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Golden Gate assembly (GGA) can seamlessly generate full-length genes from DNA fragments. In principle, GGA could be used to design combinatorial mutation libraries for protein engineering, but creating accurate, complex, and cost-effective libraries has been challenging. We present GGAssembler, a graph-theoretical method for economical design of DNA fragments that assemble a combinatorial library that encodes any desired diversity. We used GGAssembler for one-pot in vitro assembly of camelid antibody libraries comprising >10 5 variants with DNA costs <0.007$ per variant and dropping significantly with increased library complexity. >93% of the desired variants were present in the assembly product and >99% were represented within the expected order of magnitude as verified by deep sequencing. The GGAssembler workflow is, therefore, an accurate approach for generating complex variant libraries that may drastically reduce costs and accelerate discovery and optimization of antibodies, enzymes and other proteins. The workflow is accessible through a Google Colab notebook at https://github.com/Fleishman-Lab/GGAssembler., (© 2024 The Author(s). Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Almost all attempts to date at gene therapy approaches for monogenetic disease have used the amino acid sequences of the natural protein. In the current study, we use a designed, thermostable form of glucocerebrosidase (GCase), the enzyme defective in Gaucher disease (GD), to attempt to alleviate neurological symptoms in a GD mouse that models type 3 disease, i.e. the chronic neuronopathic juvenile subtype. Upon injection of an AAVrh10 (adeno-associated virus, serotype rh10) vector containing the designed GCase (dGCase) into the left lateral ventricle of Gba -/- ;Gba tg mice, a significant improvement in body weight and life-span was observed, compared to injection of the same mouse with the wild type enzyme (wtGCase). Moreover, a reduction in levels of glucosylceramide (GlcCer), and an increase in levels of GCase activity were seen in the right hemisphere of Gba -/- ;Gba tg mice, concomitantly with a significant improvement in motor function, reduction of neuroinflammation and a reduction in mRNA levels of various genes shown previously to be elevated in the brain of mouse models of neurological forms of GD. Together, these data pave the way for the possible use of modified proteins in gene therapy for lysosomal storage diseases and other monogenetic disorders., (© 2024. The Author(s).)

Mutations in protein active sites can dramatically improve function. The active site, however, is densely packed and extremely sensitive to mutations. Therefore, some mutations may only be tolerated in combination with others in a phenomenon known as epistasis. Epistasis reduces the likelihood of obtaining improved functional variants and dramatically slows natural and lab evolutionary processes. Research has shed light on the molecular origins of epistasis and its role in shaping evolutionary trajectories and outcomes. In addition, sequence- and AI-based strategies that infer epistatic relationships from mutational patterns in natural or experimental evolution data have been used to design functional protein variants. In recent years, combinations of such approaches and atomistic design calculations have successfully predicted highly functional combinatorial mutations in active sites. These were used to design thousands of functional active-site variants, demonstrating that, while our understanding of epistasis remains incomplete, some of the determinants that are critical for accurate design are now sufficiently understood. We conclude that the space of active-site variants that has been explored by evolution may be expanded dramatically to enhance natural activities or discover new ones. Furthermore, design opens the way to systematically exploring sequence and structure space and mutational impacts on function, deepening our understanding and control over protein activity., Competing Interests: Competing interests statement:R.L.-S. and S.J.F. are named inventors on patents relating to methods and designs described in the manuscript, and S.J.F. consults on the application of protein design methods.

The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calculations, as well as machine learning tools, have dramatically improved protein engineering and design. In this Review, we discuss how these methods have enabled the design of increasingly complex structures and therapeutically relevant activities. Additionally, protein optimization methods have improved the stability and activity of complex eukaryotic proteins. Thanks to their increased reliability, computational design methods have been applied to improve therapeutics and enzymes for green chemistry and have generated vaccine antigens, antivirals and drug-delivery nano-vehicles. Moreover, the high success of design methods reflects an increased understanding of basic rules that govern the relationships among protein sequence, structure and function. However, de novo design is still limited mostly to α-helix bundles, restricting its potential to generate sophisticated enzymes and diverse protein and small-molecule binders. Designing complex protein structures is a challenging but necessary next step if we are to realize our objective of generating new-to-nature activities., (© 2024. Springer Nature Limited.)

