Substrate phage: selection of protease substrates by monovalent phage display

Non-prime- and prime-side profiling of Pro-Pro endopeptidase specificity using synthetic combinatorial peptide libraries and mass spectrometry

A group of bacterial proteases, the Pro-Pro endopeptidases (PPEPs), possess the unique ability to hydrolyze proline-proline bonds in proteins. Since a protease's function is largely determined by its substrate specificity, methods that can extensively characterize substrate specificity are valuable tools for protease research. Previously, we achieved an in-depth characterization of PPEP prime-side specificity. However, PPEP specificity is also determined by the non-prime-side residues in the substrate. To gain a more complete insight into the determinants of PPEP specificity, we characterized the non-prime- and prime-side specificity of various PPEPs using a combination of synthetic combinatorial peptide libraries and mass spectrometry. With this approach, we deepened our understanding of the P3-P3' specificities of PPEP-1 and PPEP-2, while identifying the endogenous substrate of PPEP-2 as the most optimal substrate in our library data. Furthermore, by employing the library approach, we investigated the altered specificity of mutants of PPEP-1 and PPEP-2. Additionally, we characterized a novel PPEP from Anoxybacillus tepidamans, which we termed PPEP-4. Based on structural comparisons, we hypothesized that PPEP-4 displays a PPEP-1-like prime-side specificity, which was substantiated by the experimental data. Intriguingly, another putative PPEP from Clostridioides difficile, CD1597, did not display Pro-Pro endoproteolytic activity. Collectively, we characterized PPEP specificity in detail using our robust peptide library method and, together with additional structural information, provide more insight into the intricate mechanisms that govern protease specificity.

An N terminomics toolbox combining 2-pyridinecarboxaldehyde probes and click chemistry for profiling protease specificity

Proteomic profiling of protease-generated N termini provides key insights into protease function and specificity. However, current technologies have sequence limitations or require specialized synthetic reagents for N-terminal peptide isolation. Here, we introduce an N terminomics toolbox that combines selective N-terminal biotinylation using 2-pyridinecarboxaldehyde (2PCA) reagents with chemically cleavable linkers to enable efficient enrichment of protein N termini. By incorporating a commercially available alkyne-modified 2PCA in combination with Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC), our strategy eliminates the need for chemical synthesis of N-terminal probes. Using these reagents, we developed PICS2 (Proteomic Identification of Cleavage Sites with 2PCA) to profile the specificity of subtilisin/kexin-type proprotein convertases (PCSKs). We also implemented CHOPPER (chemical enrichment of protease substrates with purchasable, elutable reagents) for global sequencing of apoptotic proteolytic cleavage sites. Based on their broad applicability and ease of implementation, PICS2 and CHOPPER are useful tools that will advance our understanding of protease biology.

RBD-specific single-chain antibody protects against acute lung injury in mice

As SARS-CoV-2 variants continue spreading globally, the discovery of broad spectrum therapeutically active antibodies with retaining good protective activity is a global priority. It was reported that infection with SARS-CoV-2 could cause acute lung injury (ALI) in clinical investigations. Therefore, we discovered that anti-RBD scFv is effective against SARS-CoV-2-induced ALI. To begin, we utilized the receptor binding domain (RBD) of spike glycoprotein as a target to produce single-chain antibodies (scFvs) through an intensive phage display technology. The binding affinity and inhibitory effect of the scFvs were evaluated via ELISA and flow cytometry. Moreover, anti-RBD scFv No.35 significantly prevented ALI caused by LPS and SARS-CoV-2 spike RBD protein in mouse model. Thus, the anti-RBD scFv will aid the development of potential antibody treatments and reduce the inflammatory response of SARS-CoV-2.

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.

In-Depth Specificity Profiling of Endopeptidases Using Dedicated Mix-and-Split Synthetic Peptide Libraries and Mass Spectrometry

Proteases comprise the class of enzymes that catalyzes the hydrolysis of peptide bonds, thereby playing a pivotal role in many aspects of life. The amino acids surrounding the scissile bond determine the susceptibility toward protease-mediated hydrolysis. A detailed understanding of the cleavage specificity of a protease can lead to the identification of its endogenous substrates, while it is also essential for the design of inhibitors. Although many methods for protease activity and specificity profiling exist, none of these combine the advantages of combinatorial synthetic libraries, i.e., high diversity, equimolar concentration, custom design regarding peptide length, and randomization, with the sensitivity and detection power of mass spectrometry. Here, we developed such a method and applied it to study a group of bacterial metalloproteases that have the unique specificity to cleave between two prolines, i.e., Pro-Pro endopeptidases (PPEPs). We not only confirmed the prime-side specificity of PPEP-1 and PPEP-2, but also revealed some new unexpected peptide substrates. Moreover, we have characterized a new PPEP (PPEP-3) that has a prime-side specificity that is very different from that of the other two PPEPs. Importantly, the approach that we present in this study is generic and can be extended to investigate the specificity of other proteases.

Identification of SARS-CoV-2 PLpro and 3CLpro human proteome substrates using substrate phage display coupled with protein network analysis

Viral proteases play key roles in viral replication, and they also facilitate immune escape by proteolyzing diverse target proteins. Deep profiling of viral protease substrates in host cells is beneficial for understanding viral pathogenesis and for antiviral drug discovery. Here, we utilized substrate phage display coupled with protein network analysis (SPD-PNA) to identify human proteome substrates of SARS-CoV-2 viral proteases, including papain-like protease (PLpro) and 3C-like protease (3CLpro). We first performed peptide substrates selection of PLpro and 3CLpro, and we then used the top 24 preferred substrate sequences to identify a total of 290 putative protein substrates. Protein network analysis revealed that the top clusters of PLpro and 3CLpro substrate proteins contain ubiquitin-related proteins and cadherin-related proteins respectively. We verified that cadherin-6 (CDH6) and cadherin-12 (CDH12) are novel substrates of 3CLpro and CD177 is a novel substrate of PLpro using in vitro cleavage assays. We thus demonstrated SPD-PNA is a simple and high throughput method to identify human proteome substrates of SARS-CoV-2 viral proteases for further understanding of virus-host interactions.

