Making the cut with protease engineering

Carbohydrate-active enzyme (CAZyme) discovery and engineering via (Ultra)high-throughput screening

Carbohydrate-active enzymes (CAZymes) constitute a diverse set of enzymes that catalyze the assembly, degradation, and modification of carbohydrates. These enzymes have been fashioned into potent, selective catalysts by millennia of evolution, and yet are also highly adaptable and readily evolved in the laboratory. To identify and engineer CAZymes for different purposes, (ultra)high-throughput screening campaigns have been frequently utilized with great success. This review provides an overview of the different approaches taken in screening for CAZymes and how mechanistic understandings of CAZymes can enable new approaches to screening. Within, we also cover how cutting-edge techniques such as microfluidics, advances in computational approaches and synthetic biology, as well as novel assay designs are leading the field towards more informative and effective screening approaches.

The multifaceted role of proteases and modern analytical methods for investigation of their catalytic activity

We discuss the diverse functions of proteases in the context of their biotechnological and medical significance, as well as analytical approaches used to determine the functional activity of these enzymes. An insight into modern approaches to studying the kinetics and specificity of proteases, based on spectral (absorption, fluorescence), mass spectrometric, immunological, calorimetric, and electrochemical methods of analysis is given. We also examine in detail electrochemical systems for determining the activity and specificity of proteases. Particular attention is given to exploring innovative electrochemical systems based on the detection of the electrochemical oxidation signal of amino acid residues, thereby eliminating the need for extra redox labels in the process of peptide synthesis. In the review, we highlight the main prospects for the further development of electrochemical systems for the study of biotechnologically and medically significant proteases, which will enable the miniaturization of the analytical process for determining the catalytic activity of these enzymes.

Perspective on Agricultural Industrialization: Modification Strategies for Enhancing the Catalytic Capacity of Keratinase

Keratinases is a special hydrolytic enzyme produced by microorganisms, which has the ability to catalyze the degradation of keratin. Currently, keratinases show great potential for application in many agricultural and industrial fields, such as biofermented feed, leather tanning, hair removal, and fertilizer production. However, these potentials have not yet been fully unleashed on an industrial scale. This paper reviews the sources, properties, and catalytic mechanisms of keratinases. Strategies for the molecular modification of keratinases are summarized and discussed in terms of improving the substrate specificity, thermostability, and pH tolerance of keratinases. The modification strategies are also enriched by the introduction of immobilized enzymes and directed evolution. In addition, the selection of modification strategies when facing specific industrial applications is discussed and prospects are provided. We believe that this review serves as a reference for the future quest to extend the application of keratinases from the laboratory to industry.

Advances in the understanding and exploitation of carbohydrate-active enzymes

Carbohydrate-active enzymes (CAZymes) are responsible for the biosynthesis, modification and degradation of all glycans in Nature. Advances in genomic and metagenomic methodologies, in conjunction with lower cost gene synthesis, have provided access to a steady stream of new CAZymes with both well-established and novel mechanisms. At the same time, increasing access to cryo-EM has resulted in exciting new structures, particularly of transmembrane glycosyltransferases of various sorts. This improved understanding has resulted in widespread progress in applications of CAZymes across diverse fields, including therapeutics, organ transplantation, foods, and biofuels. Herein, we highlight a few of the many important advances that have recently been made in the understanding and applications of CAZymes.

Leveraging yeast sequestration to study and engineer posttranslational modification enzymes

Enzymes that catalyze posttranslational modifications (PTMs) of peptides and proteins (PTM-enzymes)-proteases, protein ligases, oxidoreductases, kinases, and other transferases-are foundational to our understanding of health and disease and empower applications in chemical biology, synthetic biology, and biomedicine. To fully harness the potential of PTM-enzymes, there is a critical need to decipher their enzymatic and biological mechanisms, develop molecules that can probe and modulate them, and endow them with improved and novel functions. These objectives are contingent upon implementation of high-throughput functional screens and selections that interrogate large sequence libraries to isolate desired PTM-enzyme properties. This review discusses the principles of Saccharomyces cerevisiae organelle sequestration to study and engineer PTM-enzymes. These include outer membrane sequestration, specifically methods that modify yeast surface display, and cytoplasmic sequestration based on enzyme-mediated transcription activation. Furthermore, we present a detailed discussion of yeast endoplasmic reticulum sequestration for the first time. Where appropriate, we highlight the major features and limitations of different systems, specifically how they can measure and control enzyme catalytic efficiencies. Taken together, yeast-based high-throughput sequestration approaches significantly lower the barrier to understanding how PTM-enzymes function and how to reprogram them.

