Protein Engineering Research Articles

A strategy for successful dual-species protein expression of genes with non-optimal codon usage destined for bacterial and yeast cell factories.

Recombinant protein expression on an industrial scale traditionally utilizes one of two microbial workhorses: Escherichia coli or Saccharomyces cerevisiae. Additionally, random protein engineering of enzymes and proteins aimed for expression in S. cerevisiae are often mutagenized and pre-screened in E. coli before expression in yeast. This introduces artificial bottlenecks as the bacterial expression vector needs to be substituted for a yeast expression vector via sub-cloning, and the new library re-evaluated before a final screening in yeast. Here, we put forward a protein expression and engineering strategy that involves the use of a dual-host shuttle vector (pYB-Dual) designed with both a strong inducible yeast promoter (pGAL1), and a strong inducible bacterial promoter (pT7-RNAP), which allows for inducible protein expression in both species. Additionally, we demonstrate that by transforming the pYB-Dual vector into the E. coli strain Rosetta 2, which has elevated levels of 7 rare tRNAs, we can achieve high-level protein expression in both yeast and bacteria, even when using a mNeonGreen gene codon optimized for yeast. This dual expression vector is expected to remove bottlenecks during protein engineering of commercially important enzymes destined for high-titer expression in yeast.

Sequence-guidedRedesign of an Omega-transaminase from Bacillus megaterium for theAsymmetric Synthesis of Chiral Amines.

ω-Transaminases (ω-TAs) are attractive biocatalysts asymmetrically catalyzing ketones to chiral amines. However, poor non-native catalytic activity and substrate promiscuity severely hamper its wide application in industrial production. Protein engineering efforts have generally focused on reshaping the substrate-binding pockets of ω-TAs. However, hotspots around the substrate tunnel as well as distant sites outside the pockets may also affect its activity. In this study, the ω-TA from Bacillus megaterium (BmeTA) was selected for engineering. The tunnel mutation Y164F synergy with distant mutation A245T which was acquired through a multiple sequence alignment showed improved soluble expression, a 3.7-fold higher specific activity and a 19.9-fold longer half-life at 45℃. Molecule Dynamics simulation explains the mechanism of improved catalytic activity, enhanced thermostability and improved soluble expression of BmeTAY164F/A245T(2M). Finally, the resting cells of 2M were used for biocatalytic processes. 450 mM of S-methoxyisopropylamine (S-MOIPA) was obtained with an ee value of 97.3% and a conversion rate of 90%, laying the foundation for its industrial production. Mutant 2M was also found to be more advantageous in catalyzing the transamination of various ketones. These results demonstrated that sites that are far away from the active center also play an important role in the redesign of ω-TAs.

Chemoenzymatic Synthesis of 2‐Aryl Thiazolines from 4‐Hydroxybenzaldehydes Using Vanillyl Alcohol Oxidases

Nitrogen heterocycles are commonly found in bioactive natural products and drugs. However, the biocatalytic tools for nitrogen heterocycle synthesis are limited. Herein, we report the discovery of vanillyl alcohol oxidases (VAOs) as efficient biocatalysts for the one‐pot synthesis of 2‐aryl thiazolines from various 4‐hydroxybenzaldehydes and aminothiols. The wild‐type biocatalyst features a broad scope of 4‐hydroxybenzaldehydes. Though the scope of aminothiols is limited, it could be improved via semi‐rational protein engineering, generating a variant to produce previously inaccessible cysteine‐derived bioactive 2‐aryl thiazolines using the wild‐type VAO. Benefiting from the derivatizable functional groups in the enzymatic products, we further chemically modified these products to expand the chemical space, offering a new chemoenzymatic strategy for the green and efficient synthesis of structurally diverse 2‐aryl‐thiazoline derivatives to prompt their use in drug discovery and catalysis.

Genotype sampling for deep-learning assisted experimental mapping of a combinatorially complete fitness landscape.

