experiments highlight how average ensemble dimensions can be controlled via mutations even in the disordered regime, the prevalence of non-native interactions and provide testable controls for molecular simulations.

Improvements of thermophilic enzymes: From genetic modifications to applications

Thermozymes (from thermophiles or hyperthermophiles) offer obvious advantages due to their excellent thermostability, broad pH adaptation, and hydrolysis ability, resulting in diverse industrial applications including food, paper, and textile processing, biofuel production. However, natural thermozymes with low yield and poor adaptability severely hinder their large-scale applications. Extensive studies demonstrated that using genetic modifications such as directed evolution, semi-rational design, and rational design, expression regulations and chemical modifications effectively improved enzyme's yield, thermostability and catalytic efficiency. However, mechanism-based techniques for thermozymes improvements and applications need more attention. In this review, stabilizing mechanisms of thermozymes are summarized for thermozymes improvements, and these improved thermozymes eventually have large-scale industrial applications.

Modulation of allosteric coupling by mutations: from protein dynamics and packing to altered native ensembles and function

A large body of work has gone into understanding the effect of mutations on protein structure and function. Conventional treatments have involved quantifying the change in stability, activity and relaxation rates of the mutants with respect to the wild-type protein. However, it is now becoming increasingly apparent that mutational perturbations consistently modulate the packing and dynamics of a significant fraction of protein residues, even those that are located >10–15 Å from the mutated site. Such long-range modulation of protein features can distinctly tune protein stability and the native conformational ensemble contributing to allosteric modulation of function. In this review, I summarize a series of experimental and computational observations that highlight the incredibly pliable nature of proteins and their response to mutational perturbations manifested via the intra-protein interaction network. I highlight how an intimate understanding of mutational effects could pave the way for integrating stability, folding, cooperativity and even allostery within a single physical framework.

Evolution of substrate specificity in the Nucleobase-Ascorbate Transporter (NAT) protein family

L-ascorbic acid (vitamin C) is an essential metabolite in animals and plants due to its role as an enzyme co-factor and antioxidant activity. In most eukaryotic organisms, L-ascorbate is biosynthesized enzymatically, but in several major groups, including the primate suborder Haplorhini, this ability is lost due to gene truncations in the gene coding for L-gulonolactone oxidase. Specific ascorbate transporters (SVCTs) have been characterized only in mammals and shown to be essential for life. These belong to an extensively studied transporter family, called Nucleobase-Ascorbate Transporters (NAT). The prototypic member of this family, and one of the most extensively studied eukaryotic transporters, is UapA, a uric acid-xanthine/H⁺ symporter in the fungus Aspergillus nidulans. Here, we investigate molecular aspects of NAT substrate specificity and address the evolution of ascorbate transporters apparently from ancestral nucleobase transporters. We present a phylogenetic analysis, identifying a distinct NAT clade that includes all known L-ascorbate transporters. This clade includes homologues only from vertebrates, and has no members in non-vertebrate or microbial eukaryotes, plants or prokaryotes. Additionally, we identify within the substrate-binding site of NATs a differentially conserved motif, which we propose is critical for nucleobase versus ascorbate recognition. This conclusion is supported by the amino acid composition of this motif in distinct phylogenetic clades and mutational analysis in the UapA transporter. Together with evidence obtained herein that UapA can recognize with extremely low affinity L-ascorbate, our results support that ascorbate-specific NATs evolved by optimization of a sub-function of ancestral nucleobase transporters.