Modular and integrative activity reporters enhance biochemical studies in the yeast ER

The yeast endoplasmic reticulum sequestration and screening (YESS) system is a broadly applicable platform to perform high-throughput biochemical studies of post-translational modification enzymes (PTM-enzymes). This system enables researchers to profile and engineer the activity and substrate specificity of PTM-enzymes and to discover inhibitor-resistant enzyme mutants. In this study, we expand the capabilities of YESS by transferring its functional components to integrative plasmids. The YESS integrative system yields uniform protein expression and protease activities in various configurations, allows one to integrate activity reporters at two independent loci and to split the system between integrative and centromeric plasmids. We characterize these integrative reporters with two viral proteases, Tobacco etch virus (TEVp) and 3-chymotrypsin like protease (3CLpro), in terms of coefficient of variance, signal-to-noise ratio and fold-activation. Overall, we provide a framework for chromosomal-based studies that is modular, enabling rigorous high-throughput assays of PTM-enzymes in yeast.

A high-throughput screening platform for enzymes active on mucin-type O-glycoproteins

Mucin-type O-glycosylation is a post-translational modification present at the interface between cells where it has important roles in cellular communication. However, deciphering the function of O-glycoproteins and O-glycans can be challenging, especially as few enzymes are available for their assembly or selective degradation. Here, to address this deficiency, we developed a genetically encoded screening methodology for the discovery and engineering of the diverse classes of enzymes that act on O-glycoproteins. The method uses Escherichia coli that have been engineered to produce an O-glycosylated fluorescence resonance energy transfer probe that can be used to screen for O-glycopeptidase activity. Subsequent cleavage of the substrate by O-glycopeptidases provides a read-out of the glycosylation state of the probe, allowing the method to also be used to assay glycosidases and glycosyltransferases. We further show the potential of this methodology in the first ultrahigh-throughput-directed evolution of an O-glycopeptidase.

Prediction and design of protease enzyme specificity using a structure-aware graph convolutional network

Site-specific proteolysis by the enzymatic cleavage of small linear sequence motifs is a key posttranslational modification involved in physiology and disease. The ability to robustly and rapidly predict protease-substrate specificity would also enable targeted proteolytic cleavage by designed proteases. Current methods for predicting protease specificity are limited to sequence pattern recognition in experimentally derived cleavage data obtained for libraries of potential substrates and generated separately for each protease variant. We reasoned that a more semantically rich and robust model of protease specificity could be developed by incorporating the energetics of molecular interactions between protease and substrates into machine learning workflows. We present Protein Graph Convolutional Network (PGCN), which develops a physically grounded, structure-based molecular interaction graph representation that describes molecular topology and interaction energetics to predict enzyme specificity. We show that PGCN accurately predicts the specificity landscapes of several variants of two model proteases. Node and edge ablation tests identified key graph elements for specificity prediction, some of which are consistent with known biochemical constraints for protease:substrate recognition. We used a pretrained PGCN model to guide the design of protease libraries for cleaving two noncanonical substrates, and found good agreement with experimental cleavage results. Importantly, the model can accurately assess designs featuring diversity at positions not present in the training data. The described methodology should enable the structure-based prediction of specificity landscapes of a wide variety of proteases and the construction of tailor-made protease editors for site-selectively and irreversibly modifying chosen target proteins.

Short Peptides for Hydrolase Supramolecular Mimicry and Their Potential Applications

Hydrolases are enzymes that have found numerous applications in various industrial sectors spanning from pharmaceuticals to foodstuff and beverages, consumers' products such as detergents and personal care, textiles, and even for biodiesel production and environmental bioremediation. Self-assembling and gelling short peptides have been designed for their mimicry so that their supramolecular organization leads to the creation of hydrophobic pockets for catalysis to occur. Catalytic gels of this kind can also find numerous industrial applications to address important global challenges of our time. This concise review focuses on the last 5 years of progress in this fast-paced, popular field of research with an eye towards the future.

Modular and integrative activity reporters enhance biochemical studies in the yeast ER

The yeast endoplasmic reticulum sequestration and screening (YESS) system is a generalizable platform that has become highly useful to investigate post-translational modification enzymes (PTM-enzymes). This system enables researchers to profile and engineer the activity and substrate specificity of PTM-enzymes and to discover inhibitor-resistant enzyme mutants. In this study, we expand the capabilities of YESS by transferring its functional components to integrative plasmids. The YESS integrative system yields uniform protein expression and protease activities in various configurations, allows one to integrate activity reporters at two independent loci and to split the system between integrative and centromeric plasmids. We characterize these integrative reporters with two viral proteases, Tobacco etch virus (TEVp) and 3-chymotrypsin like protease (3CL pro ), in terms of coefficient of variance, signal-to-noise ratio and fold-activation. Overall, we provide a framework for chromosomal-based studies that is modular, enabling rigorous high-throughput assays of PTM-enzymes in yeast.

