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Computational protein design is advancing rapidly. Here we describe efficient routes starting from validated parallel and antiparallel peptide assemblies to design two families of α-helical barrel proteins with central channels that bind small molecules. Computational designs are seeded by the sequences and structures of defined de novo oligomeric barrel-forming peptides, and adjacent helices are connected by loop building. For targets with antiparallel helices, short loops are sufficient. However, targets with parallel helices require longer connectors; namely, an outer layer of helix-turn-helix-turn-helix motifs that are packed onto the barrels. Throughout these computational pipelines, residues that define open states of the barrels are maintained. This minimizes sequence sampling, accelerating the design process. For each of six targets, just two to six synthetic genes are made for expression in Escherichia coli. On average, 70% of these genes express to give soluble monomeric proteins that are fully characterized, including high-resolution structures for most targets that match the design models with high accuracy.

Interactions among biomacromolecules, predominantly noncovalent, underpin biological processes. However, recent advancements in biospecific chemistry have enabled the creation of specific covalent bonds between biomolecules, both in vitro and in vivo. This Review traces the evolution of biospecific chemistry in proteins, emphasizing the role of genetically encoded latent bioreactive amino acids. These amino acids react selectively with adjacent natural groups through proximity-enabled bioreactivity, enabling targeted covalent linkages. We explore various latent bioreactive amino acids designed to target different protein residues, ribonucleic acids, and carbohydrates. We then discuss how these novel covalent linkages can drive challenging protein properties and capture transient protein-protein and protein-RNA interactions in vivo. Additionally, we examine the application of covalent peptides as potential therapeutic agents and site-specific conjugates for native antibodies, highlighting their capacity to form stable linkages with target molecules. A significant focus is placed on proximity-enabled reactive therapeutics (PERx), a pioneering technology in covalent protein therapeutics. We detail its wide-ranging applications in immunotherapy, viral neutralization, and targeted radionuclide therapy. Finally, we present a perspective on the existing challenges within biospecific chemistry and discuss the potential avenues for future exploration and advancement in this rapidly evolving field.

Extracellular vesicles (EVs) play key roles in diverse biological processes, transport biomolecules between cells and have been engineered for therapeutic applications. A useful EV bioengineering strategy is to express engineered proteins on the EV surface to confer targeting, bioactivity and other properties. Measuring how incorporation varies across a population of EVs is important for characterising such materials and understanding their function, yet it remains challenging to quantitatively characterise the absolute number of engineered proteins incorporated at single-EV resolution. To address these needs, we developed a HaloTag-based characterisation platform in which dyes or other synthetic species can be covalently and stoichiometrically attached to engineered proteins on the EV surface. To evaluate this system, we employed several orthogonal quantification methods, including flow cytometry and fluorescence microscopy, and found that HaloTag-mediated quantification is generally robust across EV analysis methods. We compared HaloTag-labelling to antibody-labelling of EVs using single vesicle flow cytometry, enabling us to measure the substantial degree to which antibody labelling can underestimate proteins present on an EV. Finally, we demonstrate the use of HaloTag to compare between protein designs for EV bioengineering. Overall, the HaloTag system is a useful EV characterisation tool which complements and expands existing methods.

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from

The Exabiome project seeks to improve the understanding of microbiomes through the development of methods for accelerating metagenomic science using exascale computing. This article gives an overview of scientific impact of the three components of the project: metagenome assembly, protein family detection, and comparative analysis of metagenomes. Exabiome developed MetaHipMer, the only metagenome assembler capable of scaling to full exascale systems. MetaHipMer has enabled ground-breaking assemblies on the Frontier supercomputer, with many scientific benefits, such as the discovery of rare species and viral genomes. To investigate protein families, Exabiome developed two exascale tools, PASTIS and HipMCL. Together, these can utilize exascale resources to understand the functional diversity of billions of dark matter proteins and novel protein families. For comparative analysis, Exabiome developed kmerprof, a tool that can be used to compare huge metagenomes for many different scientific purposes, for example, grouping human microbiomes according to body location.

The sensitivity and responsiveness of living cells to environmental changes are enabled by dynamic protein structures, inspiring efforts to construct artificial supramolecular protein assemblies. However, despite their sophisticated structures, designed protein assemblies have yet to be incorporated into macroscale devices for real-life applications. We report a 2D crystalline protein assembly of C98/E57/E66L-rhamnulose-1-phosphate aldolase (CEERhuA) that selectively blocks or passes molecular species when exposed to a chemical trigger. CEERhuA crystals are engineered via cobalt(II) coordination bonds to undergo a coherent conformational change from a closed state (pore dimensions

The effective design of combinatorial libraries to balance fitness and diversity facilitates the engineering of useful enzyme functions, particularly those that are poorly characterized or unknown in biology. We introduce MODIFY, a machine learning (ML) algorithm that learns from natural protein sequences to infer evolutionarily plausible mutations and predict enzyme fitness. MODIFY co-optimizes predicted fitness and sequence diversity of starting libraries, prioritizing high-fitness variants while ensuring broad sequence coverage. In silico evaluation shows that MODIFY outperforms state-of-the-art unsupervised methods in zero-shot fitness prediction and enables ML-guided directed evolution with enhanced efficiency. Using MODIFY, we engineer generalist biocatalysts derived from a thermostable cytochrome c to achieve enantioselective C-B and C-Si bond formation via a new-to-nature carbene transfer mechanism, leading to biocatalysts six mutations away from previously developed enzymes while exhibiting superior or comparable activities. These results demonstrate MODIFY's potential in solving challenging enzyme engineering problems beyond the reach of classic directed evolution.