Experimental characterization of fitness landscapes, which map genotypes onto fitness, is important for both evolutionary biology and protein engineering. It faces a fundamental obstacle in the astronomical number of genotypes whose fitness needs to be measured for any one protein. Deep learning may help to predict the fitness of many genotypes from a smaller neural network training sample of genotypes with experimentally measured fitness. Here I use a recently published experimentally mapped fitness landscape of more than 260,000 protein genotypes to ask how such sampling is best performed. I show that multilayer perceptrons, recurrent neural networks (RNNs), convolutional networks, and transformers, can explain more than 90 percent of fitness variance in the data. In addition, 90 percent of this performance is reached with a training sample comprising merely ≈103 sequences. Generalization to unseen test data is best when training data is sampled randomly and uniformly, or sampled to minimize the number of synonymous sequences. In contrast, sampling to maximize sequence diversity or codon usage bias reduces performance substantially. These observations hold for more than one network architecture. Simple sampling strategies may perform best when training deep learning neural networks to map fitness landscapes from experimental data. The fitness landscape data analyzed here is publicly available as described previously (Papkou, et al., 2023). All code used to analyze this landscape is publicly available at https://github.com/andreas-wagner-uzh/fitness_landscape_sampling. Supplementary data are available at Bioinformatics online.

Material-specific binding peptides empower sustainable innovations in plant health, biocatalysis, medicine and microplastic quantification.

Material-binding peptides (MBPs) have emerged as a diverse and innovation-enabling class of peptides in applications such as plant-/human health, immobilization of catalysts, bioactive coatings, accelerated polymer degradation and analytics for micro-/nanoplastics quantification. Progress has been fuelled by recent advancements in protein engineering methodologies and advances in computational and analytical methodologies, which allow the design of, for instance, material-specific MBPs with fine-tuned binding strength for numerous demands in material science applications. A genetic or chemical conjugation of second (biological, chemical or physical property-changing) functionality to MBPs empowers the design of advanced (hybrid) materials, bioactive coatings and analytical tools. In this review, we provide a comprehensive overview comprising naturally occurring MBPs and their function in nature, binding properties of short man-made MBPs (<20 amino acids) mainly obtained from phage-display libraries, and medium-sized binding peptides (20-100 amino acids) that have been reported to bind to metals, polymers or other industrially produced materials. The goal of this review is to provide an in-depth understanding of molecular interactions between materials and material-specific binding peptides, and thereby empower the use of MBPs in material science applications. Protein engineering methodologies and selected examples to tailor MBPs toward applications in agriculture with a focus on plant health, biocatalysis, medicine and environmental monitoring serve as examples of the transformative power of MBPs for various industrial applications. An emphasis will be given to MBPs' role in detecting and quantifying microplastics in high throughput, distinguishing microplastics from other environmental particles, and thereby assisting to close an analytical gap in food safety and monitoring of environmental plastic pollution. In essence, this review aims to provide an overview among researchers from diverse disciplines in respect to material-(specific) binding of MBPs, protein engineering methodologies to tailor their properties to application demands, re-engineering for material science applications using MBPs, and thereby inspire researchers to employ MBPs in their research.

Influence of Cluster-Situated Regulator PteF in Filipin Biosynthetic Cluster on Avermectin Biosynthesis in Streptomyces avermitilis

Crosstalk regulation is widespread in Streptomyces species. Elucidating the influence of a specific regulator on target biosynthetic gene clusters (BGCs) and cell metabolism is crucial for strain improvement through regulatory protein engineering. PteF and PteR are two regulators that control the biosynthesis of filipin, which competes for building blocks with avermectins in Streptomyces avermitilis. However, little is known about the effects of PteF and PteR on avermectin biosynthesis. In this study, we investigated their impact on avermectin biosynthesis and global cell metabolism. The deletion of pteF resulted in a 55.49% avermectin titer improvement, which was 23.08% higher than that observed from pteR deletion, suggesting that PteF plays a more significant role in regulating avermectin biosynthesis, while PteF hardly influences the transcription level of genes in avermectin and other polyketide BGCs. Transcriptome data revealed that PteF exhibited a global regulatory effect. Avermectin production enhancement could be attributed to the repression of the tricarboxylic acid cycle and fatty acid biosynthetic pathway, as well as the enhancement of pathways supplying acyl-CoA precursors. These findings provide new insights into the role of PteF on avermectin biosynthesis and cell metabolism, offering important clues for designing and building efficient metabolic pathways to develop high-yield avermectin-producing strains.

Chemoenzymatic Synthesis of 2-Aryl Thiazolines from 4-Hydroxybenzaldehydes Using Vanillyl Alcohol Oxidases.

