Phage-assisted evolution of botulinum neurotoxin proteases with reprogrammed specificity

Systems and Methods for Continuous Evolution of Enzymes

Directed evolution generates novel biomolecules with desired functions by iteratively diversifying the genetic sequence of wildtype biomolecules, relaying the genetic information to the molecule with function, and selecting the variants that progresses towards the properties of interest. While traditional directed evolution consumes significant labor and time for each step, continuous evolution seeks to automate all steps so directed evolution can proceed with minimum human intervention and dramatically shortened time. A major application of continuous evolution is the generation of novel enzymes, which catalyze reactions under conditions that are not favorable to their wildtype counterparts, or on altered substrates. The challenge to continuously evolve enzymes lies in automating sufficient, unbiased gene diversification, providing selection for a wide array of reaction types, and linking the genetic information to the phenotypic function. Over years of development, continuous evolution has accumulated versatile strategies to address these challenges, enabling its use as a general tool for enzyme engineering. As the capability of continuous evolution continues to expand, its impact will increase across various industries. In this review, we summarize the working mechanisms of recently developed continuous evolution strategies, discuss examples of their applications focusing on enzyme evolution, and point out their limitations and future directions.

Design of a mucin-selective protease for targeted degradation of cancer-associated mucins

Targeted protein degradation is an emerging strategy for the elimination of classically undruggable proteins. Here, to expand the landscape of targetable substrates, we designed degraders that achieve substrate selectivity via recognition of a discrete peptide and glycan motif and achieve cell-type selectivity via antigen-driven cell-surface binding. We applied this approach to mucins, O-glycosylated proteins that drive cancer progression through biophysical and immunological mechanisms. Engineering of a bacterial mucin-selective protease yielded a variant for fusion to a cancer antigen-binding nanobody. The resulting conjugate selectively degraded mucins on cancer cells, promoted cell death in culture models of mucin-driven growth and survival, and reduced tumor growth in mouse models of breast cancer progression. This work establishes a blueprint for the development of biologics that degrade specific protein glycoforms on target cells.

A combinatorial strategy for HRV 3C protease engineering to achieve the N-terminal free cleavage

Human rhinovirus 3C protease (HRV 3CP) has a high specificity against the substrate of LEVLFQ↓G at P1' site, which plays an important role in biotechnology and academia as a fusion tag removal tool. However, a non-ignorable limitation is that an extra residue of Gly would remain at the N terminus of the recombinant target protein after cleavage with HRV 3CP, thus potentially causing protein mis-functionality or immunogenicity. Here, we developed a combinatorial strategy by integrating structure-guided library design and high-throughput screening of eYESS approach for HRV 3CP engineering to expand its P1' specificity. Finally, a C3 variant was obtained, exhibiting a broad substrate P1' specificity to recognize 20 different amino acids with the highest activity against LEVLFQ↓M (kcat/KM = 3.72 ± 0.04 mM-1∙s-1). Further biochemical and NGS-mediated substrate profiling analysis showed that C3 variant still kept its substrate stringency at P1 site and good residue tolerance at P2' site, but with an expanded P1' specificity. Structural simulation of C3 indicated a reconstructed S1' binding pocket as well as new interactions with the substrates. Overall, our studies here prompt not only the practical applications and understanding of substrate recognition mechanisms of HRV 3CP, also provide new tools for other enzyme engineering.

Advances in recombinant protease production: current state and perspectives

Proteases, enzymes that catalyze the hydrolysis of peptide bonds in proteins, are important in the food industry, biotechnology, and medical fields. With increasing demand for proteases, there is a growing emphasis on enhancing their expression and production through microbial systems. However, proteases' native hosts often fall short in high-level expression and compatibility with downstream applications. As a result, the recombinant production of proteases has become a significant focus, offering a solution to these challenges. This review presents an overview of the current state of protease production in prokaryotic and eukaryotic expression systems, highlighting key findings and trends. In prokaryotic systems, the Bacillus spp. is the predominant host for proteinase expression. Yeasts are commonly used in eukaryotic systems. Recent advancements in protease engineering over the past five years, including rational design and directed evolution, are also highlighted. By exploring the progress in both expression systems and engineering techniques, this review provides a detailed understanding of the current landscape of recombinant protease research and its prospects for future advancements.