Polyketide retrobiosynthesis, where the biosynthetic pathway of a given polyketide can be reversibly engineered due to the colinearity of the polyketide synthase (PKS) structure and function, has the potential to produce millions of organic molecules. Mixing and matching modules from natural PKSs is one of the routes to produce many of these molecules. Evolutionary analysis of PKSs suggests that traditionally used module boundaries may not lead to the most productive hybrid PKSs and that new boundaries around and within the ketosynthase domain may be more active when constructing hybrid PKSs. As this is still a nascent area of research, the generality of these design principles based on existing engineering efforts remains inconclusive. Recent advances in structural modeling and synthetic biology present an opportunity to accelerate PKS engineering by re-evaluating insights gained from previous engineering efforts with cutting edge tools.

Protein engineering holds immense promise in shaping the future of biomedicine and biotechnology. This Review focuses on our ongoing development of Mutexa, a computational ecosystem designed to enable intelligent protein engineering. In this vision, researchers will seamlessly acquire sequences of protein variants with desired functions as biocatalysts, therapeutic peptides, and diagnostic proteins through a finely-tuned computational machine, akin to Amazon Alexas role as a versatile virtual assistant. The technical foundation of Mutexa has been established through the development of a database that combines and relates enzyme structures and their respective functions (e.g., IntEnzyDB), workflow software packages that enable high-throughput protein modeling (e.g., EnzyHTP and LassoHTP), and scoring functions that map the sequence-structure-function relationship of proteins (e.g., EnzyKR and DeepLasso). We will showcase the applications of these tools in benchmarking the convergence conditions of enzyme functional descriptors across mutants, investigating protein electrostatics and cavity distributions in SAM-dependent methyltransferases, and understanding the role of nonelectrostatic dynamic effects in enzyme catalysis. Finally, we will conclude by addressing the future steps and fundamental challenges in our endeavor to develop new Mutexa applications that assist the identification of beneficial mutants in protein engineering.

Characterizing differences in sequences between two conditions, such as with and without drug exposure, using high-throughput sequencing data is a prevalent problem involving quantifying changes in sequence abundances, and predicting such differences for unobserved sequences. A key shortcoming of current approaches is their extremely limited ability to share information across related but non-identical reads. Consequently, they cannot use sequencing data effectively, nor be directly applied in many settings of interest. We introduce model-based enrichment (MBE) to overcome this shortcoming. We evaluate MBE using both simulated and real data. Overall, MBE improves accuracy compared to current differential analysis methods.

DNA-editing enzymes perform chemical reactions on DNA nucleobases. These reactions can change the genetic identity of the modified base or modulate gene expression. Interest in DNA-editing enzymes has burgeoned in recent years due to the advent of clustered regularly interspaced short palindromic repeat-associated (CRISPR-Cas) systems, which can be used to direct their DNA-editing activity to specific genomic loci of interest. In this review, we showcase DNA-editing enzymes that have been repurposed or redesigned and developed into programmable base editors. These include deaminases, glycosylases, methyltransferases, and demethylases. We highlight the astounding degree to which these enzymes have been redesigned, evolved, and refined and present these collective engineering efforts as a paragon for future efforts to repurpose and engineer other families of enzymes. Collectively, base editors derived from these DNA-editing enzymes facilitate programmable point mutation introduction and gene expression modulation by targeted chemical modification of nucleobases.

Genetically encoded voltage indicators, particularly those based on microbial rhodopsins, are gaining traction in neuroscience as fluorescent sensors for imaging voltage dynamics with high-spatiotemporal precision. Here we establish a novel genetically encoded voltage indicator candidate based on the recently discovered subfamily of the microbial rhodopsin clade, termed heliorhodopsins. We discovered that upon excitation at 530 to 560 nm, wildtype heliorhodopsin exhibits near-infrared fluorescence, which is sensitive to membrane voltage. We characterized the fluorescence brightness, photostability, voltage sensitivity, and kinetics of wildtype heliorhodopsin in HEK293T cells and further examined the impact of mutating key residues near the retinal chromophore. The S237A mutation significantly improved the fluorescence response of heliorhodopsin by 76% providing a highly promising starting point for further protein evolution.