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.

Multiplex substrate profiling by mass spectrometry for proteases

Proteolysis is a central regulator of many biological pathways and the study of proteases has had a significant impact on our understanding of both native biology and disease. Proteases are key regulators of infectious disease and misregulated proteolysis in humans contributes to a variety of maladies, including cardiovascular disease, neurodegeneration, inflammatory diseases, and cancer. Central to understanding a protease's biological role, is characterizing its substrate specificity. This chapter will facilitate the characterization of individual proteases and complex, heterogeneous proteolytic mixtures and provide examples of the breadth of applications that leverage the characterization of misregulated proteolysis. Here we present the protocol of Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS), a functional assay that quantitatively characterizes proteolysis using a synthetic library of physiochemically diverse, model peptide substrates, and mass spectrometry. We present a detailed protocol as well as examples of the use of MSP-MS for the study of disease states, for the development of diagnostic and prognostic tests, for the generation of tool compounds, and for the development of protease-targeted drugs.

Diagnostic and therapeutic potential of protease inhibition

Proteases are enzymes that hydrolyze peptide bonds in proteins and peptides; thus, they control virtually all biological processes. Our understanding of protease function has advanced considerably from nonselective digestive enzymes to highly specialized molecular scissors that orchestrate complex signaling networks through a limited proteolysis. The catalytic activity of proteases is tightly regulated at several levels, ranging from gene expression through trafficking and maturation to posttranslational modifications. However, when this delicate balance is disturbed, many diseases develop, including cancer, inflammatory disorders, diabetes, and neurodegenerative diseases. This new understanding of the role of proteases in pathologic physiology indicates that these enzymes represent excellent molecular targets for the development of therapeutic inhibitors, as well as for the design of chemical probes to visualize their redundant activity. Recently, numerous platform technologies have been developed to identify and optimize protease substrates and inhibitors, which were further used as lead structures for the development of chemical probes and therapeutic drugs. Due to this considerable success, the clinical potential of proteases in therapeutics and diagnostics is rapidly growing and is still not completely explored. Therefore, small molecules that can selectively target aberrant protease activity are emerging in diseases cells. In this review, we describe modern trends in the design of protease drugs as well as small molecule activity-based probes to visualize selected proteases in clinical settings.

Making the cut with protease engineering

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

Methods to Analyze the Redox Reactivity of Plant Proteins

Proteins can be covalently modified by a broad range of highly reactive chemicals and redox mechanisms. Reversible redox-mediated post-translational modifications of sensitive cysteine thiol groups in proteins impact protein characteristics such as interaction behavior and activity state. Evaluating the response of proteins to redox perturbation or reactive chemical species is critical for understanding the underlying mechanisms involved and their contribution to plant stress physiology. Here we provide a detailed workflow that includes procedures for (i) purification, processing, and analysis of protein samples with redox agents, (ii) determining redox-modulated monomer to oligomer transitions using size exclusion chromatography, and (iii) activity assays for monitoring the impact of redox agents on purified enzymes and in crude extracts from plants subjected to oxidative stress. We exemplified how to apply several of the methods discussed for analyzing redox-sensing metallopeptidases, such as thimet oligopeptidases. We anticipate that these protocols should find broad applications in monitoring biochemical properties of other classes of redox-sensitive plant proteins.

Urinary detection of lung cancer in mice via noninvasive pulmonary protease profiling

Lung cancer is the leading cause of cancer-related death, and patients most commonly present with incurable advanced-stage disease. U.S. national guidelines recommend screening for high-risk patients with low-dose computed tomography, but this approach has limitations including high false-positive rates. Activity-based nanosensors can detect dysregulated proteases in vivo and release a reporter to provide a urinary readout of disease activity. Here, we demonstrate the translational potential of activity-based nanosensors for lung cancer by coupling nanosensor multiplexing with intrapulmonary delivery and machine learning to detect localized disease in two immunocompetent genetically engineered mouse models. The design of our multiplexed panel of sensors was informed by comparative transcriptomic analysis of human and mouse lung adenocarcinoma datasets and in vitro cleavage assays with recombinant candidate proteases. Intrapulmonary administration of the nanosensors to a Kras- and Trp53-mutant lung adenocarcinoma mouse model confirmed the role of metalloproteases in lung cancer and enabled accurate detection of localized disease, with 100% specificity and 81% sensitivity. Furthermore, this approach generalized to an alternative autochthonous model of lung adenocarcinoma, where it detected cancer with 100% specificity and 95% sensitivity and was not confounded by lipopolysaccharide-driven lung inflammation. These results encourage the clinical development of activity-based nanosensors for the detection of lung cancer.

Covalent Small Molecule Immunomodulators Targeting the Protease Active Site

Cells of the immune system utilize multiple proteases to regulate cell functions and orchestrate innate and adaptive immune responses. Dysregulated protease activities are implicated in many immune-related disorders; thus, protease inhibitors have been actively investigated for pharmaceutical development. Although historically considered challenging with concerns about toxicity, compounds that covalently modify the protease active site represent an important class of agents, emerging not only as chemical probes but also as approved drugs. Here, we provide an overview of technologies useful for the study of proteases with the focus on recent advances in chemoproteomic methods and screening platforms. By highlighting covalent inhibitors that have been designed to target immunomodulatory proteases, we identify opportunities for the development of small molecule immunomodulators.