Plasmodium falciparum reticulocyte-binding protein homolog 5 (RH5) is a leading blood-stage malaria vaccine antigen target, currently in a phase 2b clinical trial as a full-length soluble protein/adjuvant vaccine candidate called RH5.1/Matrix-M. We identify that disordered regions of the full-length RH5 molecule induce non-growth inhibitory antibodies in human vaccinees and that a re-engineered and stabilized immunogen (including just the alpha-helical core of RH5) induces a qualitatively superior growth inhibitory antibody response in rats vaccinated with this protein formulated in Matrix-M adjuvant. In parallel, bioconjugation of this immunogen, termed "RH5.2," to hepatitis B surface antigen virus-like particles (VLPs) using the "plug-and-display" SpyTag-SpyCatcher platform technology also enables superior quantitative antibody immunogenicity over soluble protein/adjuvant in vaccinated mice and rats. These studies identify a blood-stage malaria vaccine candidate that may improve upon the current leading soluble protein vaccine candidate RH5.1/Matrix-M. The RH5.2-VLP/Matrix-M vaccine candidate is now under evaluation in phase 1a/b clinical trials., Competing Interests: Declaration of interests S.J.D. is an inventor on patent applications relating to RH5 malaria vaccines and antibodies, is a co-founder of and shareholder in SpyBiotech, and has been a consultant to GSK on malaria vaccines. A.M.M. has been a consultant to GSK on malaria vaccines, has an immediate family member who is an inventor on patent applications relating to RH5 malaria vaccines and antibodies, and is a co-founder of and shareholder in SpyBiotech. M.R.H. is an inventor on patents relating to peptide targeting via spontaneous amide bond formation and is a co-founder of and shareholder in SpyBiotech. S.B. is an inventor on patent applications relating to vaccines made using spontaneous amide bond formation and is a co-founder of, shareholder in, and employee of SpyBiotech. J.J. is an inventor on patent applications relating to vaccines made using spontaneous amide bond formation and is a co-founder of and shareholder in SpyBiotech. R.A.D. is an inventor on patent applications relating to vaccines made using spontaneous amide bond formation and shareholder in SpyBiotech. L.D.W.K., J.R.B., D.Q., A.M.L., S.E.S., B.G.W., K. McHugh, I.C., S.J.F., and D.P. are inventors on patent applications relating to RH5 malaria vaccines and/or antibodies., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Membrane proteins play critical physiological roles as receptors, channels, pumps, and transporters. Despite their importance, however, low expression levels often hamper the experimental characterization of membrane proteins. We present an automated and web-accessible design algorithm called mPROSS (https://mPROSS.weizmann.ac.il), which uses phylogenetic analysis and an atomistic potential, including an empirical lipophilicity scale, to improve native-state energy. As a stringent test, we apply mPROSS to the Kv1.2-Kv2.1 paddle chimera voltage-gated potassium channel. Four designs, encoding 9-26 mutations relative to the parental channel, were functional and maintained potassium-selective permeation and voltage dependence in Xenopus oocytes with up to 14-fold increase in whole-cell current densities. Additionally, single-channel recordings reveal no significant change in the channel-opening probability nor in unitary conductance, indicating that functional expression levels increase without impacting the activity profile of individual channels. Our results suggest that the expression levels of other dynamic channels and receptors may be enhanced through one-shot design calculations., (© 2024 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Conventional methods for humanizing animal-derived antibodies involve grafting their complementarity-determining regions onto homologous human framework regions. However, this process can substantially lower antibody stability and antigen-binding affinity, and requires iterative mutational fine-tuning to recover the original antibody properties. Here we report a computational method for the systematic grafting of animal complementarity-determining regions onto thousands of human frameworks. The method, which we named CUMAb (for computational human antibody design; available at http://CUMAb.weizmann.ac.il ), starts from an experimental or model antibody structure and uses Rosetta atomistic simulations to select designs by energy and structural integrity. CUMAb-designed humanized versions of five antibodies exhibited similar affinities to those of the parental animal antibodies, with some designs showing marked improvement in stability. We also show that (1) non-homologous frameworks are often preferred to highest-homology frameworks, and (2) several CUMAb designs that differ by dozens of mutations and that use different human frameworks are functionally equivalent., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Albumin is the most abundant protein in the blood serum of mammals and has essential carrier and physiological roles. Albumins are also used in a wide variety of molecular and cellular experiments and in the cultivated meat industry. Despite their importance, however, albumins are challenging for heterologous expression in microbial hosts, likely due to 17 conserved intramolecular disulfide bonds. Therefore, albumins used in research and biotechnological applications either derive from animal serum, despite severe ethical and reproducibility concerns, or from recombinant expression in yeast or rice. We use the PROSS algorithm to stabilize human and bovine serum albumins, finding that all are highly expressed in E. coli. Design accuracy is verified by crystallographic analysis of a human albumin variant with 16 mutations. This albumin variant exhibits ligand binding properties similar to those of the wild type. Remarkably, a design with 73 mutations relative to human albumin exhibits over 40 °C improved stability and is stable beyond the boiling point of water. Our results suggest that proteins with many disulfide bridges have the potential to exhibit extreme stability when subjected to design. The designed albumins may be used to make economical, reproducible, and animal-free reagents for molecular and cell biology. They also open the way to high-throughput screening to study and enhance albumin carrier properties., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: O.K. and S.J.F. are named inventors in a patent application filed by Weizmann Institute of Science on the stabilized albumin variants. SJF is a paid consultant to companies that apply protein design algorithms., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Acid-β-glucosidase (GCase, EC3.2.1.45), the lysosomal enzyme which hydrolyzes the simple glycosphingolipid, glucosylceramide (GlcCer), is encoded by the GBA1 gene. Biallelic mutations in GBA1 cause the human inherited metabolic disorder, Gaucher disease (GD), in which GlcCer accumulates, while heterozygous GBA1 mutations are the highest genetic risk factor for Parkinson's disease (PD). Recombinant GCase (e.g., Cerezyme ® ) is produced for use in enzyme replacement therapy for GD and is largely successful in relieving disease symptoms, except for the neurological symptoms observed in a subset of patients. As a first step toward developing an alternative to the recombinant human enzymes used to treat GD, we applied the PROSS stability-design algorithm to generate GCase variants with enhanced stability. One of the designs, containing 55 mutations compared to wild-type human GCase, exhibits improved secretion and thermal stability. Furthermore, the design has higher enzymatic activity than the clinically used human enzyme when incorporated into an AAV vector, resulting in a larger decrease in the accumulation of lipid substrates in cultured cells. Based on stability-design calculations, we also developed a machine learning-based approach to distinguish benign from deleterious (i.e., disease-causing) GBA1 mutations. This approach gave remarkably accurate predictions of the enzymatic activity of single-nucleotide polymorphisms in the GBA1 gene that are not currently associated with GD or PD. This latter approach could be applied to other diseases to determine risk factors in patients carrying rare mutations., (© 2023 The Authors. The FEBS Journal published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Controlled degradation of proteins is necessary for ensuring their abundance and sustaining a healthy and accurately functioning proteome. One of the degradation routes involves the uncapped 20S proteasome, which cleaves proteins with a partially unfolded region, including those that are damaged or contain intrinsically disordered regions. This degradation route is tightly controlled by a recently discovered family of proteins named Catalytic Core Regulators (CCRs). Here, we show that CCRs function through an allosteric mechanism, coupling the physical binding of the PSMB4 β-subunit with attenuation of the complex's three proteolytic activities. In addition, by dissecting the structural properties that are required for CCR-like function, we could recapitulate this activity using a designed protein that is half the size of natural CCRs. These data uncover an allosteric path that does not involve the proteasome's enzymatic subunits but rather propagates through the non-catalytic subunit PSMB4. This way of 20S proteasome-specific attenuation opens avenues for decoupling the 20S and 26S proteasome degradation pathways as well as for developing selective 20S proteasome inhibitors., (© 2023. The Author(s).)