Continuous evolution of compact protein degradation tags regulated by selective molecular glues

Conditional protein degradation tags (degrons) are usually >100 amino acids long or are triggered by small molecules with substantial off-target effects, thwarting their use as specific modulators of endogenous protein levels. We developed a phage-assisted continuous evolution platform for molecular glue complexes (MG-PACE) and evolved a 36-amino acid zinc finger (ZF) degron (SD40) that binds the ubiquitin ligase substrate receptor cereblon in complex with PT-179, an orthogonal thalidomide derivative. Endogenous proteins tagged in-frame with SD40 using prime editing are degraded by otherwise inert PT-179. Cryo-electron microscopy structures of SD40 in complex with ligand-bound cereblon revealed mechanistic insights into the molecular basis of SD40's activity and specificity. Our efforts establish a system for continuous evolution of molecular glue complexes and provide ZF tags that overcome shortcomings associated with existing degrons.

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.

EvoAI enables extreme compression and reconstruction of the protein sequence space

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here, we first establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.

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.

Engineered bacterial orthogonal DNA replication system for continuous evolution

Continuous evolution can generate biomolecules for synthetic biology and enable evolutionary investigation. The orthogonal DNA replication system (OrthoRep) in yeast can efficiently mutate long DNA fragments in an easy-to-operate manner. However, such a system is lacking in bacteria. Therefore, we developed a bacterial orthogonal DNA replication system (BacORep) for continuous evolution. We achieved this by harnessing the temperate phage GIL16 DNA replication machinery in Bacillus thuringiensis with an engineered error-prone orthogonal DNA polymerase. BacORep introduces all 12 types of nucleotide substitution in 15-kilobase genes on orthogonally replicating linear plasmids with a 6,700-fold higher mutation rate than that of the host genome, the mutation rate of which is unchanged. Here we demonstrate the utility of BacORep-based continuous evolution by generating strong promoters applicable to model bacteria, Bacillus subtilis and Escherichia coli, and achieving a 7.4-fold methanol assimilation increase in B. thuringiensis. BacORep is a powerful tool for continuous evolution in prokaryotic cells.

A look at the future-new BoNTs and delivery systems in development: What it could mean in the clinic

Despite the expanding clinical utility of botulinum neurotoxins, there remain problems to be solved for attaining the best outcome. The efficacy and safety need to be reconsidered for commercially available preparations all derived from subtype A1 or B1. Emerging new toxins include A2 or A6 subtypes or engineered toxins with less spread, more potency, longer durations of action, less antigenicity and better safety profile than currently used preparations. Non-toxic BoNTs with a few amino acid replacements of the light chain (LC) may have a role as a drug-delivery system if the toxicity is abolished entirely. At present, efficacy of these BoNTs in animal botulism was demonstrated.

Virus-assisted directed evolution of biomolecules

Directed evolution is a powerful technique that uses principles of natural evolution to enable the development of biomolecules with novel functions. However, the slow pace of natural evolution does not support the demand for rapidly generating new biomolecular functions in the laboratory. Viruses offer a unique path to design fast laboratory evolution experiments, owing to their innate ability to evolve much more rapidly than most living organisms, facilitated by a smaller genome size that tolerate a high frequency of mutations, as well as a fast rate of replication. These attributes offer a great opportunity to evolve various biomolecules by linking their activity to the replication of a suitable virus. This review highlights the recent advances in the application of virus-assisted directed evolution of designer biomolecules in both prokaryotic and eukaryotic cells.

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.

Advances in ultrahigh-throughput screening technologies for protein evolution

Inspired by natural evolution, directed evolution randomly mutates the gene of interest through artificial evolution conditions with variants being screened for the required properties. Directed evolution is vital to the enhancement of protein properties and comprises the construction of libraries with considerable diversity as well as screening methods with sufficient efficiency as key steps. Owing to the various characteristics of proteins, specific methods are urgently needed for library screening, which is one of the main limiting factors in accelerating evolution. This review initially organizes the principles of ultrahigh-throughput screening from the perspective of protein properties. It then provides a comprehensive introduction to the latest progress and future trends in ultrahigh-throughput screening technologies for directed evolution.

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.