Directed Evolution of Proteins Based on Mutational Scanning

Directed evolution has emerged as one of the most effective protein engineering methods in basic research as well as in applications in synthetic organic chemistry and biotechnology. The successful engineering of protein activity, allostery, binding affinity, expression, folding, fluorescence, solubility, substrate scope, selectivity (enantio-, stereo-, and regioselectivity), and/or stability (temperature, organic solvents, pH) is just limited by the throughput of the genetic selection, display, or screening system that is available for a given protein. Sometimes it is possible to analyze millions of protein variants from combinatorial libraries per day. In other cases, however, only a few hundred variants can be screened in a single day, and thus the creation of smaller yet smarter libraries is needed. Different strategies have been developed to create these libraries. One approach is to perform mutational scanning or to construct "mutability landscapes" in order to understand sequence-function relationships that can guide the actual directed evolution process. Herein we provide a protocol for economically constructing scanning mutagenesis libraries using a cytochrome P450 enzyme in a high-throughput manner. The goal is to engineer activity, regioselectivity, and stereoselectivity in the oxidative hydroxylation of a steroid, a challenging reaction in synthetic organic chemistry. Libraries based on mutability landscapes can be used to engineer any fitness trait of interest. The protocol is also useful for constructing gene libraries for deep mutational scanning experiments.

Parallel Screening for Rapid Identification of Orthogonal Bioluminescent Tools

Bioluminescence imaging with luciferase enzymes and luciferin small molecules is a well-established technique for tracking cells and other biological features in rodent models. Despite its popularity, bioluminescence has long been hindered by a lack of distinguishable probes. Here we present a method to rapidly identify new substrate-selective luciferases for multicomponent imaging. Our strategy relies on parallel screening of luciferin analogues with panels of mutant enzymes. The compiled data set is then analyzed in silico to uncover mutually orthogonal sets. Using this approach, we screened 159 mutant enzymes with 12 luciferins. Thousands of orthogonal pairs were revealed with sufficient selectivity for use in biological environments. Over 100 pairs were validated in vitro, and three were applied in cell and animal models. The parallel screening method is both generalizable and scalable and will streamline the search for larger collections of orthogonal probes.

Discovery of human-like L-asparaginases with potential clinical use by directed evolution

L-asparaginase is a chemotherapy drug used to treat acute lymphoblastic leukemia (ALL). The main prerequisite for clinical efficacy of L-asparaginases is micromolar KM for asparagine to allow for complete depletion of this amino acid in the blood. Since currently approved L-asparaginases are of bacterial origin, immunogenicity is a challenge, which would be mitigated by a human enzyme. However, all human L-asparaginases have millimolar KM for asparagine. We recently identified the low KM guinea pig L-asparaginase (gpASNase1). Because gpASNase1 and human L-asparaginase 1 (hASNase1) share ~70% amino-acid identity, we decided to humanize gpASNase1 by generating chimeras with hASNase1 through DNA shuffling. To identify low KM chimeras we developed a suitable bacterial selection system (E. coli strain BW5Δ). Transforming BW5Δ with the shuffling libraries allowed for the identification of several low KM clones. To further humanize these clones, the C-terminal domain of gpASNase1 was replaced with that of hASNase1. Two of the identified clones, 63N-hC and 65N-hC, share respectively 85.7% and 87.1% identity with the hASNase1 but have a KM similar to gpASNase1. These clones possess 100-140 fold enhanced catalytic efficiency compared to hASNase1. Notably, we also show that these highly human-like L-asparaginases maintain their in vitro ALL killing potential.

Hydrogen-Deuterium Exchange of Lipoxygenase Uncovers a Relationship between Distal, Solvent Exposed Protein Motions and the Thermal Activation Barrier for Catalytic Proton-Coupled Electron Tunneling

Defining specific pathways for efficient heat transfer from protein-solvent interfaces to their active sites represents one of the compelling and timely challenges in our quest for a physical description of the origins of enzyme catalysis. Enzymatic hydrogen tunneling reactions constitute excellent systems in which to validate experimental approaches to this important question, given the inherent temperature independence of quantum mechanical wave function overlap. Herein, we present the application of hydrogen-deuterium exchange coupled to mass spectrometry toward the spatial resolution of protein motions that can be related to an enzyme's catalytic parameters. Employing the proton-coupled electron transfer reaction of soybean lipoxygenase as proof of principle, we first corroborate the impact of active site mutations on increased local flexibility and, second, uncover a solvent-exposed loop, 15-34 Å from the reactive ferric center whose temperature-dependent motions are demonstrated to mirror the enthalpic barrier for catalytic C-H bond cleavage. A network that connects this surface loop to the active site is structurally identified and supported by changes in kinetic parameters that result from site-specific mutations.