Photosynthetic light harvesting requires efficient energy transfer within dynamic networks of light-harvesting complexes embedded within phospholipid membranes. Artificial light-harvesting models are valuable tools for understanding the structural features underpinning energy absorption and transfer within chromophore arrays. Here, a method for attaching a protein-based light-harvesting model to a planar, fluid supported lipid bilayer (SLB) is developed.  The protein model consists of the tobacco mosaic viral capsid proteins that are gene-doubled to create a tandem dimer (dTMV). Assemblies of dTMV break the facial symmetry of the double disk to allow for differentiation between the disk faces. A single reactive lysine residue is incorporated into the dTMV assemblies for the site-selective attachment of chromophores for light absorption. On the opposing dTMV face, a cysteine residue is incorporated for the bioconjugation of a peptide containing a polyhistidine tag for association with SLBs. The dual-modified dTMV complexes show significant association with SLBs and exhibit mobility on the bilayer. The techniques used herein offer a new method for protein-surface attachment and provide a platform for evaluating excited state energy transfer events in a dynamic, fully synthetic artificial light-harvesting system.

Hematopoietic stem cell transplantation (HSCT) can replace endogenous microglia with circulation-derived macrophages but has high mortality. To mitigate the risks of HSCT and expand the potential for microglia replacement, we engineered an inhibitor-resistant CSF1R that enables robust microglia replacement. A glycine to alanine substitution at position 795 of human CSF1R (G795A) confers resistance to multiple CSF1R inhibitors, including PLX3397 and PLX5622. Biochemical and cell-based assays show no discernable gain or loss of function. G795A- but not wildtype-CSF1R expressing macrophages efficiently engraft the brain of PLX3397-treated mice and persist after cessation of inhibitor treatment. To gauge translational potential, we CRISPR engineered human-induced pluripotent stem cell-derived microglia (iMG) to express G795A. Xenotransplantation studies demonstrate that G795A-iMG exhibit nearly identical gene expression to wildtype iMG, respond to inflammatory stimuli, and progressively expand in the presence of PLX3397, replacing endogenous microglia to fully occupy the brain. In sum, we engineered a human CSF1R variant that enables nontoxic, cell type, and tissue-specific replacement of microglia.

Chimeric antigen receptors (CAR) are fusion proteins whose functional domains are often connected in a plug-and-play manner to generate multiple CAR variants. However, CARs with highly similar sequences can exhibit dramatic differences in function. Thus, approaches to rationally optimize CAR proteins are critical to the development of effective CAR T-cell therapies. Here, we report that as few as two amino-acid changes in nonsignaling domains of a CAR were able to significantly enhance in vivo antitumor efficacy. We demonstrate juxtamembrane alanine insertion and single-chain variable fragment sequence hybridization as two strategies that could be combined to maximize CAR functionality, and describe a CD20 CAR that outperformed the CD19 CAR in antitumor efficacy in preclinical in vitro and in vivo assays. Precise changes in the CAR sequence drove dramatically different transcriptomic profiles upon antigen stimulation, with the most efficacious CAR inducing an enrichment in highly functional memory T cells upon antigen stimulation. These findings underscore the importance of sequence-level optimization to CAR T-cell function, and the protein-engineering strategy described here may be applied to the development of additional CARs against diverse antigens. See related Spotlight by Scheller and Hudecek, p. 142.

Identifying function-enhancing enzyme variants is a holy grail challenge in protein science because it will allow researchers to expand the biocatalytic toolbox for late-stage functionalization of drug-like molecules, environmental degradation of plastics and other pollutants, and medical treatment of food allergies. Data-driven strategies, including statistical modeling, machine learning, and deep learning, have largely advanced the understanding of the sequence-structure-function relationships for enzymes. They have also enhanced the capability of predicting and designing new enzymes and enzyme variants for catalyzing the transformation of new-to-nature reactions. Here, we reviewed the recent progresses of data-driven models that were applied in identifying efficiency-enhancing mutants for catalytic reactions. We also discussed existing challenges and obstacles faced by the community. Although the review is by no means comprehensive, we hope that the discussion can inform the readers about the state-of-the-art in data-driven enzyme engineering, inspiring more joint experimental-computational efforts to develop and apply data-driven modeling to innovate biocatalysts for synthetic and pharmaceutical applications.