Identification of highly selective covalent inhibitors by phage display

Molecules that covalently bind macromolecular targets have found widespread applications as activity-based probes and as irreversibly binding drugs. However, the general reactivity of the electrophiles needed for covalent bond formation makes control of selectivity difficult. There is currently no rapid, unbiased screening method to identify new classes of covalent inhibitors from highly diverse pools of candidate molecules. Here we describe a phage display method to directly screen for ligands that bind to protein targets through covalent bond formation. This approach makes use of a reactive linker to form cyclic peptides on the phage surface while simultaneously introducing an electrophilic 'warhead' to covalently react with a nucleophile on the target. Using this approach, we identified cyclic peptides that irreversibly inhibited a cysteine protease and a serine hydrolase with nanomolar potency and exceptional specificity. This approach should enable rapid, unbiased screening to identify new classes of highly selective covalent inhibitors for diverse molecular targets.

Quantitative profiling of protease specificity

Proteases are an important class of enzymes, whose activity is central to many physiologic and pathologic processes. Detailed knowledge of protease specificity is key to understanding their function. Although many methods have been developed to profile specificities of proteases, few have the diversity and quantitative grasp necessary to fully define specificity of a protease, both in terms of substrate numbers and their catalytic efficiencies. We have developed a concept of “selectome”; the set of substrate amino acid sequences that uniquely represent the specificity of a protease. We applied it to two closely related members of the Matrixin family–MMP-2 and MMP-9 by using substrate phage display coupled with Next Generation Sequencing and information theory-based data analysis. We have also derived a quantitative measure of substrate specificity, which accounts for both the number of substrates and their relative catalytic efficiencies. Using these advances greatly facilitates elucidation of substrate selectivity between closely related members of a protease family. The study also provides insight into the degree to which the catalytic cleft defines substrate recognition, thus providing basis for overcoming two of the major challenges in the field of proteolysis: 1) development of highly selective activity probes for studying proteases with overlapping specificities, and 2) distinguishing targeted proteolysis from bystander proteolytic events.

Proteases and proteolysis are intimately involved in virtually all biological processes from embryonic development to programmed cell death and cellular protein recycling. As the only irreversible posttranslational modification, proteolysis represents a committed step in regulation of biological networks and pathways. Imbalance of proteolytic activity has catastrophic implications and is the basis of many genetic disorders as well as a multitude of pathological states of varying etiologies. To understand protease function, one must gain insight into the repertoires of substrates targeted by these enzymes. As many proteases recognize a wide variety of sequences in proteins, it is a challenge to establish if a particular cleavage represents a targeted or a bystander proteolytic event. In addition, since many proteases have overlapping specificities, especially among closely related members of the same gene families, it is a challenge to develop highly selective tools for studying or inhibition of these enzymes. In this work, we used two closely related proteases (MMP-2 and 9) as a model system for development of an information theory-based approach to quantification of substrate specificity and demonstrated its potential for distinguishing between the target and bystander proteolytic events as well as for uncovering selectivity between closely related proteases.

Expanding the Chemical Diversity of Genetically Encoded Libraries

The power of ribosomes has increasingly been harnessed for the synthesis and selection of molecular libraries. Technologies, such as phage display, yeast display, and mRNA display, effectively couple genotype to phenotype for the molecular evolution of high affinity epitopes for many therapeutic targets. Genetic code expansion is central to the success of these technologies, allowing researchers to surpass the intrinsic capabilities of the ribosome and access new, genetically encoded materials for these selections. Here, we review techniques for the chemical expansion of genetically encoded libraries, their abilities and limits, and opportunities for further development. Importantly, we also discuss methods and metrics used to assess the efficiency of modification and library diversity with these new techniques.

Platform to Discover Protease-Activated Antibiotics and Application to Siderophore-Antibiotic Conjugates

Here we present a platform for discovery of protease-activated prodrugs and apply it to antibiotics that target Gram-negative bacteria. Because cleavable linkers for prodrugs had not been developed for bacterial proteases, we used substrate phage to discover substrates for proteases found in the bacterial periplasm. Rather than focusing on a single protease, we used a periplasmic extract of E. coli to find sequences with the greatest susceptibility to the endogenous mixture of periplasmic proteases. Using a fluorescence assay, candidate sequences were evaluated to identify substrates that release native amine-containing payloads. We next designed conjugates consisting of (1) an N-terminal siderophore to facilitate uptake, (2) a protease-cleavable linker, and (3) an amine-containing antibiotic. Using this strategy, we converted daptomycin-which by itself is active only against Gram-positive bacteria-into an antibiotic capable of targeting Gram-negative Acinetobacter species. We similarly demonstrated siderophore-facilitated delivery of oxazolidinone and macrolide antibiotics into a number of Gram-negative species. These results illustrate this platform's utility for development of protease-activated prodrugs, including Trojan horse antibiotics.

