High-Throughput Screening in Protein Engineering: Recent Advances and Future Perspectives

A snapshot of biomanufacturing and the need for enabling research infrastructure

Biomanufacturing is crucial for the bioeconomy, with growing investment and attention from industries and governments. Over recent decades numerous biotech companies have been founded, and policies have increasingly prioritised sustainable production methods. However, translation of biotechnological innovations into industrial applications remains challenging, requiring interdisciplinary research infrastructures (RIs) to address gaps in bioprocess development, scalability, and competitiveness. This opinion examines the current landscape of biomanufacturing and highlights the pivotal role of RIs in supporting these transitions. It also proposes enhanced research interoperability, standardisation, and democratisation through meta-workflows that streamline operations within and between RIs. By improving data sharing, process harmonisation, and scalability, these ecosystems can help to overcome technical and economic barriers in a concerted effort towards sustainable, bio-based global manufacturing.

Engineering thermostability of industrial enzymes for enhanced application performance

Thermostability is a key factor for the industrial application of enzymes. This review categorizes enzymes by their applications and discusses the importance of engineering thermostability for practical use. It summarizes fundamental theories and recent advancements in enzyme thermostability modification, including directed evolution, semi-rational design, and rational design. Directed evolution uses high-throughput screening to generate random mutations, while semi-rational design combines hotspot identification with screening. Rational design focuses on key residues to enhance stability by improving rigidity, foldability, and reducing aggregation. The review also covers rational strategies like engineering folding energy, surface charge, machine learning methods, and consensus design, along with tools that support these approaches. Practical examples are critically assessed to highlight the benefits and limitations of these strategies. Finally, the challenges and potential contributions of artificial intelligence in enzyme thermostability engineering are discussed.

High-throughput screening for optimizing adoptive T cell therapies

Adoptive T cell therapy is a pivotal strategy in cancer immunotherapy, demonstrating potent clinical efficacy. However, its limited durability often results in primary resistance. High-throughput screening technologies, which include both genetic and non-genetic approaches, facilitate the optimization of adoptive T cell therapies by enabling the selection of biologically significant targets or substances from extensive libraries. In this review, we examine advancements in high-throughput screening technologies and their applications in adoptive T cell therapies. We highlight the use of genetic screening for T cells, tumor cells, and other promising combination strategies, and elucidate the role of non-genetic screening in identifying small molecules and targeted delivery systems relevant to adoptive T cell therapies, providing guidance for future research and clinical applications.

Comprehensive Understanding of Laboratory Evolution for Food Enzymes: From Design to Screening Innovations

In the field of food processing, enzymes play a pivotal role in improving product quality and flavor, and extending shelf life. However, the exposure of traditional food enzymes to high temperatures during processing often leads to a decrease in activity or even inactivation, limiting the effectiveness of their application under high-temperature conditions. Therefore, the modification of thermostability and activity of enzymes to adapt to extreme conditions through protein engineering has become a key way to improve the efficiency and economic benefits of industrial production. Directed evolution and semirational design strategies in the laboratory have proven to be broadly applicable frameworks for biochemical researchers in the food field, including those who are beginners. In this review, we systematically summarize semirational design strategies and high-throughput screening strategies, and introduce some intuitive computer simulation software to improve the thermostability and enzyme activity of food enzymes. The application of these strategies and techniques provides a comprehensive guide for the optimization of food enzymes. In addition, the latest hot topics of genetically engineered food enzymes in the field of application are discussed.