Cancer Drug Delivery Systems Using Bacterial Toxin Translocation Mechanisms

Recent advances in targeted cancer therapy hold great promise for both research and clinical applications and push the boundaries in finding new treatments for various currently incurable cancers. However, these therapies require specific cell-targeting mechanisms for the efficient delivery of drug cargo across the cell membrane to reach intracellular targets and avoid diffusion to unwanted tissues. Traditional drug delivery systems suffer from a limited ability to travel across the barriers posed by cell membranes and, therefore, there is a need for high doses, which are associated with adverse reactions and safety concerns. Bacterial toxins have evolved naturally to specifically target cell subtypes via their receptor binding module, penetrating the cell membrane efficiently through the membrane translocation process and then successfully delivering the toxic cargo into the host cytosol. They have, thus, been harnessed for the delivery of various drugs. In this review, we focus on bacterial toxin translocation mechanisms and recent progress in the targeted delivery systems of cancer therapy drugs that have been inspired by the receptor binding and membrane translocation processes of the anthrax toxin protective antigen, diphtheria toxin, and Pseudomonas exotoxin A. We also discuss the challenges and limitations of these studies that should be addressed before bacterial toxin-based drug delivery systems can become a viable new generation of drug delivery approaches in clinical translation.

Botulinum neurotoxins: Future innovations

Botulinum neurotoxins (BoNTs) are multi-domain proteins whose potent and selective actions on nerve endings have led to innovations in both basic and clinical science. The various BoNT domains are responsible for binding to gangliosides and proteins associated with nerve cell membranes, internalization into the cell, and cleavage of one or more SNARE (soluble N-ethylmaleimide sensitive factor attachment protein receptor) proteins necessary for vesicle docking and fusion. Novel modifications to BoNT molecules, such as the creation of chimeras, helped identify the protein domains responsible for various aspects of BoNT action, such as localized effects. Other molecular modifications have been introduced in attempts to increase the specificity of BoNTs for autonomic or sensory neurons, with the ultimate goal of optimizing therapeutic selectivity. This research, in turn, has led to the development of BoNT-based proteins that can target non-SNARE substrates such as phosphatase and tensin homolog (PTEN). Still others are developing different BoNT serotypes, subtypes, or variants that are longer- or shorter-acting or have faster onset for various clinical purposes. New formulations of BoNTs that provide convenience for both patients and physicians are under investigation. Novel clinical uses are being evaluated for onabotulinumtoxinA, including in the prevention of post-operative atrial fibrillation. All these innovations capitalize on the unique properties of BoNTs, which continue to intrigue scientists and clinicians across numerous fields of study.

Evolution of an adenine base editor into a small, efficient cytosine base editor with low off-target activity

Cytosine base editors (CBEs) are larger and can suffer from higher off-target activity or lower on-target editing efficiency than current adenine base editors (ABEs). To develop a CBE that retains the small size, low off-target activity and high on-target activity of current ABEs, we evolved the highly active deoxyadenosine deaminase TadA-8e to perform cytidine deamination using phage-assisted continuous evolution. Evolved TadA cytidine deaminases contain mutations at DNA-binding residues that alter enzyme selectivity to strongly favor deoxycytidine over deoxyadenosine deamination. Compared to commonly used CBEs, TadA-derived cytosine base editors (TadCBEs) offer similar or higher on-target activity, smaller size and substantially lower Cas-independent DNA and RNA off-target editing activity. We also identified a TadA dual base editor (TadDE) that performs equally efficient cytosine and adenine base editing. TadCBEs support single or multiplexed base editing at therapeutically relevant genomic loci in primary human T cells and primary human hematopoietic stem and progenitor cells. TadCBEs expand the utility of CBEs for precision gene editing.

DNA-Encoded Libraries: Towards Harnessing their Full Power with Darwinian Evolution

DNA-encoded library (DEL) technologies are transforming the drug discovery process, enabling the identification of ligands at unprecedented speed and scale. DEL makes use of libraries that are orders of magnitude larger than traditional high-throughput screens. While a DNA tag alludes to a genotype-phenotype connection that is exploitable for molecular evolution, most of the work in the field is performed with libraries where the tag serves as an amplifiable barcode but does not allow "translation" into the synthetic product it is linked to. In this Review, we cover technologies that enable the "translation" of the genetic tag into synthetic molecules, both biochemically and chemically, and explore how it can be used to harness Darwinian evolutionary pressure.