Mutations in a protein active site can lead to dramatic and useful changes in protein activity. The active site, however, is sensitive to mutations due to a high density of molecular interactions, substantially reducing the likelihood of obtaining functional multipoint mutants. We introduce an atomistic and machine-learning-based approach, called high-throughput Functional Libraries (htFuncLib), that designs a sequence space in which mutations form low-energy combinations that mitigate the risk of incompatible interactions. We apply htFuncLib to the GFP chromophore-binding pocket, and, using fluorescence readout, recover >16,000 unique designs encoding as many as eight active-site mutations. Many designs exhibit substantial and useful diversity in functional thermostability (up to 96 °C), fluorescence lifetime, and quantum yield. By eliminating incompatible active-site mutations, htFuncLib generates a large diversity of functional sequences. We envision that htFuncLib will be used in one-shot optimization of activity in enzymes, binders, and other proteins., (© 2023. The Author(s).)

Until now, membrane-protein stabilization has relied on iterations of mutations and screening. We now validate a one-step algorithm, mPROSS, for stabilizing membrane proteins directly from an AlphaFold2 model structure. Applied to the lipid-generating enzyme, ceramide synthase, 37 designed mutations lead to a more stable form of human CerS2. Together with molecular dynamics simulations, we propose a pathway by which substrates might be delivered to the ceramide synthases., (© 2023. The Author(s).)

Several methods have been developed to explore interactions among water-soluble proteins or regions of proteins. However, techniques to target transmembrane domains (TMDs) have not been examined thoroughly despite their importance. Here, we developed a computational approach to design sequences that specifically modulate protein-protein interactions in the membrane. To illustrate this method, we demonstrated that BclxL can interact with other members of the B cell lymphoma 2 (Bcl2) family through the TMD and that these interactions are required for BclxL control of cell death. Next, we designed sequences that specifically recognize and sequester the TMD of BclxL. Hence, we were able to prevent BclxL intramembrane interactions and cancel its antiapoptotic effect. These results advance our understanding of protein-protein interactions in membranes and provide a means to modulate them. Moreover, the success of our approach may trigger the development of a generation of inhibitors targeting interactions between TMDs.

The generation of enantiodivergent biocatalysts for C-H oxyfunctionalizations is ever more important in modern synthetic chemistry. Here, we have applied the FuncLib algorithm based on phylogenetic and Rosetta calculations to design a diverse repertoire of active, stable, and enantiodivergent fungal peroxygenases. 24 designs, each carrying 4-5 mutations in the catalytic core, were expressed functionally in yeast and benchmarked against characteristic model compounds. Several designs were active and stable in a range of temperature and pH, displaying unprecedented enantiodivergence, changing regioselectivity from alkyl to aromatic hydroxylation, and increasing catalytic efficiencies up to 10-fold, with 15-fold improvements in total turnover numbers over the parental enzyme. We find that this dramatic functional divergence stems from beneficial epistasis among the mutations and an extensive reorganization of the heme channel. Our work demonstrates that FuncLib can rapidly design highly functional libraries enriched in enantioselective peroxygenases not seen in nature for a range of biotechnological applications.