Prenyltransfer is an early-stage carbon-hydrogen bond (C-H) functionalization prevalent in the biosynthesis of a diverse array of biologically active bacterial, fungal, plant, and metazoan diketopiperazine (DKP) alkaloids. Toward the development of a unified strategy for biocatalytic construction of prenylated DKP indole alkaloids, we sought to identify and characterize a substrate-permissive C2 reverse prenyltransferase (PT). As the first tailoring event within the biosynthesis of cytotoxic notoamide metabolites, PT NotF catalyzes C2 reverse prenyltransfer of brevianamide F. Solving a crystal structure of NotF (in complex with native substrate and prenyl donor mimic dimethylallyl S-thiolodiphosphate (DMSPP)) revealed a large, solvent-exposed active site, intimating NotF may possess a significantly broad substrate scope. To assess the substrate selectivity of NotF, we synthesized a panel of 30 sterically and electronically differentiated tryptophanyl DKPs, the majority of which were selectively prenylated by NotF in synthetically useful conversions (2 to >99%). Quantitative representation of this substrate library and development of a descriptive statistical model provided insight into the molecular origins of NotF's substrate promiscuity. This approach enabled the identification of key substrate descriptors (electrophilicity, size, and flexibility) that govern the rate of NotF-catalyzed prenyltransfer, and the development of an "induced fit docking (IFD)-guided" engineering strategy for improved turnover of our largest substrates. We further demonstrated the utility of NotF in tandem with oxidative cyclization using flavin monooxygenase, BvnB. This one-pot, in vitro biocatalytic cascade enabled the first chemoenzymatic synthesis of the marine fungal natural product, (-)-eurotiumin A, in three steps and 60% overall yield.

Natural killer (NK) cells are a major subset of innate immune cells that are essential for host defense against pathogens and cancer. Two main classes of inhibitory NK receptors (NKR), KIR and CD94/NKG2A, play a key role in suppressing NK activity upon engagement with tumor cells or virus-infected cells, limiting their antitumor and antiviral activities. Here, we find that single-chain NKR antagonists linked to a VHH that binds the cell surface phosphatase CD45 potentiate NK and T activities to a greater extent than NKR blocking antibodies alone in vitro. We also uncovered crosstalk between NKG2A and Ly49 that collectively inhibit NK cell activation, such that CD45-NKG2A and CD45-Ly49 bispecific molecules show synergistic effects in their ability to enhance NK cell activation. The basis of the activity enhancement by CD45 ligation may reflect greater antagonism of inhibitory signaling from engagement of MHC I on target cells, combined with other mechanisms, including avidity effects, tonic signaling, antagonism of weak inhibition from engagement of MHC I on non-target cells, and possible CD45 segregation within the NK cell-target cell synapse. These results uncover a strategy for enhancing the activity of NK and T cells that may improve cancer immunotherapies.

Far-red and near-infrared (NIR) genetically encoded calcium ion (Ca2+ ) indicators (GECIs) are powerful tools for in vivo and multiplexed imaging of neural activity and cell signaling. Inspired by a previous report to engineer a far-red fluorescent protein (FP) from a biliverdin (BV)-binding NIR FP, we have developed a far-red fluorescent GECI, designated iBB-GECO1, from a previously reported NIR GECI. iBB-GECO1 exhibits a relatively high molecular brightness, an inverse response to Ca2+ with ΔF/Fmin  = -13, and a near-optimal dissociation constant (Kd ) for Ca2+ of 105 nM. We demonstrate the utility of iBB-GECO1 for four-color multiplexed imaging in MIN6 cells and five-color imaging in HEK293T cells. Like other BV-binding GECIs, iBB-GECO1 did not give robust signals during in vivo imaging of neural activity in mice, but did provide promising results that will guide future engineering efforts. SIGNIFICANCE: Genetically encoded calcium ion (Ca2+ ) indicators (GECIs) compatible with common far-red laser lines (~630-640 nm) on commercial microscopes are of critical importance for their widespread application to deep-tissue multiplexed imaging of neural activity. In this study, we engineered a far-red excitable fluorescent GECI, designated iBB-GECO1, that exhibits a range of preferable specifications such as high brightness, large fluorescence response to Ca2+ , and compatibility with multiplexed imaging in mammalian cells.

The need for new coronavirus disease 2019 (COVID-19) therapeutic strategies continues, especially as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants emerge. Zhang and colleagues elegantly engineered a mutant angiotensin-converting enzyme 2 (ACE2) that competitively binds SARS-CoV-2 spike protein, reduces viral uptake by human lung cells, and ameliorates SARS-CoV-2-induced lung injury in mice expressing human ACE2.

Exosomes are cell-derived nanovesicles involved in regulating intercellular communications. In contrast to conventional nanomedicines, exosomes are characterized by unique advantages for therapeutic development. Despite their major successes in drug delivery, the full potential of exosomes for immunotherapy remains untapped. Herein we designed genetically engineered exosomes featured with surfaced-displayed antibody targeting groups and immunomodulatory proteins. Through genetic fusions with exosomal membrane proteins, Expi293F cell-derived exosomes were armed with monoclonal antibodies specific for human T-cell CD3 and epidermal growth factor receptor (EGFR) as well as immune checkpoint modulators, programmed death 1 (PD-1) and OX40 ligand (OX40L). The resulting genetically engineered multifunctional immune-modulating exosomes (GEMINI-Exos) can not only redirect and activate T cells toward killing EGFR-positive triple negative breast cancer (TNBC) cells but also elicit robust anti-cancer immunity, giving rise to highly potent inhibition against established TNBC tumors in mice. GEMINI-Exos represent candidate agents for immunotherapy and may offer a general strategy for generating exosome-based immunotherapeutics with desired functions and properties.