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.

Functional Deimmunization of Botulinum Neurotoxin Protease Domain via Computationally Driven Library Design and Ultrahigh-Throughput Screening

Botulinum neurotoxin serotype A (BoNT/A) is a widely used cosmetic agent that also has diverse therapeutic applications; however, adverse antidrug immune responses and associated loss of efficacy have been reported in clinical uses. Here, we describe computational design and ultrahigh-throughput screening of a massive BoNT/A light-chain (BoNT/A-LC) library optimized for reduced T cell epitope content and thereby dampened immunogenicity. We developed a functional assay based on bacterial co-expression of BoNT/A-LC library members with a Förster resonance energy transfer (FRET) sensor for BoNT/A-LC enzymatic activity, and we employed high-speed fluorescence-activated cell sorting (FACS) to identify numerous computationally designed variants having wild-type-like enzyme kinetics. Many of these variants exhibited decreased immunogenicity in humanized HLA transgenic mice and manifested in vivo paralytic activity when incorporated into full-length toxin. One variant achieved near-wild-type paralytic potency and a 300% reduction in antidrug antibody response in vivo. Thus, we have achieved a striking level of BoNT/A-LC functional deimmunization by combining computational library design and ultrahigh-throughput screening. This strategy holds promise for deimmunizing other biologics with complex superstructures and mechanisms of action.

Structure and activity of botulinum neurotoxin X

Botulinum neurotoxins (BoNTs) are the most potent toxins known and are used to treat an increasing number of medical disorders. All BoNTs are naturally co-expressed with a protective partner protein (NTNH) with which they form a 300 kDa complex, to resist acidic and proteolytic attack from the digestive tract. We have previously identified a new botulinum neurotoxin serotype, BoNT/X, that has unique and therapeutically attractive properties. We present the cryo-EM structure of the BoNT/X-NTNH/X complex at 3.1 Å resolution. Unexpectedly, the BoNT/X complex is stable and protease resistant at both neutral and acidic pH and disassembles only in alkaline conditions. Using the stabilizing effect of NTNH, we isolated BoNT/X and showed that it has very low potency both in vitro and in vivo . Given the high catalytic activity and translocation efficacy of BoNT/X, low activity of the full toxin is likely due to the receptor-binding domain, which presents weak ganglioside binding and exposed hydrophobic surfaces.

Reprogramming the Cleavage Specificity of Botulinum Neurotoxin Serotype B1

Proteases with reprogrammed specificity for nonnative substrates are highly desired in synthetic biology and biomedicine. However, generating reprogrammed proteases that are orthogonal and highly specific for a new target has been a major challenge. In this work, we sought to expand the versatility of protease systems by engineering an orthogonal botulinum neurotoxin serotype B (BoNT/B) protease that recognizes an orthogonal substrate. We designed and validated an orthogonal BoNT/B protease system in mammalian cells, combining mutations in the protease with compensatory mutations in the protease substrate and incorporating a truncated target sequence and then demonstrated use of this orthogonal BoNT/B protease-substrate combination to regulate complex transcriptional circuitry in mammalian cells. Transposing this platform into yeast, we demonstrated utility of this approach for in vivo protease evolution. We tested this platform with the newly designed orthogonal protease and then used it in a high-throughput screen to identify novel orthogonal protease/protease substrate combinations. While carrying out this work, we also generated new cleavage reporters that could be used to report botulinum toxin protease activity in mammalian cells using simple fluorescent readouts. We envision that these approaches will expand the applications of botulinum protease in new directions and aid in the development of new reprogrammed proteases.

Exploiting spatial dimensions to enable parallelized continuous directed evolution

Current strategies to improve the throughput of continuous directed evolution technologies often involve complex mechanical fluid‐controlling system or robotic platforms, which limits their popularization and application in general laboratories. Inspired by our previous study on bacterial range expansion, in this study, we report a system termed SPACE for rapid and extensively parallelizable evolution of biomolecules by introducing spatial dimensions into the landmark phage‐assisted continuous evolution system. Specifically, M13 phages and chemotactic Escherichia coli cells were closely inoculated onto a semisolid agar. The phages came into contact with the expanding front of the bacterial range, and then comigrated with the bacteria. This system leverages competition over space, wherein evolutionary progress is closely associated with the production of spatial patterns, allowing the emergence of improved or new protein functions. In a prototypical problem, SPACE remarkably simplified the process and evolved the promoter recognition of T7 RNA polymerase (RNAP) to a library of 96 random sequences in parallel. These results establish SPACE as a simple, easy to implement, and massively parallelizable platform for continuous directed evolution in general laboratories.