The design of structurally diverse enzymes is constrained by long-range interactions that are necessary for accurate folding. We introduce an atomistic and machine learning strategy for the combinatorial assembly and design of enzymes (CADENZ) to design fragments that combine with one another to generate diverse, low-energy structures with stable catalytic constellations. We applied CADENZ to endoxylanases and used activity-based protein profiling to recover thousands of structurally diverse enzymes. Functional designs exhibit high active-site preorganization and more stable and compact packing outside the active site. Implementing these lessons into CADENZ led to a 10-fold improved hit rate and more than 10,000 recovered enzymes. This design-test-learn loop can be applied, in principle, to any modular protein family, yielding huge diversity and general lessons on protein design principles.

White-rot fungi secrete an impressive repertoire of high-redox potential laccases (HRPLs) and peroxidases for efficient oxidation and utilization of lignin. Laccases are attractive enzymes for the chemical industry due to their broad substrate range and low environmental impact. Since expression of functional recombinant HRPLs is challenging, however, iterative-directed evolution protocols have been applied to improve their expression, activity, and stability. We implement a rational, stabilize-and-diversify strategy to two HRPLs that we could not functionally express. First, we use the PROSS stability-design algorithm to allow functional expression in yeast. Second, we use the stabilized enzymes as starting points for FuncLib active-site design to improve their activity and substrate diversity. Four of the FuncLib-designed HRPLs and their PROSS progenitor exhibit substantial diversity in reactivity profiles against high-redox potential substrates, including lignin monomers. Combinations of 3-4 subtle mutations that change the polarity, solvation, and sterics of the substrate-oxidation site result in orders of magnitude changes in reactivity profiles. These stable and versatile HRPLs are a step toward generating an effective lignin-degrading consortium of enzymes that can be secreted from yeast. The stabilize-and-diversify strategy can be applied to other challenging enzyme families to study and expand the utility of natural enzymes., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Blocking the interaction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with its angiotensin-converting enzyme 2 (ACE2) receptor was proved to be an effective therapeutic option. Various protein binders as well as monoclonal antibodies that effectively target the receptor-binding domain (RBD) of SARS-CoV-2 to prevent interaction with ACE2 were developed. The emergence of SARS-CoV-2 variants that accumulate alterations in the RBD can severely affect the efficacy of such immunotherapeutic agents, as is indeed the case with Omicron that resists many of the previously isolated monoclonal antibodies. Here, we evaluate an ACE2-based immunoadhesin that we have developed early in the pandemic against some of the recent variants of concern (VoCs), including the Delta and the Omicron variants. We show that our ACE2-immunoadhesin remains effective in neutralizing these variants, suggesting that immunoadhesin-based immunotherapy is less prone to escape by the virus and has a potential to remain effective against future VoCs., Competing Interests: The Weizmann Institute has filed for a patent for the ACE2mod-Fc immunoadhesin., (© 2022 The Authors.)

Over half the proteins in the E. coli cytoplasm form homo or hetero-oligomeric structures. Experimentally determined structures are often considered in determining a protein's oligomeric state, but static structures miss the dynamic equilibrium between different quaternary forms. The problem is exacerbated in homo-oligomers, where the oligomeric states are challenging to characterize. Here, we re-evaluated the oligomeric state of 17 different bacterial proteins across a broad range of protein concentrations and solutions by native mass spectrometry (MS), mass photometry (MP), size exclusion chromatography (SEC), and small-angle X-ray scattering (SAXS), finding that most exhibit several oligomeric states. Surprisingly, some proteins did not show mass-action driven equilibrium between the oligomeric states. For approximately half the proteins, the predicted oligomeric forms described in publicly available databases underestimated the complexity of protein quaternary structures in solution. Conversely, AlphaFold multimer provided an accurate description of the potential multimeric states for most proteins, suggesting that it could help resolve uncertainties on the solution state of many proteins., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Recent advances in protein-design methodology have led to a dramatic increase in reliability and scale. With these advances, dozens and even thousands of designed proteins are automatically generated and screened. Nevertheless, the success rate, particularly in design of functional proteins, is low and fundamental goals such as reliable de novo design of efficient enzymes remain beyond reach. Experimental analyses have consistently indicated that a major reason for design failure is inaccuracy and misfolding relative to the design conception. To address this challenge, we describe complementary methods to diagnose and ameliorate suboptimal regions in designed proteins: first, we develop a Rosetta atomistic computational mutation scanning approach to detect energetically suboptimal positions in designs (available on a web server https://pSUFER.weizmann.ac.il); second, we demonstrate that AlphaFold2 ab initio structure prediction flags regions that may misfold in designed enzymes and binders; and third, we focus FuncLib design calculations on suboptimal positions in a previously designed low-efficiency enzyme, improving its catalytic efficiency by 330-fold. Furthermore, applied to a de novo designed protein that exhibited limited stability, the same approach markedly improved stability and expressibility. Thus, foldability analysis and enhancement may dramatically increase the success rate in design of functional proteins., (© 2022 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Imaging of gene-expression patterns in live animals is difficult to achieve with fluorescent proteins because tissues are opaque to visible light. Imaging of transgene expression with magnetic resonance imaging (MRI), which penetrates to deep tissues, has been limited by single reporter visualization capabilities. Moreover, the low-throughput capacity of MRI limits large-scale mutagenesis strategies to improve existing reporters. Here we develop an MRI system, called GeneREFORM, comprising orthogonal reporters for two-color imaging of transgene expression in deep tissues. Starting from two promiscuous deoxyribonucleoside kinases, we computationally designed highly active, orthogonal enzymes ('reporter genes') that specifically phosphorylate two MRI-detectable synthetic deoxyribonucleosides ('reporter probes'). Systemically administered reporter probes exclusively accumulate in cells expressing the designed reporter genes, and their distribution is displayed as pseudo-colored MRI maps based on dynamic proton exchange for noninvasive visualization of transgene expression. We envision that future extensions of GeneREFORM will pave the way to multiplexed deep-tissue mapping of gene expression in live animals., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