GGAssembler: Precise and economical design and synthesis of combinatorial mutation libraries

Golden Gate assembly (GGA) can seamlessly generate full-length genes from DNA fragments. In principle, GGA could be used to design combinatorial mutation libraries for protein engineering, but creating accurate, complex, and cost-effective libraries has been challenging. We present GGAssembler, a graph-theoretical method for economical design of DNA fragments that assemble a combinatorial library that encodes any desired diversity. We used GGAssembler for one-pot in vitro assembly of camelid antibody libraries comprising >105 variants with DNA costs <0.007$ per variant and dropping significantly with increased library complexity. >93% of the desired variants were present in the assembly product and >99% were represented within the expected order of magnitude as verified by deep sequencing. The GGAssembler workflow is, therefore, an accurate approach for generating complex variant libraries that may drastically reduce costs and accelerate discovery and optimization of antibodies, enzymes and other proteins. The workflow is accessible through a Google Colab notebook at https://github.com/Fleishman-Lab/GGAssembler.

Integrating Computational Design and Experimental Approaches for Next-Generation Biologics

Therapeutic protein engineering has revolutionized medicine by enabling the development of highly specific and potent treatments for a wide range of diseases. This review examines recent advances in computational and experimental approaches for engineering improved protein therapeutics. Key areas of focus include antibody engineering, enzyme replacement therapies, and cytokine-based drugs. Computational methods like structure-based design, machine learning integration, and protein language models have dramatically enhanced our ability to predict protein properties and guide engineering efforts. Experimental techniques such as directed evolution and rational design approaches continue to evolve, with high-throughput methods accelerating the discovery process. Applications of these methods have led to breakthroughs in affinity maturation, bispecific antibodies, enzyme stability enhancement, and the development of conditionally active cytokines. Emerging approaches like intracellular protein delivery, stimulus-responsive proteins, and de novo designed therapeutic proteins offer exciting new possibilities. However, challenges remain in predicting in vivo behavior, scalable manufacturing, immunogenicity mitigation, and targeted delivery. Addressing these challenges will require continued integration of computational and experimental methods, as well as a deeper understanding of protein behavior in complex physiological environments. As the field advances, we can anticipate increasingly sophisticated and effective protein therapeutics for treating human diseases.

Progress in Identification of UDP-Glycosyltransferases for Ginsenoside Biosynthesis

Ginsenosides, the primary pharmacologically active constituents of the Panax genus, have demonstrated a variety of medicinal properties, including anticardiovascular disease, cytotoxic, antiaging, and antidiabetes effects. However, the low concentration of ginsenosides in plants and the challenges associated with their extraction impede the advancement and application of ginsenosides. Heterologous biosynthesis represents a promising strategy for the targeted production of these natural active compounds. As representative triterpenoids, the biosynthetic pathway of the aglycone skeletons of ginsenosides has been successfully decoded. While the sugar moiety is vital for the structural diversity and pharmacological activity of ginsenosides, the mining of uridine diphosphate-dependent glycosyltransferases (UGTs) involved in ginsenoside biosynthesis has attracted a lot of attention and made great progress in recent years. In this paper, we summarize the identification and functional study of UGTs responsible for ginsenoside synthesis in both plants, such as Panax ginseng and Gynostemma pentaphyllum, and microorganisms including Bacillus subtilis and Saccharomyces cerevisiae. The UGT-related microbial cell factories for large-scale ginsenoside production are also mentioned. Additionally, we delve into strategies for UGT mining, particularly potential rapid screening or identification methods, providing insights and prospects. This review provides insights into the study of other unknown glycosyltransferases as candidate genetic elements for the heterologous biosynthesis of rare ginsenosides.

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.

Semirational engineering of Cytophaga hutchinsonii polyphosphate kinase for developing a cost-effective, robust, and efficient adenosine 5'-triphosphate regeneration system

IMPORTANCE

The adenosine 5'-triphosphate (ATP) regeneration system can significantly reduce the cost of many biocatalytic processes. Numerous studies have endeavored to utilize the ATP regeneration system based on Cytophaga hutchinsonii PPK (ChPPK). However, the wild-type ChPPK enzyme possesses limitations such as low enzymatic activity, poor stability, and limited substrate tolerance, impeding its application in catalytic reactions. To enhance the performance of ChPPK, we employed a semi-rational design approach to obtain the variant ChPPK/A79G/S106C/I108F/L285P. The enzymatic kinetic parameters and the catalytic performance in the synthesis of nicotinamide mononucleotide demonstrated that the variant ChPPK/A79G/S106C/I108F/L285P exhibited superior enzymatic properties than the wild-type enzyme. All data indicated that our engineered ATP regeneration system holds inherent potential for implementation in biocatalytic processes.

