"Site and Mutation"-Specific Predictions Enable Minimal Directed Evolution Libraries

Tailoring of levansucrase product size by a comparative molecular dynamics approach

Levan is widely used as food additives. Its utilization is significantly influenced by its molecular weight. Bacillus subtilis levansucrase (Bs-SacB) and Priestia megaterium levansucrase (Pm-SacB) yield levan of different weights. To delve deeper into the molecular underpinnings of the molecular weight disparity between the products of these two enzymes, we conducted a focused study on the eight loops surrounding the active sites of Bs-SacB and Pm-SacB and identified Loop3 and loop4 as critical determinants in changing the molecular weight of Bs-SacB 's products. Subsequently, leveraging mutation energy analysis and non-homologous substitution strategies, we crafted tailored modifications in loop3 and loop4, yielding a spectrum of mutant enzymes that exhibit diverse molecular weight profiles including F182Y (3698 Da), CYTI (3093 Da), 3-Pbl (2776 Da), 4-Bml (1845 Da), and F182K (1571 Da). This research provide a novel comparative molecular dynamics approach to change product molecular weight and it is successfully applied in the modification of levansucrase.

Insight into Protein Engineering: From In silico Modelling to In vitro Synthesis

Protein engineering alters the polypeptide chain to obtain a novel protein with improved functional properties. This field constantly evolves with advanced in silico tools and techniques to design novel proteins and peptides. Rational incorporating mutations, unnatural amino acids, and post-translational modifications increases the applications of engineered proteins and peptides. It aids in developing drugs with maximum efficacy and minimum side effects. Currently, the engineering of peptides is gaining attention due to their high stability, binding specificity, less immunogenic, and reduced toxicity properties. Engineered peptides are potent candidates for drug development due to their high specificity and low cost of production compared with other biologics, including proteins and antibodies. Therefore, understanding the current perception of designing and engineering peptides with the help of currently available in silico tools is crucial. This review extensively studies various in silico tools available for protein engineering in the prospect of designing peptides as therapeutics, followed by in vitro aspects. Moreover, a discussion on the chemical synthesis and purification of peptides, a case study, and challenges are also incorporated.

Identification, Characterization, and Computer-Aided Rational Design of a Novel Thermophilic Esterase from Geobacillus subterraneus, and Application in the Synthesis of Cinnamyl Acetate

Investigation of a novel thermophilic esterase gene from Geobacillus subterraneus DSMZ 13552 indicated a high amino acid sequence similarity of 25.9% to a reported esterase from Geobacillus sp. A strategy that integrated computer-aided rational design tools was developed to select mutation sites. Six mutants were selected from four criteria based on the simulated saturation mutation (including 19 amino acid residues) results. Of these, the mutants Q78Y and G119A were found to retain 87% and 27% activity after incubation at 70 °C for 20 min, compared with the 19% activity for the wild type. Subsequently, a double-point mutant (Q78Y/G119A) was obtained and identified with optimal temperature increase from 65 to 70 °C and a 41.51% decrease in Km. The obtained T1/2 values of 42.2 min (70 °C) and 16.9 min (75 °C) for Q78Y/G119A showed increases of 340% and 412% compared with that in the wild type. Q78Y/G119A was then employed as a biocatalyst to synthesize cinnamyl acetate, for which the conversion rate reached 99.40% with 0.3 M cinnamyl alcohol at 60 °C. The results validated the enhanced enzymatic properties of the mutant and indicated better prospects for industrial application as compared to that in the wild type. This study reported a method by which an enzyme could evolve to achieve enhanced thermostability, thereby increasing its potential for industrial applications, which could also be expanded to other esterases.

From nature to industry: Harnessing enzymes for biocatalysis

Biocatalysis harnesses enzymes to make valuable products. This green technology is used in countless applications from bench scale to industrial production and allows practitioners to access complex organic molecules, often with fewer synthetic steps and reduced waste. The last decade has seen an explosion in the development of experimental and computational tools to tailor enzymatic properties, equipping enzyme engineers with the ability to create biocatalysts that perform reactions not present in nature. By using (chemo)-enzymatic synthesis routes or orchestrating intricate enzyme cascades, scientists can synthesize elaborate targets ranging from DNA and complex pharmaceuticals to starch made in vitro from CO2-derived methanol. In addition, new chemistries have emerged through the combination of biocatalysis with transition metal catalysis, photocatalysis, and electrocatalysis. This review highlights recent key developments, identifies current limitations, and provides a future prospect for this rapidly developing technology.