Deep profiling of protease substrate specificity enabled by dual random and scanned human proteome substrate phage libraries

Proteolysis is a major posttranslational regulator of biology inside and outside of cells. Broad identification of optimal cleavage sites and natural substrates of proteases is critical for drug discovery and to understand protease biology. Here, we present a method that employs two genetically encoded substrate phage display libraries coupled with next generation sequencing (SPD-NGS) that allows up to 10,000-fold deeper sequence coverage of the typical six- to eight-residue protease cleavage sites compared to state-of-the-art synthetic peptide libraries or proteomics. We applied SPD-NGS to two classes of proteases, the intracellular caspases, and the ectodomains of the sheddases, ADAMs 10 and 17. The first library (Lib 10AA) allowed us to identify 10⁴ to 10⁵ unique cleavage sites over a 1,000-fold dynamic range of NGS counts and produced consensus and optimal cleavage motifs based position-specific scoring matrices. A second SPD-NGS library (Lib hP), which displayed virtually the entire human proteome tiled in contiguous 49 amino acid sequences with 25 amino acid overlaps, enabled us to identify candidate human proteome sequences. We identified up to 10⁴ natural linear cut sites, depending on the protease, and captured most of the examples previously identified by proteomics and predicted 10- to 100-fold more. Structural bioinformatics was used to facilitate the identification of candidate natural protein substrates. SPD-NGS is rapid, reproducible, simple to perform and analyze, inexpensive, and renewable, with unprecedented depth of coverage for substrate sequences, and is an important tool for protease biologists interested in protease specificity for specific assays and inhibitors and to facilitate identification of natural protein substrates.

Protease Activity Profiling via Programmable Phage Display of Comprehensive Proteome-Scale Peptide Libraries

Endopeptidases catalyze the internal cleavage of proteins, playing pivotal roles in protein turnover, substrate maturation, and the activation of signaling cascades. A broad range of biological functions in health and disease are controlled by proteases, yet assays to characterize their activities at a proteomic scale do not exist. To address this unmet need, we developed Sensing EndoPeptidase Activity via Release and recapture using flAnking Tag Epitopes (SEPARATE), which uses a monovalent phage display of the human proteome at a 90-aa peptide resolution. We demonstrate that SEPARATE is compatible with several human proteases from distinct catalytic classes, including caspase-1, ADAM17, and thrombin. Both well-characterized and newly identified substrates of these enzymes were detected in the assay. SEPARATE was used to discover a non-canonical caspase-1 substrate, the E3 ubiquitin ligase HUWE1, a key mediator of apoptotic cell death. SEPARATE enables efficient, unbiased assessment of endopeptidase activity by using a phage-displayed proteome. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.

Strategies for Tuning the Selectivity of Chemical Probes that Target Serine Hydrolases

Serine hydrolases comprise a large family of enzymes that have diverse roles in key cellular processes, such as lipid metabolism, cell signaling, and regulation of post-translation modifications of proteins. They are also therapeutic targets for multiple human pathologies, including viral infection, diabetes, hypertension, and Alzheimer disease; however, few have well-defined substrates and biological functions. Activity-based probes (ABPs) have been used as effective tools to both profile activity and screen for selective inhibitors of serine hydrolases. One broad-spectrum ABP containing a fluorophosphonate electrophile has been used extensively to advance our understanding of diverse serine hydrolases. Due to the success of this single reagent, several robust chemistries have been developed to further diversify and tune the selectivity of ABPs used to target serine hydrolases. In this review, we highlight approaches to identify selective serine hydrolase ABPs and suggest new synthetic methodologies that could be applied to further advance probe development.

Synthetic and biological approaches to map substrate specificities of proteases

Proteases are regulators of diverse biological pathways including protein catabolism, antigen processing and inflammation, as well as various disease conditions, such as malignant metastasis, viral infection and parasite invasion. The identification of substrates of a given protease is essential to understand its function and this information can also aid in the design of specific inhibitors and active site probes. However, the diversity of putative protein and peptide substrates makes connecting a protease to its downstream substrates technically difficult and time-consuming. To address this challenge in protease research, a range of methods have been developed to identify natural protein substrates as well as map the overall substrate specificity patterns of proteases. In this review, we highlight recent examples of both synthetic and biological methods that are being used to define the substrate specificity of protease so that new protease-specific tools and therapeutic agents can be developed.

Design and Characterization of a New pVII Combinatorial Phage Display Peptide Library for Protease Substrate Mining Using Factor VII Activating Protease (FSAP) as Model

We describe a novel, easy and efficient combinatorial phage display peptide substrate-mining method to map the substrate specificity of proteases. The peptide library is displayed on the pVII capsid of the M13 bacteriophage, which renders pIII necessary for infectivity and efficient retrieval, in an unmodified state. As capture module, the 3XFLAG was chosen due to its very high binding efficiency to anti-FLAG mAbs and its independency of any post-translational modification. This library was tested with Factor-VII activating protease (WT-FSAP) and its single-nucleotide polymorphism variant Marburg-I (MI)-FSAP. The WT-FSAP results confirmed the previously reported Arg/Lys centered FSAP cleavage site consensus as dominant, as well as reinforcing MI-FSAP as a loss-of-function mutant. Surprisingly, rare substrate clones devoid of basic amino acids were also identified. Indeed one of these peptides was cleaved as free peptide, thus suggesting a broader range of WT-FSAP substrates than previously anticipated.

Protease-activated prodrugs: strategies, challenges, and future directions

Proteases play critical roles in virtually all biological processes, including proliferation, cell death and survival, protein turnover, and migration. However, when dysregulated, these enzymes contribute to the progression of multiple diseases, with cancer, neurodegenerative disorders, inflammation, and blood disorders being the most prominent examples. For a long time, disease-associated proteases have been used for the activation of various prodrugs due to their well-characterized catalytic activity and ability to selectively cleave only those substrates that strictly correspond with their active site architecture. To date, versatile peptide sequences that are cleaved by proteases in a site-specific manner have been utilized as bioactive linkers for the targeted delivery of multiple types of cargo, including fluorescent dyes, photosensitizers, cytotoxic drugs, antibiotics, and pro-antibodies. This platform is highly adaptive, as multiple protease-labile conjugates have already been developed, some of which are currently in clinical use for cancer treatment. In this review, recent advancements in the development of novel protease-cleavable linkers for selective drug delivery are described. Moreover, the current limitations regarding the selectivity of linkers are discussed, and the future perspectives that rely on the application of unnatural amino acids for the development of highly selective peptide linkers are also presented.