IL13Rα2 is an attractive target due to its overexpression in a variety of cancers and rare expression in healthy tissue, motivating expansion of interleukin 13 (IL13)-based chimeric antigen receptor (CAR) T cell therapy from glioblastoma into systemic malignancies. IL13Rα1, the other binding partner of IL13, is ubiquitously expressed in healthy tissue, raising concerns about the therapeutic window of systemic administration. IL13 mutants with diminished binding affinity to IL13Rα1 were previously generated by structure-guided protein engineering. In this study, two such variants, termed C4 and D7, are characterized for their ability to mediate IL13Rα2-specific response as binding domains for CAR T cells. Despite IL13Rα1 and IL13Rα2 sharing similar binding interfaces on IL13, mutations to IL13 that decrease binding affinity for IL13Rα1 did not drastically change binding affinity for IL13Rα2. Micromolar affinity to IL13Rα1 was sufficient to pacify IL13-mutein CAR T cells in the presence of IL13Rα1-overexpressing cells in vitro. Interestingly, effector activity of D7 CAR T cells, but not C4 CAR T cells, was demonstrated when cocultured with IL13Rα1/IL4Rα-coexpressing cancer cells. While low-affinity interactions with IL13Rα1 did not result in observable toxicities in mice, in vivo biodistribution studies demonstrated that C4 and D7 CAR T cells were better able to traffic away from IL13Rα1+ lung tissue than were wild-type (WT) CAR T cells. These results demonstrate the utility of structure-guided engineering of ligand-based binding domains with appropriate selectivity while validating IL13-mutein CARs with improved selectivity for application to systemic IL13Rα2-expressing malignancies.

SignificanceComputational protein design promises to advance applications in medicine and biotechnology by creating proteins with many new and useful functions. However, new functions require the design of specific and often irregular atom-level geometries, which remains a major challenge. Here, we develop computational methods that design and predict local protein geometries with greater accuracy than existing methods. Then, as a proof of concept, we leverage these methods to design new protein conformations in the enzyme ketosteroid isomerase that change the protein's preference for a key functional residue. Our computational methods are openly accessible and can be applied to the design of other intricate geometries customized for new user-defined protein functions.

Protein switches perform essential roles in many biological processes and are exciting targets for de novo protein design, which aims to produce proteins of arbitrary shape and functionality. However, the biophysical requirements for switch function - multiple conformational states, fine-tuned energetics, and stimuli-responsiveness - pose a formidable challenge for design by computation (or intuition). A variety of methods have been developed toward tackling this challenge, usually taking inspiration from the wealth of sequence and structural information available for naturally occurring protein switches. More recently, modular switches have been designed computationally, and new methods have emerged for sampling unexplored structure space, providing promising new avenues toward the generation of purpose-built switches and de novo signaling systems for cellular 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.

To expand protein's covalent bonding ability, latent bioreactive unnatural amino acids have been designed and genetically encoded into proteins, which react with specific natural amino acid residues through proximity-enabled bioreactivity. The resultant new covalent bonds can be selectively created within and between proteins in vitro, in cells, and in vivo. Offering diverse properties previously unattainable, these covalent linkages have been harnessed to enhance protein properties, to modulate protein function, to probe ligand-receptor binding, to identify elusive protein interactions, and to develop covalent protein drugs. Selective introduction of covalent bonds into proteins is affording novel avenues for biological studies, synthetic biology, and biotherapeutics.

Transgenic expression of bacterial nitroreductase (NTR) enzymes sensitizes eukaryotic cells to prodrugs such as metronidazole (MTZ), enabling selective cell-ablation paradigms that have expanded studies of cell function and regeneration in vertebrates. However, first-generation NTRs required confoundingly toxic prodrug treatments to achieve effective cell ablation, and some cell types have proven resistant. Here we used rational engineering and cross-species screening to develop an NTR variant, NTR 2.0, which exhibits ~100-fold improvement in MTZ-mediated cell-specific ablation efficacy, eliminating the need for near-toxic prodrug treatment regimens. NTR 2.0 therefore enables sustained cell-loss paradigms and ablation of previously resistant cell types. These properties permit enhanced interrogations of cell function, extended challenges to the regenerative capacities of discrete stem cell niches, and novel modeling of chronic degenerative diseases. Accordingly, we have created a series of bipartite transgenic reporter/effector resources to facilitate dissemination of NTR 2.0 to the research community.