Nitrogen heterocycles are commonly found in bioactive natural products and drugs. However, the biocatalytic tools for nitrogen heterocycle synthesis are limited. Herein, we report the discovery of vanillyl alcohol oxidases (VAOs) as efficient biocatalysts for the one-pot synthesis of 2-aryl thiazolines from various 4-hydroxybenzaldehydes and aminothiols. The wild-type biocatalyst features a broad scope of 4-hydroxybenzaldehydes. Though the scope of aminothiols is limited, it could be improved via semi-rational protein engineering, generating a variant to produce previously inaccessible cysteine-derived bioactive 2-aryl thiazolines using the wild-type VAO. Benefiting from the derivatizable functional groups in the enzymatic products, we further chemically modified these products to expand the chemical space, offering a new chemoenzymatic strategy for the green and efficient synthesis of structurally diverse 2-aryl-thiazoline derivatives to prompt their use in drug discovery and catalysis.

Antibodies expand the scope of angiotensin receptor pharmacology.

G-protein-coupled receptors (GPCRs) are key regulators of human physiology and are the targets of many small-molecule research compounds and therapeutic drugs. While most of these ligands bind to their target GPCR with high affinity, selectivity is often limited at the receptor, tissue and cellular levels. Antibodies have the potential to address these limitations but their properties as GPCR ligands remain poorly characterized. Here, using protein engineering, pharmacological assays and structural studies, we develop maternally selective heavy-chain-only antibody ('nanobody') antagonists against the angiotensin II type I receptor and uncover the unusual molecular basis of their receptor antagonism. We further show that our nanobodies can simultaneously bind to angiotensin II type I receptor with specific small-molecule antagonists and demonstrate that ligand selectivity can be readily tuned. Our work illustrates that antibody fragments can exhibit rich and evolvable pharmacology, attesting to their potential as next-generation GPCR modulators.

PROSCA: an online platform for humanized scaffold mining facilitating rational protein engineering.

Protein scaffolds with small size, high stability and low immunogenicity show important applications in the field of protein engineering and design. However, no relevant computational platform has been reported yet to mining such scaffolds with the desired properties from massive protein structures in human body. Here, we developed PROSCA, a structure-based online platform dedicated to explore the space of the entire human proteome, and to discovery new privileged protein scaffolds with potential engineering value that have never been noticed. PROSCA accepts structure of protein as an input, which can be subsequently aligned with a certain class of protein structures (e.g. the human proteome either from experientially resolved or AlphaFold2 predicted structures, and the human proteins belonging to specific families or domains), and outputs humanized protein scaffolds which are structurally similar with the input protein as well as other related important information such as families, sequences, structures and expression level in human tissues. Through PROSCA, the user can also get excellent experience in visualizations of protein structures and expression overviews, and download the figures and tables of results which can be customized according to the user's needs. Along with the advanced protein engineering and selection technologies, PROSCA will facilitate the rational design of new functional proteins with privileged scaffolds. PROSCA is freely available at https://idrblab.org/prosca/.

Construct Phenylethanoid Glycosides Harnessing Biosynthetic Networks, Protein Engineering and One‐Pot Multienzyme Cascades

AbstractPhenylethanoid glycosides (PhGs) exhibit a multitude of structural variations linked to diverse pharmacological activities. Assembling various PhGs via multienzyme cascades represents a concise strategy over traditional synthetic methods. However, the challenge lies in identifying a comprehensive set of catalytic enzymes. This study explores biosynthetic PhG reconstruction from natural precursors, aiming to replicate and amplify their structural diversity. We discovered 12 catalytic enzymes, including four novel 6′‐OH glycosyltransferases and three new polyphenol oxidases, revealing the intricate network in PhG biosynthesis. Subsequently, the crystal structure of CmGT3 (2.62 Å) was obtained, guiding the identification of conserved residue 144# as a critical determinant for sugar donor specificity. Engineering this residue in PhG glycosyltransferases (FsGT61, CmGT3, and FsGT6) altered their sugar donor recognition. Finally, a one‐pot multienzyme cascade was established, where the combined action of glycosyltransferases and acyltransferases boosted conversion rates by up to 12.6‐fold. This cascade facilitated the reconstruction of 26 PhGs with conversion rates ranging from 5–100 %, and 20 additional PhGs detectable by mass spectrometry. PhGs with extra glycosyl and hydroxyl modules demonstrated notable liver cell protection. This work not only provides catalytic tools for PhG biosynthesis, but also serves as a proof‐of‐concept for cell‐free enzymatic construction of diverse natural products.

Construct Phenylethanoid Glycosides Harnessing Biosynthetic Networks, Protein Engineering and One-Pot Multienzyme Cascades.