The ability to alter the genomes of living cells is key to understanding how genes influence the functions of organisms and will be critical to modify living systems for useful purposes. However, this promise has long been limited by the technical challenges involved in genetic engineering. Recent advances in gene editing have bypassed some of these challenges but they are still far from ideal. Here we use FuncLib to computationally design Cas9 enzymes with substantially higher donor-independent editing activities. We use genetic circuits linked to cell survival in yeast to quantify Cas9 activity and discover synergistic interactions between engineered regions. These hyperactive Cas9 variants function efficiently in mammalian cells and introduce larger and more diverse pools of insertions and deletions into targeted genomic regions, providing tools to enhance and expand the possible applications of CRISPR-based gene editing., (© 2022. The Author(s).)

De novo-designed receptor transmembrane domains (TMDs) present opportunities for precise control of cellular receptor functions. We developed a de novo design strategy for generating programmed membrane proteins (proMPs): single-pass α-helical TMDs that self-assemble through computationally defined and crystallographically validated interfaces. We used these proMPs to program specific oligomeric interactions into a chimeric antigen receptor (CAR) that we expressed in mouse primary T cells and found that both in vitro CAR T cell cytokine release and in vivo antitumor activity scaled linearly with the oligomeric state encoded by the receptor TMD, from monomers up to tetramers. All programmed CARs stimulated substantially lower T cell cytokine release relative to the commonly used CD28 TMD, which we show elevated cytokine release through lateral recruitment of the endogenous T cell costimulatory receptor CD28. Precise design using orthogonal and modular TMDs thus provides a new way to program receptor structure and predictably tune activity for basic or applied synthetic biology., Competing Interests: AE, NC, JW, MC, MC Author is an inventor on a related patent WO2021229581A2, AD, JN, RT, RC, MJ No competing interests declared, SF Reviewing editor, eLife, (© 2022, Elazar et al.)

Botulinum neurotoxin type E (BoNT/E), the fastest acting toxin of all BoNTs, cleaves the 25 kDa synaptosomal-associated protein (SNAP-25) in motor neurons, leading to flaccid paralysis. The specific detection and quantification of the BoNT/E-cleaved SNAP-25 neoepitope can facilitate the development of cell-based assays for the characterization of anti-BoNT/E antibody preparations. In order to isolate highly specific monoclonal antibodies suitable for the in vitro immuno-detection of the exposed neoepitope, mice and rabbits were immunized with an eight amino acid peptide composed of the C-terminus of the cleaved SNAP-25. The immunized rabbits developed a specific and robust polyclonal antibody response, whereas the immunized mice mostly demonstrated a weak antibody response that could not discriminate between the two forms of SNAP-25. An immune scFv phage-display library was constructed from the immunized rabbits and a panel of antibodies was isolated. The sequence alignment of the isolated clones revealed high similarity between both heavy and light chains with exceptionally short HCDR3 sequences. A chimeric scFv-Fc antibody was further expressed and characterized, exhibiting a selective, ultra-high affinity (pM) towards the SNAP-25 neoepitope. Moreover, this antibody enabled the sensitive detection of cleaved SNAP-25 in BoNT/E treated SiMa cells with no cross reactivity with the intact SNAP-25. Thus, by applying an immunization and selection procedure, we have isolated a novel, specific and high-affinity antibody against the BoNT/E-derived SNAP-25 neoepitope. This novel antibody can be applied in in vitro assays that determine the potency of antitoxin preparations and reduce the use of laboratory animals for these purposes.