Prediction and Design of Protease Enzyme Specificity Using a Structure-Aware Graph Convolutional Network

Site-specific proteolysis by the enzymatic cleavage of small linear sequence motifs is a key post-translational modification involved in physiology and disease. The ability to robustly and rapidly predict protease substrate specificity would also enable targeted proteolytic cleavage - editing - of a target protein by designed proteases. Current methods for predicting protease specificity are limited to sequence pattern recognition in experimentally-derived cleavage data obtained for libraries of potential substrates and generated separately for each protease variant. We reasoned that a more semantically rich and robust model of protease specificity could be developed by incorporating the three-dimensional structure and energetics of molecular interactions between protease and substrates into machine learning workflows. We present Protein Graph Convolutional Network (PGCN), which develops a physically-grounded, structure-based molecular interaction graph representation that describes molecular topology and interaction energetics to predict enzyme specificity. We show that PGCN accurately predicts the specificity landscapes of several variants of two model proteases: the NS3/4 protease from the Hepatitis C virus (HCV) and the Tobacco Etch Virus (TEV) proteases. Node and edge ablation tests identified key graph elements for specificity prediction, some of which are consistent with known biochemical constraints for protease:substrate recognition. We used a pre-trained PGCN model to guide the design of TEV protease libraries for cleaving two non-canonical substrates, and found good agreement with experimental cleavage results. Importantly, the model can accurately assess designs featuring diversity at positions not present in the training data. The described methodology should enable the structure-based prediction of specificity landscapes of a wide variety of proteases and the construction of tailor-made protease editors for site-selectively and irreversibly modifying chosen target proteins.

Evolution of protease activation and specificity via alpha-2-macroglobulin-mediated covalent capture

Tailoring of the activity and specificity of proteases is critical for their utility across industrial, medical and research purposes. However, engineering or evolving protease catalysts is challenging and often labour intensive. Here, we describe a generic method to accelerate this process based on yeast display. We introduce the protease selection system A2M^cap that covalently captures protease catalysts by repurposed alpha-2-macroglobulin (A2Ms). To demonstrate the utility of A2M^cap for protease engineering we exemplify the directed activity and specificity evolution of six serine proteases. This resulted in a variant of Staphylococcus aureus serin-protease-like (Spl) protease SplB, an enzyme used for recombinant protein processing, that no longer requires activation by N-terminal signal peptide removal. SCHEMA-based domain shuffling was used to map the specificity determining regions of Spl proteases, leading to a chimeric scaffold that supports specificity switching via subdomain exchange. The ability of A2M^cap to overcome key challenges en route to tailor-made proteases suggests easier access to such reagents in the future.

Improving the catalytic activity of a detergent-compatible serine protease by rational design

Serine proteases are among the most important biological additives in various industries such as detergents, leather, animal feed and food. A serine protease gene, Fgapt4, from Fusarium graminearum 2697 was identified, cloned and expressed in Pichia pastoris. The optimal pH and temperature of FgAPT4 were 8.5 and 40°C, respectively. The relative activity was >30% even at 10°C. It had a wide range of pH stability (4.0-12.0) and detergent compatibility. To improve the catalytic activity, a strategy combining molecular docking and evolutionary analysis was adopted. Twelve amino acid residue sites and three loops (A, B and C) were selected as potential hot spots that might play critical roles in the enzyme's functional properties. Twenty-eight mutants targeting changes in individual sites or loops were designed, and mutations with good performance were combined. The best mutant was FgAPT4-M3 (Q70N/D142S/A143S/loop C). The specific activity and catalytic efficiency of FgAPT4-M3 increased by 1.6 (1008.5 vs. 385.9 U/mg) and 2.2-fold (3565.1 vs. 1106.3/s/mM), respectively. Computational analyses showed that the greater flexibility of the substrate pocket may be responsible for the increased catalytic activity. In addition, its application in detergents indicated that FgAPT4-M3 has great potential in washing.

Design and Characterization of In-One Protease-Esterase PluriZyme

Proteases are abundant in prokaryotic genomes (~10 per genome), but their recovery encounters expression problems, as only 1% can be produced at high levels; this value differs from that of similarly abundant esterases (1-15 per genome), 50% of which can be expressed at good levels. Here, we design a catalytically efficient artificial protease that can be easily produced. The PluriZyme EH1AB1 with two active sites supporting the esterase activity was employed. A Leu24Cys mutation in EH1AB1, remodelled one of the esterase sites into a proteolytic one through the incorporation of a catalytic dyad (Cys24 and His214). The resulting artificial enzyme, EH1AB1C, efficiently hydrolysed (azo)casein at pH 6.5-8.0 and 60-70 °C. The presence of both esterase and protease activities in the same scaffold allowed the one-pot cascade synthesis (55.0 ± 0.6% conversion, 24 h) of L-histidine methyl ester from the dipeptide L-carnosine in the presence of methanol. This study demonstrates that active sites supporting proteolytic activity can be artificially introduced into an esterase scaffold to design easy-to-produce in-one protease-esterase PluriZymes for cascade reactions, namely, the synthesis of amino acid esters from dipeptides. It is also possible to design artificial proteases with good production yields, in contrast to natural proteases that are difficult to express.