Fundamental concepts of protein therapeutics and spacing in oncology: an updated comprehensive review

Current treatment regimens in cancer cases cause significant side effects and cannot effectively eradicate the advanced disease. Hence, much effort has been expended over the past years to understand how cancer grows and responds to therapies. Meanwhile, proteins as a type of biopolymers have been under commercial development for over three decades and have been proven to improve the healthcare system as effective medicines for treating many types of progressive disease, such as cancer. Following approving the first recombinant protein therapeutics by FDA (Humulin), there have been a revolution for drawing attention toward protein-based therapeutics (PTs). Since then, the ability to tailor proteins with ideal pharmacokinetics has provided the pharmaceutical industry with an important noble path to discuss the clinical potential of proteins in oncology research. Unlike traditional chemotherapy molecules, PTs actively target cancerous cells by binding to their surface receptors and the other biomarkers particularly associated with tumorous or healthy tissue. This review analyzes the potential and limitations of protein therapeutics (PTs) in the treatment of cancer as well as highlighting the evolving strategies by addressing all possible factors, including pharmacology profile and targeted therapy approaches. This review provides a comprehensive overview of the current state of PTs in oncology, including their pharmacology profile, targeted therapy approaches, and prospects. The reviewed data show that several current and future challenges remain to make PTs a promising and effective anticancer drug, such as safety, immunogenicity, protein stability/degradation, and protein-adjuvant interactions.

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.

Directed Evolution of Laccase for Improved Thermal Stability Facilitated by Droplet-Based Microfluidic Screening System

Laccases are attractive biocatalysts for industry due to their broad substrate spectrum, the use of oxygen as final electron acceptor, and water as the sole byproduct. Increasing efforts have been devoted to the engineering of laccases to improve their properties. The droplet-based microfluidic screening (DMFS) technology can accelerate the screening procedure and probe the large sequence space. In this study, a DMFS system including a heating step and picoinjection was used to sort large laccase libraries, yielding 12 variants with enhanced thermotolerance. All the obtained amino acid substitutions are distributed on the surface of the laccase. Interestingly, recombination of three identified substitutions of Asp to Asn on the surface resulted in the best variant M20, exhibiting 24.0-fold higher remaining activity at 58.8 °C and 1.9-3.4-fold higher remaining activity after incubation in organic solvents solution (20% (v/v) methanol and ethanol) and ionic liquid solution (20% (v/v) 1-ethyl-3-methylimidazolium ethyl sulfate) for 12 h. Furthermore, molecular dynamic simulations revealed that the recombination of the three beneficial substitutions, Asp98Asn, Asp474Asn, and Asp340Asn on the surface introduced more hydrogen bonds compared to the wild type, which made M20 more thermostable. This study highlighted the importance of the DMFS system for an efficient identification of beneficial long-distance amino acid substitutions.

Strategies for Improving Small-Molecule Biosensors in Bacteria

In recent years, small-molecule biosensors have become increasingly important in synthetic biology and biochemistry, with numerous new applications continuing to be developed throughout the field. For many biosensors, however, their utility is hindered by poor functionality. Here, we review the known types of mechanisms of biosensors within bacterial cells, and the types of approaches for optimizing different biosensor functional parameters. Discussed approaches for improving biosensor functionality include methods of directly engineering biosensor genes, considerations for choosing genetic reporters, approaches for tuning gene expression, and strategies for incorporating additional genetic modules.