Accelerating Biocatalysis Discovery with Machine Learning: A Paradigm Shift in Enzyme Engineering, Discovery, and Design

Emerging computational tools promise to revolutionize protein engineering for biocatalytic applications and accelerate the development timelines previously needed to optimize an enzyme to its more efficient variant. For over a decade, the benefits of predictive algorithms have helped scientists and engineers navigate the complexity of functional protein sequence space. More recently, spurred by dramatic advances in underlying computational tools, the promise of faster, cheaper, and more accurate enzyme identification, characterization, and engineering has catapulted terms such as artificial intelligence and machine learning to the must-have vocabulary in the field. This Perspective aims to showcase the current status of applications in pharmaceutical industry and also to discuss and celebrate the innovative approaches in protein science by highlighting their potential in selected recent developments and offering thoughts on future opportunities for biocatalysis. It also critically assesses the technology's limitations, unanswered questions, and unmet challenges.

Co-Enzymes with Dissimilar Stabilities: A Discussion of the Likely Biocatalyst Performance Problems and Some Potential Solutions

Enzymes have several excellent catalytic features, and the last few years have seen a revolution in biocatalysis, which has grown from using one enzyme to using multiple enzymes in cascade reactions, where the product of one enzyme reaction is the substrate for the subsequent one. However, enzyme stability remains an issue despite the many benefits of using enzymes in a catalytic system. When enzymes are exposed to harsh process conditions, deactivation occurs, which changes the activity of the enzyme, leading to an increase in reaction time to achieve a given conversion. Immobilization is a well-known strategy to improve many enzyme properties, if the immobilization is properly designed and controlled. Enzyme co-immobilization is a further step in the complexity of preparing a biocatalyst, whereby two or more enzymes are immobilized on the same particle or support. One crucial problem when designing and using co-immobilized enzymes is the possibility of using enzymes with very different stabilities. This paper discusses different scenarios using two co-immobilized enzymes of the same or differing stability. The effect on operational performance is shown via simple simulations using Michaelis–Menten equations to describe kinetics integrated with a deactivation term. Finally, some strategies for overcoming some of these problems are discussed.

High throughput screen for the improvement of inducible promoters for tumor microenvironment cues

Cancer immunotherapies are highly potent and are gaining wide clinical usage. However, severe side effects require focusing effector immune cell activities on the tumor microenvironment (TME). We recently developed a chimeric antigen receptor tumor-induced vector (CARTIV), a synthetic promoter activated by TME factors. To improve CARTIV functions including background, activation levels, and synergism, we screened a library of promoters with variations in key positions. Here, we present a screening method involving turning ON/OFF stimulating TNFα and IFNγ cytokines, followed by sequential cell sorting. Sequencing of enriched promoters identified seventeen candidates, which were cloned and whose activities were then validated, leading to the identification of two CARTIVs with lower background and higher induction. We further combined a third hypoxia element with the two-factor CARTIV, demonstrating additional modular improvement. Our study presents a method of fine-tuning synthetic promoters for desired immunotherapy needs.

Refactoring transcription factors for metabolic engineering

Due to the ability to regulate target metabolic pathways globally and dynamically, metabolic regulation systems composed of transcription factors have been widely used in metabolic engineering and synthetic biology. This review introduced the categories, action principles, prediction strategies, and related databases of transcription factors. Then, the application of global transcription machinery engineering technology and the transcription factor-based biosensors and quorum sensing systems are overviewed. In addition, strategies for optimizing the transcriptional regulatory tools' performance by refactoring transcription factors are summarized. Finally, the current limitations and prospects of constructing various regulatory tools based on transcription factors are discussed. This review will provide theoretical guidance for the rational design and construction of transcription factor-based metabolic regulation systems.