Phenylethanoid glycosides (PhGs) exhibit a multitude of structural variations linked to diverse pharmacological activities. Assembling various PhGs via multienzyme cascades represents a concise strategy over traditional synthetic methods. However, the challenge lies in identifying a comprehensive set of catalytic enzymes. This study explores biosynthetic PhG reconstruction from natural precursors, aiming to replicate and amplify their structural diversity. We discovered 12 catalytic enzymes, including four novel 6'-OH glycosyltransferases and three new polyphenol oxidases, revealing the intricate network in PhG biosynthesis. Subsequently, the crystal structure of CmGT3 (2.62 Å) was obtained, guiding the identification of conserved residue 144# as a critical determinant for sugar donor specificity. Engineering this residue in PhG glycosyltransferases (FsGT61, CmGT3, and FsGT6) altered their sugar donor recognition. Finally, a one-pot multienzyme cascade was established, where the combined action of glycosyltransferases and acyltransferases boosted conversion rates by up to 12.6-fold. This cascade facilitated the reconstruction of 26 PhGs with conversion rates ranging from 5-100 %, and 20 additional PhGs detectable by mass spectrometry. PhGs with extra glycosyl and hydroxyl modules demonstrated notable liver cell protection. This work not only provides catalytic tools for PhG biosynthesis, but also serves as a proof-of-concept for cell-free enzymatic construction of diverse natural products.

Editorial: Extremozymes: characteristics, structure, protein engineering and applications

Editorial: Extremozymes: characteristics, structure, protein engineering and applications

From Protein Structures to Functional Biomimetics

AbstractThe development of complex molecular scaffolds with defined folding properties represents a central challenge in chemical research. Proteins are natural scaffolds defined by a hierarchy of structural complexity and have evolved to manifest unique functional characteristics; for example, molecular recognition capabilities that facilitate the binding of target molecules with high affinity and selectivity. Utilizing these features, proteins have been used as a starting point for the design of synthetic foldamers and enhanced biocatalysts, as well as bioactive reagents in drug discovery. In this account, we describe the strategies used in our group to stabilize protein folds, ranging from the constraint of bioactive peptide conformations to chemical protein engineering. We discuss the evolution of peptides into peptidomimetics to inhibit protein–protein and protein–nucleic acid interactions, and the selective chemical modification of proteins to enhance their properties for biotechnological applications. The reported peptide- and proteomimetic structures cover a broad range of molecular sizes and they highlight the importance of structure stabilization for the design of functional biomimetics.1 Introduction2 Constraining the Conformation of Peptides3 Peptide-Based Covalent Protein Modifiers4 Chemical Protein Engineering5 Conclusions

Improving plastic degrading enzymes via directed evolution.

Plastic degrading enzymes have immense potential for use in industrial applications. Protein engineering efforts over the last decade have resulted in considerable enhancement of many properties of these enzymes. Directed evolution, a protein engineering approach that mimics the natural process of evolution in a laboratory, has been particularly useful in overcoming some of the challenges of structure-based protein engineering. For example, directed evolution has been used to improve the catalytic activity and thermostability of polyethylene terephthalate (PET)-degrading enzymes, although its use for the improvement of other desirable properties, such as solvent tolerance, has been less studied. In this review, we aim to identify some of the knowledge gaps and current challenges, and highlight recent studies related to the directed evolution of plastic-degrading enzymes.

Biocatalytic Regio‐ and Enantiocomplementary Synthesis of Chiral Aryloxazolidinones

AbstractWe described the protein engineering of the halohydrin dehalogenase HheG to enhance its R enantioselectivity for the synthesis of chiral 4‐aryloxazolidinones via α‐regioselective ring‐opening of aryl epoxides with cyanate. Additionally, we achieved the inversion of its regioselectivity and enantioselectivity, resulting in a HheG variant tailored for the synthesis of chiral 5‐aryloxazolidinones via β‐regioselective and S‐enantioselective ring‐opening of aryl epoxides with cyanate. Leveraging these engineered mutants, we developed a biocatalytic platform capable of synthesis of both chiral 4‐aryloxazolidinones (up to 47% yield, 98% ee, and 99% regioselectivity) and chiral 5‐aryloxazolidinones (up to 46% yield, &gt;99% ee, and 98% regioselectivity). Furthermore, a collaborative approach utilizing two regio‐ and enantioselective HheG mutants has been demonstrated to enable the simultaneous synthesis of chiral 4‐aryloxazolidinones and chiral 5‐aryloxazolidinones.