Exploring the Post-translational Enzymology of PaaA by mRNA Display

PaaA is a RiPP enzyme that catalyzes the transformation of two glutamic acid residues within a substrate peptide into the bicyclic core of Pantocin A. Here, for the first time, we use mRNA display techniques to understand RiPP enzyme-substrate interactions to illuminate PaaA substrate recognition. Additionally, our data revealed insights into the enzymatic timing of glutamic acid modification. The technique developed is quite sensitive and a significant advancement over current RiPP studies and opens the door to enzyme modified mRNA display libraries for natural product-like inhibitor pans.

SNAC-tag for sequence-specific chemical protein cleavage

Biocompatible chemical protein cleavage methods have been long-sought to replace enzymatic cleavages, but have yet to be realized. Here, we report the development of the SNAC-tag (Sequence-specific Nickel Assisted Cleavage) to achieve sequence-specific chemical protein cleavage under biocompatible conditions with comparable efficiency to enzymes. We demonstrate that the SNAC-tag can be inserted before both water-soluble and membrane proteins to achieve fusion protein cleavage, even when enzymatic cleavages fail.

Pep-MS assay: Protease hydrolysis assay system using photo-cleavable peptide array and mass spectrometer

Food processing technology such as protein hydrolysis using proteases has been receiving a lot of attention, and it is important to accurately understand the cleavage specificity of each protease for selecting a protease suited to aims. Although numerous methods have been reported to reveal the substrate specificity of proteases, there is no method to evaluate simply, quickly, reasonably, and accurately. This study set out to devise Pep-MS assay, a novel assay system that can be used to comprehensively clarify positions at which proteases cleave, by combining a mass spectrometer and a photo-cleavable peptide array. First, we evaluated peptide array corresponding to the primary sequences of α_S1-casein, α_S2-casein and β-casein with trypsin to verify the accuracy of the Pep-MS assay. The evaluation of cleavage positions by the trypsin protease reagent using the Pep-MS assay resulted in a matching rate of about 96.8% to rational cleavage positions. Next, we confirmed the cleavage positions in α_S2-casein or β-lactoglobulin by an industrial bacterial protease from Bacillus subtilis at some protease reaction temperatures or reaction times. The Pep-MS assay clarified the differences in the cleavage patterns due to the reaction temperature, and the change in the cleavage strength with the reaction time. Pep-MS assay is a promising method for evaluating the substrate specificity of proteases, which will be useful to find effective production conditions for functional peptide from foods and effective hydrolysis conditions for decreasing allergen of food proteins.

Directed evolution of the 3C protease from coxsackievirus using a novel fluorescence-assisted intracellular method

Proteases are crucial for regulating biological processes in organisms through hydrolysis of peptide bonds. Recombinant proteases have moreover become important tools in biotechnological, and biomedical research and as therapeutics. We have developed a label-free high-throughput method for quantitative assessment of proteolytic activity in Escherichia coli. The screening method is based on co-expression of a protease of interest and a reporter complex. This reporter consists of an aggregation-prone peptide fused to a fluorescent protein via a linker that contains the corresponding substrate sequence. Cleavage of the substrate rescues the fluorescent protein from aggregation, resulting in increased fluorescence that correlates to proteolytic activity, which can be monitored using flow cytometry. In one round of flow-cytometric cell sorting, we isolated an efficiently cleaved tobacco etch virus (TEV) substrate from a 1:100 000 background of non-cleavable sequences, with around 6000-fold enrichment. We then engineered the 3C protease from coxsackievirus B3 (CVB3 3Cpro) towards improved proteolytic activity on the substrate LEVLFQ↓GP. We isolated highly proteolytic active variants from a randomly mutated CVB3 3Cpro library with up to 4-fold increase in activity. The method enables simultaneous measurement of proteolytic activity and protease expression levels and can therefore be applied for protease substrate profiling, as well as directed evolution of proteases.

Quantitative Multiplex Substrate Profiling of Peptidases by Mass Spectrometry

Proteolysis is an integral component of life and has been implicated in many disease processes. To improve our understanding of peptidase function, it is imperative to develop tools to uncover substrate specificity and cleavage efficiency. Here, we combine the quantitative power of tandem mass tags (TMTs) with an established peptide cleavage assay to yield quantitative Multiplex Substrate Profiling by Mass Spectrometry (qMSP-MS). This assay was validated with papain, a well-characterized cysteine peptidase, to generate cleavage efficiency values for hydrolysis of 275 unique peptide bonds in parallel. To demonstrate the breath of this assay, we show that qMSP-MS can uncover the substrate specificity of minimally characterized intramembrane rhomboid peptidases, as well as define hundreds of proteolytic activities in complex biological samples, including secretions from lung cancer cell lines. Importantly, our qMSP-MS library uses synthetic peptides whose termini are unmodified, allowing us to characterize not only endo- but also exo-peptidase activity. Each cleaved peptide sequence can be ranked by turnover rate, and the amino acid sequence of the best substrates can be used for designing fluorescent reporter substrates. Discovery of peptide substrates that are selectively cleaved by peptidases which are active at the site of disease highlights the potential for qMSP-MS to guide the development of peptidase-activating drugs for cancer and infectious disease.