Using Evolution to Guide Protein Engineering: The Devil IS in the Details

For decades, protein engineers have endeavored to reengineer existing proteins for novel applications. Overall, protein folds and gross functions can be readily transferred from one protein to another by transplanting large blocks of sequence (i.e., domain recombination). However, predictably fine-tuning function (e.g., by adjusting ligand affinity, specificity, catalysis, and/or allosteric regulation) remains a challenge. One approach has been to use the sequences of protein families to identify amino acid positions that change during the evolution of functional variation. The rationale is that these nonconserved positions could be mutated to predictably fine-tune function. Evolutionary approaches to protein design have had some success, but the engineered proteins seldom replicate the functional performances of natural proteins. This Biophysical Perspective reviews several complexities that have been revealed by evolutionary and experimental studies of protein function. These include 1) challenges in defining computational and biological thresholds that define important amino acids; 2) the co-occurrence of many different patterns of amino acid changes in evolutionary data; 3) difficulties in mapping the patterns of amino acid changes to discrete functional parameters; 4) the nonconventional mutational outcomes that occur for a particular group of functionally important, nonconserved positions; 5) epistasis (nonadditivity) among multiple mutations; and 6) the fact that a large fraction of a protein's amino acids contribute to its overall function. To overcome these challenges, new goals are identified for future studies.

A growth- and bioluminescence-based bioreporter for the in vivo detection of novel biocatalysts

The use of bioreporters in high-throughput screening for small molecules is generally laborious and/or expensive. The technology can be simplified by coupling the generation of a desired compound to cell survival, causing only positive cells to stay in the pool of generated variants. Here, a dual selection/screening system was developed for the in vivo detection of novel biocatalysts. The sensor part of the system is based on the transcriptional regulator AraC, which controls expression of both a selection reporter (LeuB or KmR; enabling growth) for rapid reduction of the initially large library size and a screening reporter (LuxCDABE; causing bioluminescence) for further quantification of the positive variants. Of four developed systems, the best system was the medium copy system with KmR as selection reporter. As a proof of principle, the system was tested for the selection of cells expressing an l-arabinose isomerase derived from mesophilic Escherichia coli or thermophilic Geobacillus thermodenitrificans. A more than a millionfold enrichment of cells with l-arabinose isomerase activity was demonstrated by selection and exclusion of false positives by screening. This dual selection/screening system is an important step towards an improved detection method for small molecules, and thereby for finding novel biocatalysts.

Ultrahigh-Throughput Improvement and Discovery of Enzymes Using Droplet-Based Microfluidic Screening

Enzymes are extremely valuable tools for industrial, environmental, and biotechnological applications and there is a constant need for improving existing biological catalysts and for discovering new ones. Screening microbe or gene libraries is an efficient way of identifying new enzymes. In this view, droplet-based microfluidics appears to be one of the most powerful approaches as it allows inexpensive screenings in well-controlled conditions and an ultrahigh-throughput regime. This review aims to introduce the main microfluidic devices and concepts to be considered for such screening before presenting and discussing the latest successful applications of the technology for enzyme discovery.

An Overview on the Enhancement of Enantioselectivity and Stability of Microbial Epoxide Hydrolases

Epoxide hydrolases (EHs; 3.3.2.x) catalyze the enantioselective ring opening of racemic epoxides to the corresponding enantiopure vicinal diols and remaining equivalent unreacted epoxides. These epoxides and diols are used for the synthesis of chiral drug intermediates. With an upsurge in the methods for identification of novel microbial EHs, a lot of EHs have been discovered and utilized for kinetic resolution of racemic epoxides. However, there is still a constraint on the account of limited EHs being successfully applied on the preparative scale for industrial biotransformations. This limitation has to be overcome before application of identified functional EHs on large scale. Many strategies such as optimizing reaction media, immobilizing EHs and laboratory-scale directed evolution of EHs have been adopted for enhancing the industrial potential of EHs. In this review, these approaches have been highlighted which can serve as a pathway for the enrichment of already identified EHs for their application on an industrial scale in future studies.