Cardio- and cerebrovascular diseases are leading causes of death and disability, resulting in one of the highest socio-economic burdens of any disease type. The discovery of bacterial and human plasminogen activators and their use as thrombolytic drugs have revolutionized treatment of these pathologies. Fibrin-specific agents have an advantage over non-specific factors because of lower rates of deleterious side effects. Specifically, staphylokinase (SAK) is a pharmacologically attractive indirect plasminogen activator protein of bacterial origin that forms stoichiometric noncovalent complexes with plasmin, promoting the conversion of plasminogen into plasmin. Here we report a computer-assisted re-design of the molecular surface of SAK to increase its affinity for plasmin. A set of computationally designed SAK mutants was produced recombinantly and biochemically characterized. Screening revealed a pharmacologically interesting SAK mutant with ∼7-fold enhanced affinity toward plasmin, ∼10-fold improved plasmin selectivity and moderately higher plasmin-generating efficiency in vitro . Collectively, the results obtained provide a framework for SAK engineering using computational affinity-design that could pave the way to next-generation of effective, highly selective, and less toxic thrombolytics., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

The overarching goal of computational protein design is to gain complete control over protein structure and function. The majority of sophisticated binders and enzymes, however, are large and exhibit diverse and complex folds that defy atomistic design calculations. Encouragingly, recent strategies that combine evolutionary constraints from natural homologs with atomistic calculations have significantly improved design accuracy. In these approaches, evolutionary constraints mitigate the risk from misfolding and aggregation, focusing atomistic design calculations on a small but highly enriched sequence subspace. Such methods have dramatically optimized diverse proteins, including vaccine immunogens, enzymes for sustainable chemistry, and proteins with therapeutic potential. The new generation of deep learning-based ab initio structure predictors can be combined with these methods to extend the scope of protein design, in principle, to any natural protein of known sequence. We envision that protein engineering will come to rely on completely computational methods to efficiently discover and optimize biomolecular activities., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this article., (Copyright © 2022 Olga Khersonsky and Sarel J. Fleishman.)

White-rot fungi secrete a repertoire of high-redox potential oxidoreductases to efficiently decompose lignin. Of these enzymes, versatile peroxidases (VPs) are the most promiscuous biocatalysts. VPs are attractive enzymes for research and industrial use but their recombinant production is extremely challenging. To date, only a single VP has been structurally characterized and optimized for recombinant functional expression, stability, and activity. Computational enzyme optimization methods can be applied to many enzymes in parallel but they require accurate structures. Here, we demonstrate that model structures computed by deep-learning-based ab initio structure prediction methods are reliable starting points for one-shot PROSS stability-design calculations. Four designed VPs encoding as many as 43 mutations relative to the wildtype enzymes are functionally expressed in yeast, whereas their wildtype parents are not. Three of these designs exhibit substantial and useful diversity in their reactivity profiles and tolerance to environmental conditions. The reliability of the new generation of structure predictors and design methods increases the scale and scope of computational enzyme optimization, enabling efficient discovery and exploitation of the functional diversity in natural enzyme families directly from genomic databases.

Lassa virus (LASV) is a human pathogen, causing substantial morbidity and mortality 1,2 . Similar to other Arenaviridae, it presents a class-I spike complex on its surface that facilitates cell entry. The virus's cellular receptor is matriglycan, a linear carbohydrate that is present on α-dystroglycan 3,4 , but the molecular mechanism that LASV uses to recognize this glycan is unknown. In addition, LASV and other arenaviruses have a unique signal peptide that forms an integral and functionally important part of the mature spike 5-8 ; yet the structure, function and topology of the signal peptide in the membrane remain uncertain 9-11 . Here we solve the structure of a complete native LASV spike complex, finding that the signal peptide crosses the membrane once and that its amino terminus is located in the extracellular region. Together with a double-sided domain-switching mechanism, the signal peptide helps to stabilize the spike complex in its native conformation. This structure reveals that the LASV spike complex is preloaded with matriglycan, suggesting the mechanism of binding and rationalizing receptor recognition by α-dystroglycan-tropic arenaviruses. This discovery further informs us about the mechanism of viral egress and may facilitate the rational design of novel therapeutics that exploit this binding site., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Stabilizing antigenic proteins as vaccine immunogens or diagnostic reagents is a stringent case of protein engineering and design as the exterior surface must maintain recognition by receptor(s) and antigen-specific antibodies at multiple distinct epitopes. This is a challenge, as stability enhancing mutations must be focused on the protein core, whereas successful computational stabilization algorithms typically select mutations at solvent-facing positions. In this study, we report the stabilization of SARS-CoV-2 Wuhan Hu-1 Spike receptor binding domain using a combination of deep mutational scanning and computational design, including the FuncLib algorithm. Our most successful design encodes I358F, Y365W, T430I, and I513L receptor binding domain mutations, maintains recognition by the receptor ACE2 and a panel of different anti-receptor binding domain monoclonal antibodies, is between 1 and 2°C more thermally stable than the original receptor binding domain using a thermal shift assay, and is less proteolytically sensitive to chymotrypsin and thermolysin than the original receptor binding domain. Our approach could be applied to the computational stabilization of a wide range of proteins without requiring detailed knowledge of active sites or binding epitopes. We envision that this strategy may be particularly powerful for cases when there are multiple or unknown binding sites., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Solute-binding proteins (SBPs) have evolved to balance the demands of ligand affinity, thermostability, and conformational change to accomplish diverse functions in small molecule transport, sensing, and chemotaxis. Although the ligand-induced conformational changes that occur in SBPs make them useful components in biosensors, they are challenging targets for protein engineering and design. Here, we have engineered a d-alanine-specific SBP into a fluorescence biosensor with specificity for the signaling molecule d-serine (D-serFS). This was achieved through binding site and remote mutations that improved affinity ( K D = 6.7 ± 0.5 μM), specificity (40-fold increase vs glycine), thermostability ( T m = 79 °C), and dynamic range (∼14%). This sensor allowed measurement of physiologically relevant changes in d-serine concentration using two-photon excitation fluorescence microscopy in rat brain hippocampal slices. This work illustrates the functional trade-offs between protein dynamics, ligand affinity, and thermostability and how these must be balanced to achieve desirable activities in the engineering of complex, dynamic proteins.