Protease Specificity: Towards In Vivo Imaging Applications and Biomarker Discovery

Proteases are considered of major importance in biomedical research because of their crucial roles in health and disease. Their ability to hydrolyze their protein and peptide substrates at single or multiple sites, depending on their specificity, makes them unique among the enzymes. Understanding protease specificity is therefore crucial to understand their biology as well as to develop tools and drugs. Recent advancements in the fields of proteomics and chemical biology have improved our understanding of protease biology through extensive specificity profiling and identification of physiological protease substrates. There are growing efforts to transfer this knowledge into clinical modalities, but their success is often limited because of overlapping protease features, protease redundancy, and chemical tools lacking specificity. Herein, we discuss the current trends and challenges in protease research and how to exploit the growing information on protease specificities for understanding protease biology, as well as for development of selective substrates, cleavable linkers, and activity-based probes and for biomarker discovery.

Recent Advances in Activity-Based Protein Profiling of Proteases

The activity of proteases is tightly regulated, and dysregulation is linked to a variety of human diseases. For this reason, ABPP is a well-suited method to study protease biology and the design of protease probes has pushed the boundaries of ABPP. The development of highly selective protease probes is still a challenging task. After an introduction, the first section of this chapter discusses several strategies to enable detection of a single active protease species. These range from the usage of non-natural amino acids, combination of probes with antibodies, and engineering of the target proteases. A next section describes the different types of detection tags that facilitate the read-out possibilities including various types of imaging methods and mass spectrometry-based target identification. The power of protease ABPP is illustrated by examples for a selected number of proteases. It is expected that some protease probes that have been evaluated in animal models of human disease will find translation into clinical application in the near future.

Serpin Phage Display: The Use of a T7 System to Probe Reactive Center Loop Libraries with Different Serine Proteinases

Phage display is a protein engineering approach that involves construction of libraries of variant proteins displayed on the surface of bacteriophage as capsid fusion proteins and their screening for binding and inhibitory function through the use of bait proteins. Recently, we adapted a commercially available T7 phage display system to create phage-displayed serpin libraries hypervariable in up to five positions in their reactive center loop (RCL). The RCL is a key determinant in serpin specificity, the relationship between the structure of a given serpin and which target proteinase(s) it inhibits. In this chapter, we describe protocols to assess the feasibility of this method for different serpin/proteinase combinations and share experience with this technology gathered in the course of studying two serpins and multiple proteinases with this powerful iterative screening approach.

Phage-assisted continuous evolution of proteases with altered substrate specificity

Here we perform phage-assisted continuous evolution (PACE) of TEV protease, which canonically cleaves ENLYFQS, to cleave a very different target sequence, HPLVGHM, that is present in human IL-23. A protease emerging from ∼2500 generations of PACE contains 20 non-silent mutations, cleaves human IL-23 at the target peptide bond, and when pre-mixed with IL-23 in primary cultures of murine splenocytes inhibits IL-23-mediated immune signaling. We characterize the substrate specificity of this evolved enzyme, revealing shifted and broadened specificity changes at the six positions in which the target amino acid sequence differed. Mutational dissection and additional protease specificity profiling reveal the molecular basis of some of these changes. This work establishes the capability of changing the substrate specificity of a protease at many positions in a practical time scale and provides a foundation for the development of custom proteases that catalytically alter or destroy target proteins for biotechnological and therapeutic applications.Proteases are promising therapeutics to treat diseases such as hemophilia which are due to endogenous protease deficiency. Here the authors use phage-assisted continuous evolution to evolve a variant TEV protease with altered target peptide sequence specificities.

Synthesis of a HyCoSuL peptide substrate library to dissect protease substrate specificity

Many biologically and chemically based approaches have been developed to design highly active and selective protease substrates and probes. It is, however, difficult to find substrate sequences that are truly selective for any given protease, as different proteases can demonstrate a great deal of overlap in substrate specificities. In some cases, better enzyme selectivity can be achieved using peptide libraries containing unnatural amino acids such as the hybrid combinatorial substrate library (HyCoSuL), which uses both natural and unnatural amino acids. HyCoSuL is a combinatorial library of tetrapeptides containing amino acid mixtures at the P4-P2 positions, a fixed amino acid at the P1 position, and an ACC (7-amino-4-carbamoylmethylcoumarin) fluorescent tag occupying the P1' position. Once the peptide is recognized and cleaved by a protease, the ACC is released and produces a readable fluorescence signal. Here, we describe the synthesis and screening of HyCoSuL for human caspases and legumain. We also discuss possible modifications and adaptations of this approach that make it a useful tool for developing highly active and selective reagents for a wide variety of proteolytic enzymes. The protocol can be divided into three major parts: (i) solid-phase synthesis of the fluorescence-labeled HyCoSuL, (ii) screening of protease P4-P2 preferences, and (iii) synthesis of the optimized activity probes equipped with an AOMK (acyloxymethyl ketone) reactive group and a biotin label for easy detection. Beginning with the library design, the entire protocol can be completed in 4-8 weeks (HyCoSuL synthesis: 3-5 weeks; HyCoSuL screening per enzyme: 4-8 d; and activity-based probe synthesis: 1-2 weeks).