In Silico Prediction Methods for Site-Saturation Mutagenesis

Directed enzyme evolution has proven to be a powerful means to endow biocatalysts with novel catalytic repertoires. Apart from completely random gene mutagenesis, site-directed or site-saturation mutagenesis requires a semi-rational selection of the amino acid positions or the substituted residues, which can dramatically reduce the screening efforts in protein engineering. To this end, in silico prediction methods play a pivotal role in targeting site-saturation mutagenesis. In this chapter, we provide two distinct computational methods, (a) conformational dynamics-guided design and (b) protein-ligand interaction fingerprinting analysis, to identify specific positions for site-saturation mutagenesis toward manipulating substrate specificity/stereoselectivity of an alcohol dehydrogenase, and improving activity of a carboxylic acid reductase, respectively.

Accurate Prediction of Protein Thermodynamic Stability Changes upon Residue Mutation using Free Energy Perturbation

This work describes the application of a physics-based computational approach to predict the relative thermodynamic stability of protein variants, and evaluates the quantitative accuracy of those predictions compared to experimental data obtained from a diverse set of protein systems assayed at variable pH conditions. Physical stability is a key determinant of the clinical and commercial success of biological therapeutics, vaccines, diagnostics, enzymes and other protein-based products. Although experimental techniques for measuring the impact of amino acid residue mutation on the stability of proteins exist, they tend to be time consuming and costly, hence the need for accurate prediction methods. In contrast to many of the commonly available computational methods for stability prediction, the Free Energy Perturbation approach applied in this paper explicitly accounts for solvent effects and samples conformational dynamics using a rigorous molecular dynamics simulation process. On the entire validation dataset, consisting of 328 single point mutations spread across 14 distinct protein structures, our results show good overall correlation with experiment with an R² of 0.65 and a low mean unsigned error of 0.95 kcal/mol. Application of the FEP approach in conjunction with experimental assessment techniques offers opportunities to lower the time and expense of product development and reduce the risk of costly late-stage failures.

Modification of DNA regions with metagenomic DNA fragments (MDRMDF): A convenient strategy for efficient protein engineering

In this study, we have established a convenient and efficient approach named Modification of DNA Regions with Metagenomic DNA Fragments (MDRMDF) for protein engineering. Degenerate primers were designed corresponding to conserved regions of the gene of interest which were used for amplification of fragments with template of the metagenomic DNA. The resulting PCR products were used to replace the corresponding regions of the gene of interest to introduce modified gene for function-based screening. Therefore, this method can make full use of the metagenomic DNA sequences with unknown metagenomic gene information for efficient protein engineering. The β-xylosidase BH3683 was used to construct a MDRMDF library which was screened with a newly designed p-NPX-M9 medium-based strategy. As a result, a mutant protein Xyl-M56 showing high activity, improved pH stability and higher tolerance to organic solvents was obtained which may have potential for industrial application. The MDRMDF method may find wide application in enzyme engineering, metabolic engineering and other fields, especially offering a new methodological option for the directed evolution of proteins.

Community-Wide Experimental Evaluation of the PROSS Stability-Design Method

Recent years have seen a dramatic improvement in protein-design methodology. Nevertheless, most methods demand expert intervention, limiting their widespread adoption. By contrast, the PROSS algorithm for improving protein stability and heterologous expression levels has been successfully applied to a range of challenging enzymes and binding proteins. Here, we benchmark the application of PROSS as a stand-alone tool for protein scientists with no or limited experience in modeling. Twelve laboratories from the Protein Production and Purification Partnership in Europe (P4EU) challenged the PROSS algorithm with 14 unrelated protein targets without support from the PROSS developers. For each target, up to six designs were evaluated for expression levels and in some cases, for thermal stability and activity. In nine targets, designs exhibited increased heterologous expression levels either in prokaryotic and/or eukaryotic expression systems under experimental conditions that were tailored for each target protein. Furthermore, we observed increased thermal stability in nine of ten tested targets. In two prime examples, the human Stem Cell Factor (hSCF) and human Cadherin-Like Domain (CLD12) from the RET receptor, the wild type proteins were not expressible as soluble proteins in E. coli, yet the PROSS designs exhibited high expression levels in E. coli and HEK293 cells, respectively, and improved thermal stability. We conclude that PROSS may improve stability and expressibility in diverse cases, and that improvement typically requires target-specific expression conditions. This study demonstrates the strengths of community-wide efforts to probe the generality of new methods and recommends areas for future research to advance practically useful algorithms for protein science.