In recent decades, antibodies (Abs) have attracted the attention of academia and the biopharmaceutical industry due to their therapeutic properties and versatility in binding a vast spectrum of antigens. Different engineering strategies have been developed for optimizing Ab specificity, efficacy, affinity, stability and production, enabling systematic screening and analysis procedures for selecting lead candidates. This quality assessment is critical but usually demands time-consuming and labor-intensive purification procedures. Here, we harnessed the direct-mass spectrometry (direct-MS) approach, in which the analysis is carried out directly from the crude growth media, for the rapid, structural characterization of designed Abs. We demonstrate that properties such as stability, specificity and interactions with antigens can be defined, without the need for prior purification., (© 2021 Wiley-VCH GmbH.)

Recent progress in structure-prediction methods that rely on deep learning suggests that the atomic structure of almost any protein may soon be predictable directly from its amino acid sequence. This much-awaited revolution was driven by substantial improvements in the reliability of methods for inferring the spatial distances between amino acid pairs from an analysis of homologous sequences. Improved reliability has been accompanied, however, by a reduced ability to detect amino acid relationships that are not due to direct spatial contacts, such as those that arise from protein dynamics or allostery. Given the central importance of dynamics and allostery to protein activity, we argue that an important future advance would extend modeling beyond predicting a single static structure. Here, we briefly review some of the developments that have led to the remarkable recent achievement in structure prediction and speculate what methods and sources of information may be leveraged in the future to develop a modeling framework that addresses protein dynamics and allostery., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

A wide range of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralizing monoclonal antibodies (mAbs) have been reported, most of which target the spike glycoprotein. Therapeutic implementation of these antibodies has been challenged by emerging SARS-CoV-2 variants harboring mutated spike versions. Consequently, re-assessment of previously identified mAbs is of high priority. Four previously selected mAbs targeting non-overlapping epitopes are now evaluated for binding potency to mutated RBD versions, reported to mediate escape from antibody neutralization. In vitro neutralization potencies of these mAbs, and two NTD-specific mAbs, are evaluated against two frequent SARS-CoV-2 variants of concern, the B.1.1.7 Alpha and the B.1.351 Beta. Furthermore, we demonstrate therapeutic potential of three selected mAbs by treatment of K18-human angiotensin-converting enzyme 2 (hACE2) transgenic mice 2 days post-infection with each virus variant. Thus, despite the accumulation of spike mutations, the highly potent MD65 and BL6 mAbs retain their ability to bind the prevalent viral mutants, effectively protecting against B.1.1.7 and B.1.351 variants., Competing Interests: Declaration of interests Patent application for the described antibodies was filed by the Israel Institute for Biological Research. None of the authors declared any additional competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Although it is well-known that limited local mutations of enzymes, such as matrix metalloproteinases (MMPs), may change enzyme activity by orders of magnitude as well as its stability, the completely rational design of proteins is still challenging. These local changes alter the electrostatic potential and thus local electrostatic fields, which impacts the dynamics of water molecules close the protein surface. Here we show by a combined computational design, experimental, and molecular dynamics (MD) study that local mutations have not only a local but also a global effect on the solvent: In the specific case of the matrix metalloprotease MMP14, we found that the nature of local mutations, coupled with surface morphology, have the ability to influence large patches of the water hydrogen-bonding network at the protein surface, which is correlated with stability. The solvent contribution can be experimentally probed via terahertz (THz) spectroscopy, thus opening the door to the exciting perspective of rational protein design in which a systematic tuning of hydration water properties allows manipulation of protein stability and enzymatic activity., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Published by American Chemical Society.)