Comparison of electrostatic and mechanical cell sorting with limited starting material

Isolation of multiple cell populations from limited starting material and with minimal influence on cell homeostasis and viability are common requirements in both basic and clinical research. Fluorescence-activated cell sorting (FACS) is the most commonly applied sorting methodology with the majority of instruments being based on high pressure and electrostatic deflection. A more recent technology is based on a mechanical valve, operating at low pressure. In the present work we compared the two technologies by parallel sorting of small amounts of peripheral blood and umbilical cord blood on a BD FACSAria™ III and Miltenyi MACSQuant® Tyto® instrument. Concurrent manually performed magnetic-based cell sorting served as reference. Sorting metrics, including purity and viability, were compared. Expression of the heat-shock protein HSPA1A immediately post sorting and the proliferation potential of sorted T-cells in vitro was assessed. In general, there was little to distinguish the two fluorescence-activated technologies with regard to sorting metrics and HSPA1A expression. Variation, however, with respect to recovery and viability, was much smaller among Tyto sorted samples. The proliferation potential of Tyto-sorted T-cells was significantly higher compared to Aria-sorted T-cells, indicating that T-cells of the Tyto instrument are less perturbed. In summary, cell types of blood origin including CD34⁺ cells could effectively be isolated from small input amounts with either fluorescence-activated technology with little immediate effect on viability. The mechanical valve-based sorting by the Tyto instrument; however, appeared to perturb the cells to a lesser extent as judged by their proliferation potential.

Enhancement of protein thermostability by three consecutive mutations using loop-walking method and machine learning

We developed a method to improve protein thermostability, “loop-walking method”. Three consecutive positions in 12 loops of Burkholderia cepacia lipase were subjected to random mutagenesis to make 12 libraries. Screening allowed us to identify L7 as a hot-spot loop having an impact on thermostability, and the P233G/L234E/V235M mutant was found from 214 variants in the L7 library. Although a more excellent mutant might be discovered by screening all the 8000 P233X/L234X/V235X mutants, it was difficult to assay all of them. We therefore employed machine learning. Using thermostability data of the 214 mutants, a computational discrimination model was constructed to predict thermostability potentials. Among 7786 combinations ranked in silico, 20 promising candidates were selected and assayed. The P233D/L234P/V235S mutant retained 66% activity after heat treatment at 60 °C for 30 min, which was higher than those of the wild-type enzyme (5%) and the P233G/L234E/V235M mutant (35%).

Synthetic Biological Approaches for Optogenetics and Tools for Transcriptional Light-Control in Bacteria

Light has become established as a tool not only to visualize and investigate but also to steer biological systems. This review starts by discussing the unique features that make light such an effective control input in biology. It then gives an overview of how light-control came to progress, starting with photoactivatable compounds and leading up to current genetic implementations using optogenetic approaches. The review then zooms in on optogenetics, focusing on photosensitive proteins, which form the basis for optogenetic engineering using synthetic biological approaches. As the regulation of transcription provides a highly versatile means for steering diverse biological functions, the focus of this review then shifts to transcriptional light regulators, which are presented in the biotechnologically highly relevant model organism Escherichia coli.

A systematic analysis of the beta hairpin motif in the Protein Data Bank

The beta hairpin motif is a ubiquitous protein structural motif that can be found in molecules across the tree of life. This motif, which is also popular in synthetically designed proteins and peptides, is known for its stability and adaptability to broad functions. Here, we systematically probe all 49,000 unique beta hairpin substructures contained within the Protein Data Bank (PDB) to uncover key characteristics correlated with stable beta hairpin structure, including amino acid biases and enriched interstrand contacts. We find that position specific amino acid preferences, while seen throughout the beta hairpin structure, are most evident within the turn region, where they depend on subtle turn dynamics associated with turn length and secondary structure. We also establish a set of broad design principles, such as the inclusion of aspartic acid residues at a specific position and the careful consideration of desired secondary structure when selecting residues for the turn region, that can be applied to the generation of libraries encoding proteins or peptides containing beta hairpin structures.