[Peptide phage display in biotechnology and biomedicine]

To date peptide phage display is one of the most common combinatorial methods used for identifying specific peptide ligands. Phage display peptide libraries containing billions different clones successfully used for selection of ligands with high affinity and selectivity toward wide range of targets including individual proteins, bacteria, viruses, spores, different kind of cancer cells and variety of nonorganic targets (metals, alloys, semiconductors etc.) Success of using filamentous phage in phage display technologies relays on the robustness of phage particles and a possibility to genetically modify its DNA to construct new phage variants with novel properties. In this review we are discussing characteristics of the most known non-commercial peptide phage display libraries of different formats (landscape libraries in particular) and their successful applications in several fields of biotechnology and biomedicine: discovery of peptides with diagnostic values against different pathogens, discovery and using of peptides recognizing cancer cells, trends in using of phage display technologies in human interactome studies, application of phage display technologies in construction of novel nano materials.

Emerging challenges in the design of selective substrates, inhibitors and activity-based probes for indistinguishable proteases

Proteases are enzymes that hydrolyze the peptide bond of peptide substrates and proteins. Despite significant progress in recent years, one of the greatest challenges in the design and testing of substrates, inhibitors and activity‐based probes for proteolytic enzymes is achieving specificity toward only one enzyme. This specificity is particularly important if the enzyme is present with other enzymes with a similar catalytic mechanism and substrate specificity but completely different functionality. The cross‐reactivity of substrates, inhibitors and activity‐based probes with other enzymes can significantly impair or even prevent investigations of a target protease. In this review, we describe important concepts and the latest challenges, focusing mainly on peptide‐based substrate specificity techniques used to distinguish individual enzymes within major protease families.

Determinants of Macromolecular Specificity from Proteomics-Derived Peptide Substrate Data

BACKGROUND

Recent advances in proteomics methodologies allow for high throughput profiling of proteolytic cleavage events. The resulting substrate peptide distributions provide deep insights in the underlying macromolecular recognition events, as determinants of biomolecular specificity identified by proteomics approaches may be compared to structure-based analysis of corresponding protein-protein interfaces.

METHOD

Here, we present an overview of experimental and computational methodologies and tools applied in the area and provide an outlook beyond the protein class of proteases.

RESULTS AND CONCLUSION

We discuss here future potential, synergies and needs of the emerging overlap disciplines of proteomics and structure-based modelling.

Phage display and structural studies reveal plasticity in substrate specificity of caspase-3a from zebrafish

The regulation of caspase-3 enzyme activity is a vital process in cell fate decisions leading to cell differentiation and tissue development or to apoptosis. The zebrafish, Danio rerio, has become an increasingly popular animal model to study several human diseases because of their transparent embryos, short reproductive cycles, and ease of drug administration. While apoptosis is an evolutionarily conserved process in metazoans, little is known about caspases from zebrafish, particularly regarding substrate specificity and allosteric regulation compared to the human caspases. We cloned zebrafish caspase-3a (casp3a) and examined substrate specificity of the recombinant protein, Casp3a, compared to human caspase-3 (CASP3) by utilizing M13 bacteriophage substrate libraries that incorporated either random amino acids at P5-P1' or aspartate fixed at P1. The results show a preference for the tetrapeptide sequence DNLD for both enzymes, but the P4 position of zebrafish Casp3a also accommodates valine equally well. We determined the structure of zebrafish Casp3a to 2.28Å resolution by X-ray crystallography, and when combined with molecular dynamics simulations, the results suggest that a limited number of amino acid substitutions near the active site result in plasticity of the S4 sub-site by increasing flexibility of one active site loop and by affecting hydrogen-bonding with substrate. The data show that zebrafish Casp3a exhibits a broader substrate portfolio, suggesting overlap with the functions of caspase-6 in zebrafish development.

Characterizing Protease Specificity: How Many Substrates Do We Need?

Calculation of cleavage entropies allows to quantify, map and compare protease substrate specificity by an information entropy based approach. The metric intrinsically depends on the number of experimentally determined substrates (data points). Thus a statistical analysis of its numerical stability is crucial to estimate the systematic error made by estimating specificity based on a limited number of substrates. In this contribution, we show the mathematical basis for estimating the uncertainty in cleavage entropies. Sets of cleavage entropies are calculated using experimental cleavage data and modeled extreme cases. By analyzing the underlying mathematics and applying statistical tools, a linear dependence of the metric in respect to 1/n was found. This allows us to extrapolate the values to an infinite number of samples and to estimate the errors. Analyzing the errors, a minimum number of 30 substrates was found to be necessary to characterize substrate specificity, in terms of amino acid variability, for a protease (S4-S4’) with an uncertainty of 5 percent. Therefore, we encourage experimental researchers in the protease field to record specificity profiles of novel proteases aiming to identify at least 30 peptide substrates of maximum sequence diversity. We expect a full characterization of protease specificity helpful to rationalize biological functions of proteases and to assist rational drug design.

Identification of Soft Matter Binding Peptide Ligands Using Phage Display

Phage display is a powerful tool for the selection of highly affine, short peptide ligands. While originally primarily used for the identification of ligands to proteins, the scope of this technique has significantly expanded over the past two decades. Phage display nowadays is also increasingly applied to identify ligands that selectively bind with high affinity to a broad range of other substrates including natural and biological polymers as well as a variety of low-molecular-weight organic molecules. Such peptides are of interest for various reasons. The ability to selectively and with high affinity bind to the substrate of interest allows the conjugation or immobilization of, e.g., nanoparticles or biomolecules, or generally, facilitates interactions at materials interfaces. On the other hand, presentation of peptide ligands that selectively bind to low-molecular-weight organic materials is of interest for the development of sensor surfaces. The aim of this article is to highlight the opportunities provided by phage display for the identification of peptide ligands that bind to synthetic or natural polymer substrates or to small organic molecules. The article will first provide an overview of the different peptide ligands that have been identified by phage display that bind to these "soft matter" targets. The second part of the article will discuss the different characterization techniques that allow the determination of the affinity of the identified ligands to the respective substrates.