Adenosine deaminases acting on RNA (ADARs) can be repurposed to enable programmable RNA editing, however their exogenous delivery leads to transcriptome-wide off-targeting, and additionally, enzymatic activity on certain RNA motifs, especially those flanked by a 5' guanosine is very low thus limiting their utility as a transcriptome engineering toolset. Towards addressing these issues, we first performed a novel deep mutational scan of the ADAR2 deaminase domain, directly measuring the impact of every amino acid substitution across 261 residues, on RNA editing. This enabled us to create a domain-wide mutagenesis map while also revealing a novel hyperactive variant with improved enzymatic activity at 5'-GAN-3' motifs. As overexpression of ADAR enzymes, especially hyperactive variants, can lead to significant transcriptome-wide off-targeting, we next engineered a split-ADAR2 deaminase which resulted in >100-fold more specific RNA editing as compared to full-length deaminase overexpression. Taken together, we anticipate this systematic engineering of the ADAR2 deaminase domain will enable broader utility of the ADAR toolset for RNA biotechnology applications.

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.

Naturally occurring enzymes can be a source of unnatural reactivity that can be molded by directed evolution to generate efficient biocatalysts with valuable activities. Owing to the lack of exploitable stereocontrol elements in synthetic systems, steering the absolute and relative stereochemistry of free-radical processes is notoriously difficult in asymmetric catalysis. Inspired by the innate redox properties of first-row transition-metal cofactors, we repurposed cytochromes P450 to catalyze stereoselective atom-transfer radical cyclization. A set of metalloenzymes was engineered to impose substantial stereocontrol over the radical addition step and the halogen rebound step in these unnatural processes, allowing enantio- and diastereodivergent radical catalysis. This evolvable metalloenzyme platform represents a promising solution to tame fleeting radical intermediates for asymmetric catalysis.

The predominant approach for antibody generation remains animal immunization, which can yield exceptionally selective and potent antibody clones owing to the powerful evolutionary process of somatic hypermutation. However, animal immunization is inherently slow, not always accessible and poorly compatible with many antigens. Here, we describe 'autonomous hypermutation yeast surface display' (AHEAD), a synthetic recombinant antibody generation technology that imitates somatic hypermutation inside engineered yeast. By encoding antibody fragments on an error-prone orthogonal DNA replication system, surface-displayed antibody repertoires continuously mutate through simple cycles of yeast culturing and enrichment for antigen binding to produce high-affinity clones in as little as two weeks. We applied AHEAD to generate potent nanobodies against the SARS-CoV-2 S glycoprotein, a G-protein-coupled receptor and other targets, offering a template for streamlined antibody generation at large.

Exosomes are cell-derived extracellular vesicles and play important roles in mediating intercellular communications. Due to their unique advantages in transporting a variety of biomolecules, exosomes have been emerging as a new class of nanocarriers with great potential for therapeutic applications. Despite advancements in loading chemotherapeutics and interfering RNAs into exosomes, active incorporation of protein molecules into exosomes remains challenging owing to their distinctive physicochemical properties and/or a lack of knowledge of cargo sorting during exosome biogenesis. Here we report the generation of a novel type of engineered exosomes with actively incorporated membrane proteins or soluble protein cargos, named genetically infused functionally tailored exosomes (GIFTed-Exos). Through genetic fusion with exosome-associated tetraspanin CD9, transmembrane protein CD70 and glucocorticoid-induced tumor necrosis factor receptor family-related ligand (GITRL) could be displayed on exosome surface, resulting in GIFTed-Exos with excellent T-cell co-stimulatory activities. By genetically linking to a CD9-photocleavable protein fusion, fluorescent protein mCherry, apoptosis-inducing protein apoptin, and antioxidant enzyme catalase could be effectively packed into exosomes for light-controlled release. The generated GIFTed-Exos display notable in vitro and in vivo activities for delivering distinct types of protein cargos to target cells. As a possibly general approach, GIFTed-Exos provide new opportunities to create exosomes with new functions and properties for biomedical research.

Exosomes are cell-derived extracellular vesicles and play important roles in mediating intercellular communications. Due to their unique advantages in transporting a variety of biomolecules, exosomes have been emerging as a new class of nanocarriers with great potential for therapeutic applications. Despite advancements in loading chemotherapeutics and interfering RNAs into exosomes, active incorporation of protein molecules into exosomes remains challenging owing to their distinctive physicochemical properties and/or a lack of knowledge of cargo sorting during exosome biogenesis. Here we report the generation of a novel type of engineered exosomes with actively incorporated membrane proteins or soluble protein cargos, named genetically infused functionally tailored exosomes (GIFTed-Exos). Through genetic fusion with exosome-associated tetraspanin CD9, transmembrane protein CD70 and glucocorticoid-induced tumor necrosis factor receptor family-related ligand (GITRL) could be displayed on exosome surface, resulting in GIFTed-Exos with excellent T-cell co-stimulatory activities. By genetically linking to a CD9-photocleavable protein fusion, fluorescent protein mCherry, apoptosis-inducing protein apoptin, and antioxidant enzyme catalase could be effectively packed into exosomes for light-controlled release. The generated GIFTed-Exos display notable in vitro and in vivo activities for delivering distinct types of protein cargos to target cells. As a possibly general approach, GIFTed-Exos provide new opportunities to create exosomes with new functions and properties for biomedical research.