Uniting Natural History with the Molecular Sciences. The Ultimate Multidisciplinarity

Life and the Earth have coevolved over the past four billion years to deliver a rich diversity of biological structure, from biomolecules to macrophysiology. One grand challenge seeks to interconnect these structures, in ways acceptable to both natural historians and physical scientists, to give an interconnecting web of models and experiments to create a planetary understanding of the phenomenon that we call "life". The molecular scientist wants experiments; the natural historian wants reference to Darwinian fitness. Paleogenetics offers both.

Computational tools for enzyme improvement: why everyone can - and should - use them

This review presents computational methods that experimentalists can readily use to create smart libraries for enzyme engineering and to obtain insights into protein-substrate complexes. Computational tools have the reputation of being hard to use and inaccurate compared to experimental methods in enzyme engineering, yet they are essential to probe datasets of ever-increasing size and complexity. In recent years, bioinformatics groups have made a huge leap forward in providing user-friendly interfaces and accurate algorithms for experimentalists. These methods guide efficient experimental planning and allow the enzyme engineer to rationalize time and resources. Computational tools nevertheless face challenges in the realm of transient modern technology.

Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening

The Golden Gate strategy entails the use of type IIS restriction enzymes, which cut outside of their recognition sequence. It enables unrestricted design of unique DNA fragments that can be readily and seamlessly recombined. Successfully employed in other synthetic biology applications, we demonstrate its advantageous use to engineer a biocatalyst. Hot-spots for mutations were individuated in three distinct regions of Candida antarctica lipase A (Cal-A), the biocatalyst chosen as a target to demonstrate the versatility of this recombination method. The three corresponding gene segments were subjected to the most appropriate method of mutagenesis (targeted or random). Their straightforward reassembly allowed combining products of different mutagenesis methods in a single round for rapid production of a series of diverse libraries, thus facilitating directed evolution. Screening to improve discrimination of short-chain versus long-chain fatty acid substrates was aided by development of a general, automated method for visual discrimination of the hydrolysis of varied substrates by whole cells.

Protein consensus-based surface engineering (ProCoS): a computer-assisted method for directed protein evolution

Protein consensus-based surface engineering (ProCoS) is a simple and efficient method for directed protein evolution combining computational analysis and molecular biology tools to engineer protein surfaces. ProCoS is based on the hypothesis that conserved residues originated from a common ancestor and that these residues are crucial for the function of a protein, whereas highly variable regions (situated on the surface of a protein) can be targeted for surface engineering to maximize performance. ProCoS comprises four main steps: (i) identification of conserved and highly variable regions; (ii) protein sequence design by substituting residues in the highly variable regions, and gene synthesis; (iii) in vitro DNA recombination of synthetic genes; and (iv) screening for active variants. ProCoS is a simple method for surface mutagenesis in which multiple sequence alignment is used for selection of surface residues based on a structural model. To demonstrate the technique's utility for directed evolution, the surface of a phytase enzyme from Yersinia mollaretii (Ymphytase) was subjected to ProCoS. Screening just 1050 clones from ProCoS engineering-guided mutant libraries yielded an enzyme with 34 amino acid substitutions. The surface-engineered Ymphytase exhibited 3.8-fold higher pH stability (at pH 2.8 for 3 h) and retained 40% of the enzyme's specific activity (400 U/mg) compared with the wild-type Ymphytase. The pH stability might be attributed to a significantly increased (20 percentage points; from 9% to 29%) number of negatively charged amino acids on the surface of the engineered phytase.