Directed evolution for enzyme development in biocatalysis

As an important sector of the chemical industry, biocatalysis requires the continuous development of enzymes with tailor-made activity, selectivity, stability, or tolerance to unnatural environments. This is now routinely achieved by directed evolution based on iterative cycles of genetic diversification and activity screening. Here, we highlight its recent developments. First, the design of "smarter" libraries by focused mutagenesis may be a crucial start-up for a fast and successful outcome. Then library assembly and expression are also key steps that benefits from modern molecular biology progresses. Finally, various strategies may be considered for library screening depending on the final objective: while low-throughput direct assays have been very successful in generating enzymes for important biocatalytic processes, even in bringing completely new chemistries to the enzyme world, ultrahigh-throughput screening methods are emerging as powerful approaches for engineering the next generation of industrial enzymes.

Looking Back: A Short History of the Discovery of Enzymes and How They Became Powerful Chemical Tools

Enzymatic approaches to challenges in chemical synthesis are increasingly popular and very attractive to industry given their green nature and high efficiency compared to traditional methods. In this historical review we highlight the developments across several fields that were necessary to create the modern field of biocatalysis, with enzyme engineering and directed evolution at its core. We exemplify the modular, incremental, and highly unpredictable nature of scientific discovery, driven by curiosity, and showcase the resulting examples of cutting-edge enzymatic applications in industry.

Exploration of enzyme diversity: High-throughput techniques for protein production and microscale biochemical characterization

Enzymes are being increasingly utilized for acceleration of industrially and pharmaceutically critical chemical reactions. The strong demand for finding robust and efficient biocatalysts for these applications can be satisfied via the exploration of enzyme diversity. The first strategy is to mine the natural diversity, represented by millions of sequences available in the public genomic databases, by using computational approaches. Alternatively, metagenomic libraries can be targeted experimentally or computationally to explore the natural diversity of a specific environment. The second strategy, known as directed evolution, is to generate man-made diversity in the laboratory using gene mutagenesis and screen the constructed library of mutants. The selected hits must be experimentally characterized in both strategies, which currently represent the rate-limiting step in the process of diversity exploration. The traditional techniques used for biochemical characterization are time-demanding, cost, and sample volume ineffective, and low-throughput. Therefore, the development and implementation of high-throughput experimental methods are essential for discovering novel enzymes. This chapter describes the experimental protocols employing the combination of robust production and high-throughput microscale biochemical characterization of enzyme variants. We validated its applicability against the model enzyme family of haloalkane dehalogenases. These protocols can be adapted to other enzyme families, paving the way towards the functional characterization and quick identification of novel biocatalysts.

Unknown to Known: Advancing Knowledge of Coral Gene Function

Given the catastrophic changes befalling coral reefs, understanding coral gene function is essential to advance reef conservation. This has proved challenging due to the paucity of genomic data and genetic tools available for corals. Recently, CRISPR/Cas9 gene editing was applied to these species; however, a major bottleneck is the identification and prioritization of candidate genes for manipulation. This issue is exacerbated by the many unknown ('dark') coral genes that may play key roles in the stress response. We review the use of gene coexpression networks that incorporate both known and unknown genes to identify targets for reverse genetic analysis. This approach also provides a framework for the annotation of dark genes in established interaction networks to improve our fundamental knowledge of coral gene function.

Structural and biochemical insights into an engineered high-redox potential laccase overproduced in Aspergillus

Fungal laccases have great potential as biocatalysts oxidizing a variety of aromatic compounds using oxygen as co-substrate. Here, the crystal structure of 7D5 laccase (PDB 6H5Y), developed in Saccharomyces cerevisiae and overproduced in Aspergillus oryzae, is compared with that of the wild type produced by basidiomycete PM1 (Coriolopsis sp.), PDB 5ANH. SAXS showed both enzymes form monomers in solution, 7D5 laccase with a more oblate geometric structure due to heavier and more heterogeneous glycosylation. The enzyme presents superior catalytic constants towards all tested substrates, with no significant change in optimal pH or redox potential. It shows noticeable high catalytic efficiency with ABTS and dimethyl-4-phenylenediamine, 7 and 32 times better than the wild type, respectively. Computational simulations demonstrated a more favorable binding and electron transfer from the substrate to the T1 copper due to the introduced mutations. PM1 laccase is exceptionally stable to thermal inactivation (t_1/2 70 °C = 1.2 h). Yet, both enzymes display outstanding structural robustness at high temperature. They keep folded during 2 h at 100 °C though, thereafter, 7D5 laccase unfolds faster. Rigidification of certain loops due to the mutations added on the protein surface would diminish the capability to absorb temperature fluctuations leading to earlier protein unfolding.