Stable and selective permeable hydrogel microcapsules for high-throughput cell cultivation and enzymatic analysis

BACKGROUND

Miniaturization of biochemical reaction volumes within artificial microcompartments has been the key driver for directed evolution of several catalysts in the past two decades. Typically, single cells are co-compartmentalized within water-in-oil emulsion droplets with a fluorogenic substrate whose conversion allows identification of catalysts with improved performance. However, emulsion droplet-based technologies prevent cell proliferation to high density and preclude the feasibility of biochemical reactions that require the exchange of small molecule substrates. Here, we report on the development of a high-throughput screening method that addresses these shortcomings and that relies on a novel selective permeable polymer hydrogel microcapsule.

RESULTS

Hollow-core polyelectrolyte-coated chitosan alginate microcapsules (HC-PCAMs) with selective permeability were successfully constructed by jet break-up and layer-by-layer (LBL) technology. We showed that HC-PCAMs serve as miniaturized vessels for single cell encapsulation, enabling cell growth to high density and cell lysis to generate monoclonal cell lysate compartments suitable for high-throughput analysis using a large particle sorter (COPAS). The feasibility of using HC-PCAMs as reaction compartments which exchange small molecule substrates was demonstrated using the transpeptidation reaction catalyzed by the bond-forming enzyme sortase F from P. acnes. The polyelectrolyte shell surrounding microcapsules allowed a fluorescently labelled peptide substrate to enter the microcapsule and take part in the transpeptidation reaction catalyzed by the intracellularly expressed sortase enzyme retained within the capsule upon cell lysis. The specific retention of fluorescent transpeptidation products inside microcapsules enabled the sortase activity to be linked with a fluorescent readout and allowed clear separation of microcapsules expressing the wild type SrtF from those expressing the inactive variant.

CONCLUSION

A novel polymer hydrogel microcapsule-based method, which allows for high-throughput analysis based on encapsulation of single cells has been developed. The method has been validated for the transpeptidation activity of sortase enzymes and represents a powerful tool for screening of libraries of sortases, other bond-forming enzymes, as well as of binding affinities in directed evolution experiments. Moreover, selective permeable microcapsules encapsulating microcolonies provide a new and efficient means for preparing novel caged biocatalyst and biosensor agents.

In Vitro Selection of Peptides and Proteins-Advantages of mRNA Display

mRNA display is a robust in vitro selection technique that allows the selection of peptides and proteins with desired functions from libraries of trillions of variants. mRNA display relies upon a covalent linkage between a protein and its encoding mRNA molecule; the power of the technique stems from the stability of this link, and the large degree of control over experimental conditions afforded to the researcher. This article describes the major advantages that make mRNA display the method of choice among comparable in vivo and in vitro methods, including cell-surface display, phage display, and ribosomal display. We also describe innovative techniques that harness mRNA display for directed evolution, protein engineering, and drug discovery.

High-Throughput Approaches in Carbohydrate-Active Enzymology: Glycosidase and Glycosyl Transferase Inhibitors, Evolution, and Discovery

Carbohydrates are attached and removed in living systems through the action of carbohydrate-active enzymes such as glycosyl transferases and glycoside hydrolases. The molecules resulting from these enzymes have many important roles in organisms, such as cellular communication, structural support, and energy metabolism. In general, each carbohydrate transformation requires a separate catalyst, and so these enzyme families are extremely diverse. To make this diversity manageable, high-throughput approaches look at many enzymes at once. Similarly, high-throughput approaches can be a powerful way of finding inhibitors that can be used to tune the reactivity of these enzymes, either in an industrial, a laboratory, or a medicinal setting. In this review, we provide an overview of how these enzymes and inhibitors can be sought using techniques such as high-throughput natural product and combinatorial library screening, phage and mRNA display of (glyco)peptides, fluorescence-activated cell sorting, and metagenomics.