Random conjugations of chemotherapeutics to monoclonal antibodies result in heterogeneous antibody-drug conjugates (ADCs) with suboptimal pharmacological properties. We recently developed a new technology for facile generation of homogeneous ADCs by harnessing human CD38 catalytic domain and its dinucleotide-derived covalent inhibitor, termed ADP-ribosyl cyclase-enabled ADCs (ARC-ADCs). Herein we advance this technology by designing and synthesizing ARC-ADCs with customizable drug-to-antibody ratios (DARs). Through varying numbers and locations of CD38 fused to an antibody targeting human C-type lectin-like molecule-1 (hCLL-1), ARC-ADCs featuring DARs of 2 and 4 were rapidly generated via a single step with cytotoxic monomethyl auristatin F (MMAF) as payloads. In contrast to anti-hCLL-1 ARC-ADC carrying 2 drug molecules, anti-hCLL-1 ARC-ADC with a DAR of 4 shows highly potent activity in killing hCLL-1-positive acute myeloid leukemia (AML) cells both in vitro and in vivo. This work provides novel ADC candidates for combating AML and supports ARC-ADC as a general and versatile approach for producing site-specific ADCs with defined DARs.

Random conjugations of chemotherapeutics to monoclonal antibodies result in heterogeneous antibody-drug conjugates (ADCs) with suboptimal pharmacological properties. We recently developed a new technology for facile generation of homogeneous ADCs by harnessing human CD38 catalytic domain and its dinucleotide-derived covalent inhibitor, termed ADP-ribosyl cyclase-enabled ADCs (ARC-ADCs). Herein we advance this technology by designing and synthesizing ARC-ADCs with customizable drug-to-antibody ratios (DARs). Through varying numbers and locations of CD38 fused to an antibody targeting human C-type lectin-like molecule-1 (hCLL-1), ARC-ADCs featuring DARs of 2 and 4 were rapidly generated via a single step with cytotoxic monomethyl auristatin F (MMAF) as payloads. In contrast to anti-hCLL-1 ARC-ADC carrying 2 drug molecules, anti-hCLL-1 ARC-ADC with a DAR of 4 shows highly potent activity in killing hCLL-1-positive acute myeloid leukemia (AML) cells both in vitro and in vivo. This work provides novel ADC candidates for combating AML and supports ARC-ADC as a general and versatile approach for producing site-specific ADCs with defined DARs.

Genetically introducing novel chemical bonds into proteins provides innovative avenues for biochemical research, protein engineering, and biotherapeutic applications. Recently, latent bioreactive unnatural amino acids (Uaas) have been incorporated into proteins to covalently target natural residues through proximity-enabled reactivity. Aryl fluorosulfate is particularly attractive due to its exceptional biocompatibility and multitargeting capability via sulfur(VI) fluoride exchange (SuFEx) reaction. Thus far, fluorosulfate-l-tyrosine (FSY) is the only aryl fluorosulfate-containing Uaa that has been genetically encoded. FSY has a relatively rigid and short side chain, which restricts the diversity of proteins targetable and the scope of applications. Here we designed and genetically encoded a new latent bioreactive Uaa, fluorosulfonyloxybenzoyl-l-lysine (FSK), in E. coli and mammalian cells. Due to its long and flexible aryl fluorosulfate-containing side chain, FSK was particularly useful in covalently linking protein sites that are unreachable with FSY, both intra- and intermolecularly, in vitro and in live cells. In addition, we created covalent nanobodies that irreversibly bound to epidermal growth factor receptors (EGFR) on cells, with FSK and FSY targeting distinct positions on EGFR to counter potential mutational resistance. Moreover, we established the use of FSK and FSY for genetically encoded chemical cross-linking to capture elusive enzyme-substrate interactions in live cells, allowing us to target residues aside from Cys and to cross-link at the binding periphery. FSK complements FSY to expand target diversity and versatility. Together, they provide a powerful, genetically encoded, latent bioreactive SuFEx system for creating covalent bonds in diverse proteins in vitro and in vivo, which will be widely useful for biological research and applications.

The adoptive transfer of T cells that are engineered to express chimeric antigen receptors (CARs) has shown remarkable success in treating B cell malignancies but only limited efficacy against other cancer types, especially solid tumours. Compared with haematological diseases, solid tumours present a unique set of challenges, including a lack of robustly expressed, tumour-exclusive antigen targets as well as highly immunosuppressive and metabolically challenging tumour microenvironments that limit treatment safety and efficacy. Here, we review protein- and cell-engineering strategies that seek to overcome these obstacles and produce next-generation T cells with enhanced tumour specificity and sustained effector function for the treatment of solid malignancies.