Reengineering the specificity of the highly selective Clostridium botulinum protease via directed evolution

The botulinum neurotoxin serotype A (BoNT/A) cuts a single peptide bond in SNAP25, an activity used to treat a wide range of diseases. Reengineering the substrate specificity of BoNT/A’s protease domain (LC/A) could expand its therapeutic applications; however, LC/A’s extended substrate recognition (≈ 60 residues) challenges conventional approaches. We report a directed evolution method for retargeting LC/A and retaining its exquisite specificity. The resultant eight-mutation LC/A (omLC/A) has improved cleavage specificity and catalytic efficiency (1300- and 120-fold, respectively) for SNAP23 versus SNAP25 compared to a previously reported LC/A variant. Importantly, the BoNT/A holotoxin equipped with omLC/A retains its ability to form full-length holotoxin, infiltrate neurons, and cleave SNAP23. The identification of substrate control loops outside BoNT/A’s active site could guide the design of improved BoNT proteases and inhibitors.

Methods for the directed evolution of biomolecular interactions

Noncovalent interactions between biomolecules such as proteins and nucleic acids coordinate all cellular processes through changes in proximity. Tools that perturb these interactions are and will continue to be highly valuable for basic and translational scientific endeavors. By taking cues from natural systems, such as the adaptive immune system, we can design directed evolution platforms that can generate proteins that bind to biomolecules of interest. In recent years, the platforms used to direct the evolution of biomolecular binders have greatly expanded the range of types of interactions one can evolve. Herein, we review recent advances in methods to evolve protein-protein, protein-RNA, and protein-DNA interactions.

Toxicology and pharmacology of botulinum and tetanus neurotoxins: an update

Tetanus and botulinum neurotoxins cause the neuroparalytic syndromes of tetanus and botulism, respectively, by delivering inside different types of neurons, metalloproteases specifically cleaving the SNARE proteins that are essential for the release of neurotransmitters. Research on their mechanism of action is intensively carried out in order to devise improved therapies based on antibodies and chemical drugs. Recently, major results have been obtained with human monoclonal antibodies and with single chain antibodies that have allowed one to neutralize the metalloprotease activity of botulinum neurotoxin type A1 inside neurons. In addition, a method has been devised to induce a rapid molecular evolution of the metalloprotease domain of botulinum neurotoxin followed by selection driven to re-target the metalloprotease activity versus novel targets with respect to the SNARE proteins. At the same time, an intense and wide spectrum clinical research on novel therapeutics based on botulinum neurotoxins is carried out, which are also reviewed here.

Conformation-driven strategy for resilient and functional protein materials

The exceptional elastic resilience of some protein materials underlies essential biomechanical functions with broad interest in biomedical fields. However, molecular design of elastic resilience is restricted to amino acid sequences of a handful of naturally occurring resilient proteins such as resilin and elastin. Here, we exploit non-resilin/elastin sequences that adopt kinetically stabilized, random coil-dominated conformations to achieve near-perfect resilience comparable with that of resilin and elastin. We also show a direct correlation between resilience and Raman-characterized protein conformations. Furthermore, we demonstrate that metastable conformation of proteins enables the construction of mechanically graded protein materials that exhibit spatially controlled conformations and resilience. These results offer insights into molecular mechanisms of protein elastomers and outline a general conformation-driven strategy for developing resilient and functional protein materials.

The past, present, and future of enzyme-based therapies

Enzyme-based therapeutics (EBTs) have the potential to tap into an almost unmeasurable amount of enzyme biodiversity and treat myriad conditions. Although EBTs were some of the first biologics used clinically, the rate of development of newer EBTs has lagged behind that of other biologics. Here, we review the history of EBTs, and discuss the state of each class of EBT, their potential clinical advantages, and the unique challenges to their development. Additionally, we discuss key remaining technical barriers that, if addressed, could increase the diversity and rate of the development of EBTs.