High-throughput droplet-based microfluidics for directed evolution of enzymes

Natural enzymes have evolved over millions of years to allow for their effective operation within specific environments. However, it is significant to note that despite their wide structural and chemical diversity, relatively few natural enzymes have been successfully applied to industrial processes. To address this limitation, directed evolution (DE) (a method that mimics the process of natural selection to evolve proteins toward a user‐defined goal) coupled with droplet‐based microfluidics allows the detailed analysis of millions of enzyme variants on ultra‐short timescales, and thus the design of novel enzymes with bespoke properties. In this review, we aim at presenting the development of DE over the last years and highlighting the most important advancements in droplet‐based microfluidics, made in this context towards the high‐throughput demands of enzyme optimization. Specifically, an overview of the range of microfluidic unit operations available for the construction of DE platforms is provided, focusing on their suitability and benefits for cell‐based assays, as in the case of directed evolution experimentations.

Natural selection in compartmentalized environment with reshuffling

The emerging field of high-throughput compartmentalized in vitro evolution is a promising new approach to protein engineering. In these experiments, libraries of mutant genotypes are randomly distributed and expressed in microscopic compartments-droplets of an emulsion. The selection of desirable variants is performed according to the phenotype of each compartment. The random partitioning leads to a fraction of compartments receiving more than one genotype making the whole process a lab implementation of the group selection. From a practical point of view (where efficient selection is typically sought), it is important to know the impact of the increase in the mean occupancy of compartments on the selection efficiency. We carried out a theoretical investigation of this problem in the context of selection dynamics for an infinite non-mutating subdivided population that randomly colonizes an infinite number of patches (compartments) at each reproduction cycle. We derive here an update equation for any distribution of phenotypes and any value of the mean occupancy. Using this result, we demonstrate that, for the linear additive fitness, the best genotype is still selected regardless of the mean occupancy. Furthermore, the selection process is remarkably resilient to the presence of multiple genotypes per compartments, and slows down approximately inversely proportional to the mean occupancy at high values. We extend out results to more general expressions that cover nonadditive and non-linear fitnesses, as well non-Poissonian distribution among compartments. Our conclusions may also apply to natural genetic compartmentalized replicators, such as viruses or early trans-acting RNA replicators.

Recent Advances in Droplet-based Microfluidic Technologies for Biochemistry and Molecular Biology

Recently, droplet-based microfluidic systems have been widely used in various biochemical and molecular biological assays. Since this platform technique allows manipulation of large amounts of data and also provides absolute accuracy in comparison to conventional bioanalytical approaches, over the last decade a range of basic biochemical and molecular biological operations have been transferred to drop-based microfluidic formats. In this review, we introduce recent advances and examples of droplet-based microfluidic techniques that have been applied in biochemistry and molecular biology research including genomics, proteomics and cellomics. Their advantages and weaknesses in various applications are also comprehensively discussed here. The purpose of this review is to provide a new point of view and current status in droplet-based microfluidics to biochemists and molecular biologists. We hope that this review will accelerate communications between researchers who are working in droplet-based microfluidics, biochemistry and molecular biology.

Inhibition of PD1:PD-L1 interaction by an E. coli-derived optimized PD1 variant

Immune-checkpoint receptors are a set of signal transduction proteins that can stimulate or inhibit specific anti-tumor responses. It is well established that cancer cells interact with different immune checkpoints to shut down T-cell response, thereby enabling cancer proliferation. Given the importance of immune checkpoint receptors, a structure-function analysis of these systems is imperative. However, recombinant expression and purification of these membrane originated proteins is still a challenge. Therefore, many attempts are being made to improve their expression and solubility while preserving their biological relevance. For this purpose, we designed an E. coli-based optimization system that enables the acquisition of mutations that increases protein solubility and affinity towards its native ligand, while maintaining biological activity. Here we focused on the well-characterized extracellular domain of the 'programmed cell death protein 1' (PD1), an immune checkpoint receptor known to inhibit T-cell proliferation by interacting with its ligands PD-L1 and PD-L2. The simple ELISA-based screening system shown here enabled the identification of high-affinity, highly soluble, functional variants derived from the extracellular domain of human PD1. The system was based on the expression of a GST-tagged variants library in E. coli, which enabled the selection of improved PD1 variants after a single optimization round. Within only two screening rounds, the most active variant showed a 5-fold higher affinity and 2.4-fold enhanced cellular activity as compared to the wild type protein. This scheme can be translated toward other types of challenging receptors toward development of research tools or alternative therapeutics.