Design of a Selective Substrate and Activity Based Probe for Human Neutrophil Serine Protease 4

Human neutrophil serine protease 4 (NSP4), also known as PRSS57, is a recently discovered fourth member of the neutrophil serine proteases family. Although its biological function is not precisely defined, it is suggested to regulate neutrophil response and innate immune reactions. To create optimal substrates and visualization probes for NSP4 that distinguish it from other NSPs we have employed a Hybrid Combinatorial Substrate Library approach that utilizes natural and unnatural amino acids to explore protease subsite preferences. Library results were validated by synthesizing individual substrates, leading to the identification of an optimal substrate peptide. This substrate was converted to a covalent diphenyl phosphonate probe with an embedded biotin tag. This probe demonstrated high inhibitory activity and stringent specificity and may be suitable for visualizing NSP4 in the background of other NSPs.

Proteomic approaches to uncover MMP function

Proteomics has revolutionized protease research and particularly contributed to the identification of novel substrates and their sites of cleavage as key determinants of protease function. New technologies and rapid advancements in development of powerful mass spectrometers allowed unprecedented insights into activities of matrix metalloproteinases (MMPs) within their complex extracellular environments. Mass spectrometry-based proteomics extended our knowledge on MMP cleavage specificities and will help to develop more specific inhibitors as new therapeutics. Quantitative proteomics and N-terminal enrichment strategies have revealed numerous novel MMP substrates and shed light on their modes of action in vitro and in vivo. In this review, we provide an overview of current proteomic technologies in protease research and their application to the functional characterization of MMPs.

Basis for substrate recognition and distinction by matrix metalloproteinases

Genomic sequencing and structural genomics produced a vast amount of sequence and structural data, creating an opportunity for structure-function analysis in silico [Radivojac P, et al. (2013) Nat Methods 10(3):221-227]. Unfortunately, only a few large experimental datasets exist to serve as benchmarks for function-related predictions. Furthermore, currently there are no reliable means to predict the extent of functional similarity among proteins. Here, we quantify structure-function relationships among three phylogenetic branches of the matrix metalloproteinase (MMP) family by comparing their cleavage efficiencies toward an extended set of phage peptide substrates that were selected from ∼ 64 million peptide sequences (i.e., a large unbiased representation of substrate space). The observed second-order rate constants [k(obs)] across the substrate space provide a distance measure of functional similarity among the MMPs. These functional distances directly correlate with MMP phylogenetic distance. There is also a remarkable and near-perfect correlation between the MMP substrate preference and sequence identity of 50-57 discontinuous residues surrounding the catalytic groove. We conclude that these residues represent the specificity-determining positions (SDPs) that allowed for the expansion of MMP proteolytic function during evolution. A transmutation of only a few selected SDPs proximal to the bound substrate peptide, and contributing the most to selectivity among the MMPs, is sufficient to enact a global change in the substrate preference of one MMP to that of another, indicating the potential for the rational and focused redesign of cleavage specificity in MMPs.

Bioinformatic approaches for modeling the substrate specificity of HIV-1 protease: an overview

HIV-1 protease has a broad and complex substrate specificity, which hitherto has escaped a simple comprehensive definition. This, and the relatively high mutation rate of the retroviral protease, makes it challenging to design effective protease inhibitors. Several attempts have been made during the last two decades to elucidate the enigmatic cleavage specificity of HIV-1 protease and to predict cleavage of novel substrates using bioinformatic analysis methods. This review describes the methods that have been utilized to date to address this important problem and the results achieved. The data sets used are also reviewed and important aspects of these are highlighted.

Substrate-driven mapping of the degradome by comparison of sequence logos

Sequence logos are frequently used to illustrate substrate preferences and specificity of proteases. Here, we employed the compiled substrates of the MEROPS database to introduce a novel metric for comparison of protease substrate preferences. The constructed similarity matrix of 62 proteases can be used to intuitively visualize similarities in protease substrate readout via principal component analysis and construction of protease specificity trees. Since our new metric is solely based on substrate data, we can engraft the protease tree including proteolytic enzymes of different evolutionary origin. Thereby, our analyses confirm pronounced overlaps in substrate recognition not only between proteases closely related on sequence basis but also between proteolytic enzymes of different evolutionary origin and catalytic type. To illustrate the applicability of our approach we analyze the distribution of targets of small molecules from the ChEMBL database in our substrate-based protease specificity trees. We observe a striking clustering of annotated targets in tree branches even though these grouped targets do not necessarily share similarity on protein sequence level. This highlights the value and applicability of knowledge acquired from peptide substrates in drug design of small molecules, e.g., for the prediction of off-target effects or drug repurposing. Consequently, our similarity metric allows to map the degradome and its associated drug target network via comparison of known substrate peptides. The substrate-driven view of protein-protein interfaces is not limited to the field of proteases but can be applied to any target class where a sufficient amount of known substrate data is available.

Substrate phage display for protease substrate sequence characterization: bovine factor Xa as a model system

Regulatory proteases modulate proteomic dynamics with a spectrum of specificities against substrate proteins. Substrate phage display is one of the key methodologies in producing substrate sequence information in vitro. Factor Xa, a key regulatory protease in the blood coagulation system, is used as a model system to demonstrate a high-throughput procedure to quantitatively characterize substrate sequences and their susceptibilities for enzymatic cleavage. This methodology can be generalized to proteases for which the active forms (not necessarily purified forms) are available for the in vitro experiments.