Structural Analysis of Xylose Isomerase from Streptomyces avermitilis

Xylose isomerase (XI, also known as glucose isomerase) is an oxidoreductase that interconverts aldoses and ketoses. XI catalyzes the reversible isomerization of D-glucose and D-xylose into D-fructose and D-xylulose, respectively. The molecular function of XI is widely applied in producing high-fructose corn syrup (HFCS) in the food industry and bioethanol from hemicellulose in the biofuel industry. The structural information of XI from diverse strains is important for understanding molecular properties that can provide insights into protein engineering to improve enzyme efficiency. To extend the knowledge of the structural information on XI, the crystal structure of XI from Streptomyces avermitilis (SavXI) was determined at a 2.81 Å resolution. SavXI containing TIM barrel and extended α-helix domains formed the tetrameric assembly. The two metal-binding sites and their coordinating residues showed diverse conformations, providing the structural flexibility of the active site of SavXI. The structural comparison of SavXI and XI homologs exhibited unique metal-binding sites and conformations of the C-terminal α-helix domain. These structural results extend our knowledge of the molecular flexibility and mechanism of the XI family.

A systematic analysis of regression models for protein engineering.

To optimize proteins for particular traits holds great promise for industrial and pharmaceutical purposes. Machine Learning is increasingly applied in this field to predict properties of proteins, thereby guiding the experimental optimization process. A natural question is: How much progress are we making with such predictions, and how important is the choice of regressor and representation? In this paper, we demonstrate that different assessment criteria for regressor performance can lead to dramatically different conclusions, depending on the choice of metric, and how one defines generalization. We highlight the fundamental issues of sample bias in typical regression scenarios and how this can lead to misleading conclusions about regressor performance. Finally, we make the case for the importance of calibrated uncertainty in this domain.

In silico energetic and molecular dynamic simulations studies demonstrate potential effect of the point mutations with implications for protein engineering in BDNF

Protein engineering by directed evolution is time-consuming. Hence, in silico techniques like FoldX-Yasara for ∆∆G calculation, and SNPeffect for predicting propensity for aggregation, amyloid formation, and chaperone binding are employed to design proteins. Here, we used in silico techniques to engineer BDNF-NTF3 interaction and validated it using mutations with known functional implications for NGF dimer. The structures of three mutants representing a positive, negative, or neutral ∆∆G involving two interface residues in BDNF and two mutations representing a neutral and positive ∆∆G in NGF, which is aligned with BDNF, were selected for molecular dynamics (MD) simulation. Our MD results conclude that the secondary structure of individual protomers of the positive and negative mutants displayed a similar or different conformation from the NTF3 monomer, respectively. The positive mutants showed fewer hydrophobic interactions and higher hydrogen bonds compared to the wild-type, negative, and neutral mutants with similar SASA, suggesting solvent-mediated disruption of hydrogen-bonded interactions. Similar results were obtained for mutations with known functional implications for NGF and BDNF. The results suggest that mutations with known effects in homologous proteins could help in validation, and in silico directed evolution experiments could be a viable alternative to the experimental technique used for protein engineering.

Novel protein ligase based on dual split intein

Inteins are unique single-turnover enzymes that can excise themselves from the precursor protein without the aid of any external cofactors or energy. In most cases, inteins are covalently linked with the extein sequences and protein splicing happens spontaneously. In this study, a novel protein ligation system was developed based on two atypical split inteins without cross reaction, in which the large segments of one S1 and one S11 split intein fusion protein acted as a protein ligase, the small segments (only several amino acids long) was fused to the N-extein and C-extein, respectively. The splicing activity was demonstrated in E. coli and in vitro with different extein sequences, which showed ∼15% splicing efficiency in vitro. The protein trans-splicing in vitro was further optimized, and possible reaction explanations were explored. As a proof of concept, we expect this approach to expand the scope of trans-splicing-based protein engineering and provide new clues for intein based protein ligase.

Protein Grafting Techniques: From Peptide Epitopes to Lasso-Grafted Neobiologics.

Protein engineering techniques have vastly expanded their domain of impact, notably following the success of antibodies. Likewise, smaller peptide therapeutics have carved an increasingly significant niche for themselves in the pharmaceutical landscape. The concept of grafting such peptide onto larger protein scaffolds, thus harvesting the advantages of both, has given rise to a variety of protein engineering strategies that are reviewed herein. We also describe our own "Lasso-Grafting" approach, which combines traditional grafting concepts with mRNA display to streamline the production of multiple grafted drug candidates for virtually any target.