Engineered N-acetylhexosamine-active enzymes in glycoscience

BACKGROUND

In recent years, enzymes modifying N-acetylhexosamine substrates have emerged in numerous theoretical studies as well as practical applications from biology, biomedicine, and biotechnology. Advanced enzyme engineering techniques converted them into potent synthetic instruments affording a variety of valuable glycosides.

SCOPE OF REVIEW

This review presents the diversity of engineered enzymes active with N-acetylhexosamine carbohydrates: from popular glycoside hydrolases and glycosyltransferases to less known oxidases, epimerases, kinases, sulfotransferases, and acetylases. Though hydrolases in natura, engineered chitinases, β-N-acetylhexosaminidases, and endo-β-N-acetylglucosaminidases were successfully employed in the synthesis of defined natural and derivatized chitooligomers and in the remodeling of N-glycosylation patterns of therapeutic antibodies. The genes of various N-acetylhexosaminyltransferases were cloned into metabolically engineered microorganisms for producing human milk oligosaccharides, Lewis X structures, and human-like glycoproteins. Moreover, mutant N-acetylhexosamine-active glycosyltransferases were applied, e.g., in the construction of glycomimetics and complex glycostructures, industrial production of low-lactose milk, and metabolic labeling of glycans. In the synthesis of biotechnologically important compounds, several innovative glycoengineered systems are presented for an efficient bioproduction of GlcNAc, UDP-GlcNAc, N-acetylneuraminic acid, and of defined glycosaminoglycans.

MAJOR CONCLUSIONS

The above examples demonstrate that engineering of N-acetylhexosamine-active enzymes was able to solve complex issues such as synthesis of tailored human-like glycoproteins or industrial-scale production of desired oligosaccharides. Due to the specific catalytic mechanism, mutagenesis of these catalysts was often realized through rational solutions.

GENERAL SIGNIFICANCE

Specific N-acetylhexosamine glycosylation is crucial in biological, biomedical and biotechnological applications and a good understanding of its details opens new possibilities in this fast developing area of glycoscience.

Plasmonic Nanosensors for the Determination of Drug Effectiveness on Membrane Receptors

We demonstrate the potential of the NanoSPR (nanoscale surface plasmon resonance sensors) method as a simple and cheap tool for the quantitative study of membrane protein-protein interactions. We use NanoSPR to determine the effectiveness of two potential drug candidates that inhibit the protein complex formation between FtsA and ZipA at initial stages of bacterial division. As the NanoSPR method relies on individual gold nanorods as sensing elements, there is no need for fluorescent labels or organic cosolvents, and it provides intrinsically high statistics. NanoSPR could become a powerful tool in drug development, drug delivery, and membrane studies.

The Generation and Exploitation of Protein Mutability Landscapes for Enzyme Engineering

The increasing number of enzyme applications in chemical synthesis calls for new engineering methods to develop the biocatalysts of the future. An interesting concept in enzyme engineering is the generation of large-scale mutational data in order to chart protein mutability landscapes. These landscapes allow the important discrimination between beneficial mutations and those that are neutral or detrimental, thus providing detailed insight into sequence-function relationships. As such, mutability landscapes are a powerful tool with which to identify functional hotspots at any place in the amino acid sequence of an enzyme. These hotspots can be used as targets for combinatorial mutagenesis to yield superior enzymes with improved catalytic properties, stability, or even new enzymatic activities. The generation of mutability landscapes for multiple properties of one enzyme provides the exciting opportunity to select mutations that are beneficial either for one or for several of these properties. This review presents an overview of the recent advances in the construction of mutability landscapes and discusses their importance for enzyme engineering.