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.

Botulinum Neurotoxins in Central Nervous System: An Overview from Animal Models to Human Therapy

Botulinum neurotoxins (BoNTs) are potent inhibitors of synaptic vesicle fusion and transmitter release. The natural target of BoNTs is the peripheral neuromuscular junction (NMJ) where, by blocking the release of acetylcholine (ACh), they functionally denervate muscles and alter muscle tone. This leads them to be an excellent drug for the therapy of muscle hyperactivity disorders, such as dystonia, spasticity, and many other movement disorders. BoNTs are also effective in inhibiting both the release of ACh at sites other than NMJ and the release of neurotransmitters other than ACh. Furthermore, much evidence shows that BoNTs can act not only on the peripheral nervous system (PNS), but also on the central nervous system (CNS). Under this view, central changes may result either from sensory input from the PNS, from retrograde transport of BoNTs, or from direct injection of BoNTs into the CNS. The aim of this review is to give an update on available data, both from animal models or human studies, which suggest or confirm central alterations induced by peripheral or central BoNTs treatment. The data will be discussed with particular attention to the possible therapeutic applications to pathological conditions and degenerative diseases of the CNS.

Disulfide-compatible phage-assisted continuous evolution in the periplasmic space

The directed evolution of antibodies has yielded important research tools and human therapeutics. The dependence of many antibodies on disulfide bonds for stability has limited the application of continuous evolution technologies to antibodies and other disulfide-containing proteins. Here we describe periplasmic phage-assisted continuous evolution (pPACE), a system for continuous evolution of protein-protein interactions in the disulfide-compatible environment of the E. coli periplasm. We first apply pPACE to rapidly evolve novel noncovalent and covalent interactions between subunits of homodimeric YibK protein and to correct a binding-defective mutant of the anti-GCN4 Ω-graft antibody. We develop an intein-mediated system to select for soluble periplasmic expression in pPACE, leading to an eight-fold increase in soluble expression of the Ω-graft antibody. Finally, we evolve disulfide-containing trastuzumab antibody variants with improved binding to a Her2-like peptide and improved soluble expression. Together, these results demonstrate that pPACE can rapidly optimize proteins containing disulfide bonds, broadening the applicability of continuous evolution.

A System for the Evolution of Protein-Protein Interaction Inducers

Molecules that induce interactions between proteins, often referred to as "molecular glues", are increasingly recognized as important therapeutic modalities and as entry points for rewiring cellular signaling networks. Here, we report a new PACE-based method to rapidly select and evolve molecules that mediate interactions between otherwise noninteracting proteins: rapid evolution of protein-protein interaction glues (rePPI-G). By leveraging proximity-dependent split RNA polymerase-based biosensors, we developed E. coli-based detection and selection systems that drive gene expression outputs only when interactions between target proteins are induced. We then validated the system using engineered bivalent molecular glues, showing that rePPI-G robustly selects for molecules that induce the target interaction. Proof-of-concept evolutions demonstrated that rePPI-G reduces the "hook effect" of the engineered molecular glues, due at least in part to tuning the interaction affinities of each individual component of the bifunctional molecule. Altogether, this work validates rePPI-G as a continuous, phage-based evolutionary technology for optimizing molecular glues, providing a strategy for developing molecules that reprogram protein-protein interactions.

Chemical engineering of bacterial effectors for regulating cell signaling and responses

Bacteria have evolved a variety of effector proteins to facilitate their survival and proliferation within the host environment. Continuous competition at the host-pathogen interface has empowered these effectors with unique mechanism and high specificity toward their host targets. The rich repertoire of bacterial effectors has thus provided us an attractive toolkit for investigating various cellular processes, such as signal transductions. With recent advances in protein chemistry and engineering, we now have the capability for on-demand control of protein activity with high precision. Herein, we review the development of chemically engineered bacterial effectors to control kinase-mediated signal transductions, inhibit protein translation, and direct genetic editing within host cells. We also highlight future opportunities for harnessing diverse prokaryotic effectors as powerful tools for mechanistic investigation and therapeutic intervention of eukaryotic systems.