Ligands can induce G protein-coupled receptors (GPCRs) to adopt a myriad of conformations, many of which play critical roles in determining the activation of specific signaling cascades associated with distinct functional and behavioral consequences. For example, the 5-hydroxytryptamine 2A receptor (5-HT2AR) is the target of classic hallucinogens, atypical antipsychotics, and psychoplastogens. However, currently available methods are inadequate for directly assessing 5-HT2AR conformation both in vitro and in vivo. Here, we developed psychLight, a genetically encoded fluorescent sensor based on the 5-HT2AR structure. PsychLight detects behaviorally relevant serotonin release and correctly predicts the hallucinogenic behavioral effects of structurally similar 5-HT2AR ligands. We further used psychLight to identify a non-hallucinogenic psychedelic analog, which produced rapid-onset and long-lasting antidepressant-like effects after a single administration. The advent of psychLight will enable in vivo detection of serotonin dynamics, early identification of designer drugs of abuse, and the development of 5-HT2AR-dependent non-hallucinogenic therapeutics.

The ability to design functional sequences and predict effects of variation is central to protein engineering and biotherapeutics. State-of-art computational methods rely on models that leverage evolutionary information but are inadequate for important applications where multiple sequence alignments are not robust. Such applications include the prediction of variant effects of indels, disordered proteins, and the design of proteins such as antibodies due to the highly variable complementarity determining regions. We introduce a deep generative model adapted from natural language processing for prediction and design of diverse functional sequences without the need for alignments. The model performs state-of-art prediction of missense and indel effects and we successfully design and test a diverse 105-nanobody library that shows better expression than a 1000-fold larger synthetic library. Our results demonstrate the power of the alignment-free autoregressive model in generalizing to regions of sequence space traditionally considered beyond the reach of prediction and design.

The randomization and screening of combinatorial DNA libraries is a powerful technique for understanding sequence-function relationships and optimizing biosynthetic pathways. Although it can be difficult to predict a priori which sequence combinations encode functional units, it is often possible to omit undesired combinations that inflate library size and screening effort. However, defined library generation is difficult when a complex scan through sequence space is needed. To overcome this challenge, we designed a hybrid valve- and droplet-based microfluidic system that deterministically assembles DNA parts in picoliter droplets, reducing reagent consumption and bias. Using this system, we built a combinatorial library encoding an engineered histidine kinase (HK) based on bacterial CpxA. Our library encodes designed transmembrane (TM) domains that modulate the activity of the cytoplasmic domain of CpxA and variants of the structurally distant "S helix" located near the catalytic domain. We find that the S helix sets a basal activity further modulated by the TM domain. Surprisingly, we also find that a given TM motif can elicit opposing effects on the catalytic activity of different S-helix variants. We conclude that the intervening HAMP domain passively transmits signals and shapes the signaling response depending on subtle changes in neighboring domains. This flexibility engenders a richness in functional outputs as HKs vary in response to changing evolutionary pressures.

The randomization and screening of combinatorial DNA libraries is a powerful technique for understanding sequence-function relationships and optimizing biosynthetic pathways. Although it can be difficult to predict a priori which sequence combinations encode functional units, it is often possible to omit undesired combinations that inflate library size and screening effort. However, defined library generation is difficult when a complex scan through sequence space is needed. To overcome this challenge, we designed a hybrid valve- and droplet-based microfluidic system that deterministically assembles DNA parts in picoliter droplets, reducing reagent consumption and bias. Using this system, we built a combinatorial library encoding an engineered histidine kinase (HK) based on bacterial CpxA. Our library encodes designed transmembrane (TM) domains that modulate the activity of the cytoplasmic domain of CpxA and variants of the structurally distant "S helix" located near the catalytic domain. We find that the S helix sets a basal activity further modulated by the TM domain. Surprisingly, we also find that a given TM motif can elicit opposing effects on the catalytic activity of different S-helix variants. We conclude that the intervening HAMP domain passively transmits signals and shapes the signaling response depending on subtle changes in neighboring domains. This flexibility engenders a richness in functional outputs as HKs vary in response to changing evolutionary pressures.

De novo protein design offers the opportunity to test our understanding of how metalloproteins perform difficult transformations. Attaining high-resolution structural information is critical to understanding how such designs function. There have been many successes in the design of porphyrin-binding proteins; however, crystallographic characterization has been elusive, limiting what can be learned from such studies as well as the extension to new functions. Moreover, formation of highly oxidizing high-valent intermediates poses design challenges that have not been previously implemented: (1) purposeful design of substrate/oxidant access to the binding site and (2) limiting deleterious oxidation of the protein scaffold. Here we report the first crystallographically characterized porphyrin-binding protein that was programmed to not only bind a synthetic Mn-porphyrin but also maintain binding site access to form high-valent oxidation states. We explicitly designed a binding site with accessibility to dioxygen units in the open coordination site of the Mn center. In solution, the protein is capable of accessing a high-valent Mn(V)-oxo species which can transfer an O atom to a thioether substrate. The crystallographic structure is within 0.6 Å of the design and indeed contained an aquo ligand with a second water molecule stabilized by hydrogen bonding to a Gln side chain in the active site, offering a structural explanation for the observed reactivity.