Distant Non-Obvious Mutations Influence the Activity of a Hyperthermophilic Pyrococcus furiosus Phosphoglucose Isomerase

The cupin-type phosphoglucose isomerase (PfPGI) from the hyperthermophilic archaeon Pyrococcus furiosus catalyzes the reversible isomerization of glucose-6-phosphate to fructose-6-phosphate. We investigated PfPGI using protein-engineering bioinformatics tools to select functionally-important residues based on correlated mutation analyses. A pair of amino acids in the periphery of PfPGI was found to be the dominant co-evolving mutation. The position of these selected residues was found to be non-obvious to conventional protein engineering methods. We designed a small smart library of variants by substituting the co-evolved pair and screened their biochemical activity, which revealed their functional relevance. Four mutants were further selected from the library for purification, measurement of their specific activity, crystal structure determination, and metal cofactor coordination analysis. Though the mutant structures and metal cofactor coordination were strikingly similar, variations in their activity correlated with their fine-tuned dynamics and solvent access regulation. Alternative, small smart libraries for enzyme optimization are suggested by our approach, which is able to identify non-obvious yet beneficial mutations.

Artificial Metalloenzymes Based on the Biotin-Streptavidin Technology: Enzymatic Cascades and Directed Evolution

Artificial metalloenzymes (ArMs) result from anchoring a metal-containing moiety within a macromolecular scaffold (protein or oligonucleotide). The resulting hybrid catalyst combines attractive features of both homogeneous catalysts and enzymes. This strategy includes the possibility of optimizing the reaction by both chemical (catalyst design) and genetic means leading to achievement of a novel degree of (enantio)selectivity, broadening of the substrate scope, or increased activity, among others. In the past 20 years, the Ward group has exploited, among others, the biotin–(strept)avidin technology to localize a catalytic moiety within a well-defined protein environment. Streptavidin has proven versatile for the implementation of ArMs as it offers the following features: (i) it is an extremely robust protein scaffold, amenable to extensive genetic manipulation and mishandling, (ii) it can be expressed in E. coli to very high titers (up to >8 g·L^–1 in fed-batch cultures), and (iii) the cavity surrounding the biotinylated cofactor is commensurate with the size of a typical metal-catalyzed transition state. Relying on a chemogenetic optimization strategy, varying the orientation and the nature of the biotinylated cofactor within genetically engineered streptavidin, 12 reactions have been reported by the Ward group thus far. Recent efforts within our group have focused on extending the ArM technology to create complex systems for integration into biological cascade reactions and in vivo.

With the long-term goal of complementing in vivo natural enzymes with ArMs, we summarize herein three complementary research lines: (i) With the aim of mimicking complex cross-regulation mechanisms prevalent in metabolism, we have engineered enzyme cascades, including cross-regulated reactions, that rely on ArMs. These efforts highlight the remarkable (bio)compatibility and complementarity of ArMs with natural enzymes. (ii) Additionally, multiple-turnover catalysis in the cytoplasm of aerobic organisms was achieved with ArMs that are compatible with a glutathione-rich environment. This feat is demonstrated in HEK-293T cells that are engineered with a gene switch that is upregulated by an ArM equipped with a cell-penetrating module. (iii) Finally, ArMs offer the fascinating prospect of “endowing organometallic chemistry with a genetic memory.” With this goal in mind, we have identified E. coli’s periplasmic space and surface display to compartmentalize an ArM, while maintaining the critical phenotype–genotype linkage. This strategy offers a straightforward means to optimize by directed evolution the catalytic performance of ArMs. Five reactions have been optimized following these compartmentalization strategies: ruthenium-catalyzed olefin metathesis, ruthenium-catalyzed deallylation, iridium-catalyzed transfer hydrogenation, dirhodium-catalyzed cyclopropanation and carbene insertion in C–H bonds. Importantly, >100 turnovers were achieved with ArMs in E. coli whole cells, highlighting the multiple turnover catalytic nature of these systems.