Glycans decorate the cell surface, secreted glycoproteins and glycolipids, and altered glycans are often found in cancers. Despite their high diagnostic and therapeutic potential, however, glycans are polar and flexible molecules that are quite challenging for the development and design of high-affinity binding antibodies. To understand the mechanisms by which glycan neoantigens are specifically recognized by antibodies, we analyze the biomolecular recognition of the tumor-associated carbohydrate antigen CA19-9 by two distinct antibodies using X-ray crystallography. Despite the potential plasticity of glycans and the very different antigen-binding surfaces presented by the antibodies, both structures reveal an essentially identical extended CA19-9 conformer, suggesting that this conformer's stability selects the antibodies. Starting from the bound structure of one of the antibodies, we use the AbLIFT computational algorithm to design a variant with seven core mutations in the variable domain's light-heavy chain interface that exhibits tenfold improved affinity for CA19-9. The results reveal strategies used by antibodies to specifically recognize glycan antigens and show how automated antibody-optimization methods may be used to enhance the clinical potential of existing antibodies., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The Weizmann Institute of Science and the Tel Aviv University have filed a patent application for the AbLIFT designs., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Recent years have seen a dramatic improvement in protein-design methodology. Nevertheless, most methods demand expert intervention, limiting their widespread adoption. By contrast, the PROSS algorithm for improving protein stability and heterologous expression levels has been successfully applied to a range of challenging enzymes and binding proteins. Here, we benchmark the application of PROSS as a stand-alone tool for protein scientists with no or limited experience in modeling. Twelve laboratories from the Protein Production and Purification Partnership in Europe (P4EU) challenged the PROSS algorithm with 14 unrelated protein targets without support from the PROSS developers. For each target, up to six designs were evaluated for expression levels and in some cases, for thermal stability and activity. In nine targets, designs exhibited increased heterologous expression levels either in prokaryotic and/or eukaryotic expression systems under experimental conditions that were tailored for each target protein. Furthermore, we observed increased thermal stability in nine of ten tested targets. In two prime examples, the human Stem Cell Factor (hSCF) and human Cadherin-Like Domain (CLD12) from the RET receptor, the wild type proteins were not expressible as soluble proteins in E. coli, yet the PROSS designs exhibited high expression levels in E. coli and HEK293 cells, respectively, and improved thermal stability. We conclude that PROSS may improve stability and expressibility in diverse cases, and that improvement typically requires target-specific expression conditions. This study demonstrates the strengths of community-wide efforts to probe the generality of new methods and recommends areas for future research to advance practically useful algorithms for protein science., Competing Interests: Declaration of Competing Interest AG and SJF are named inventors on patents relating to the PROSS method and various designs., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

To enable a sustainable supply of chemicals, novel biotechnological solutions are required that replace the reliance on fossil resources. One potential solution is to utilize tailored biosynthetic modules for the metabolic conversion of CO 2 or organic waste to chemicals and fuel by microorganisms. Currently, it is challenging to commercialize biotechnological processes for renewable chemical biomanufacturing because of a lack of highly active and specific biocatalysts. As experimental methods to engineer biocatalysts are time- and cost-intensive, it is important to establish efficient and reliable computational tools that can speed up the identification or optimization of selective, highly active, and stable enzyme variants for utilization in the biotechnological industry. Here, we review and suggest combinations of effective state-of-the-art software and online tools available for computational enzyme engineering pipelines to optimize metabolic pathways for the biosynthesis of renewable chemicals. Using examples relevant for biotechnology, we explain the underlying principles of enzyme engineering and design and illuminate future directions for automated optimization of biocatalysts for the assembly of synthetic metabolic pathways., Competing Interests: SF is a named inventor on patent filings regarding the PROSS and FuncLib methods and several proteins designed using these tools. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Scherer, Fleishman, Jones, Dandekar and Bencurova.)

Summary: Many natural and designed proteins are only marginally stable limiting their usefulness in research and applications. Recently, we described an automated structure and sequence-based design method, called PROSS, for optimizing protein stability and heterologous expression levels that has since been validated on dozens of proteins. Here, we introduce improvements to the method, workflow and presentation, including more accurate sequence analysis, error handling and automated analysis of the quality of the sequence alignment that is used in design calculations., Availability and Implementation: PROSS2 is freely available for academic use at https://pross.weizmann.ac.il., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Pseudomonas aeruginosa is an opportunistic human pathogen that develops difficult-to-treat biofilms in immunocompromised individuals, cystic fibrosis patients, and in chronic wounds. P. aeruginosa has an arsenal of physiological attributes that enable it to evade standard antibiotic treatments, particularly in the context of biofilms where it grows slowly and becomes tolerant to many drugs. One of its survival strategies involves the production of the redox-active phenazine, pyocyanin, which promotes biofilm development. We previously identified an enzyme, PodA, that demethylated pyocyanin and disrupted P. aeruginosa biofilm development in vitro. Here, we asked if this protein could be used as a potential therapeutic for P. aeruginosa infections together with tobramycin, an antibiotic typically used in the clinic. A major roadblock to answering this question was the poor yield and stability of wild-type PodA purified from standard Escherichia coli overexpression systems. We hypothesized that the insufficient yields were due to poor packing within PodA's obligatory homotrimeric interfaces. We therefore applied the protein design algorithm, AffiLib, to optimize the symmetric core of this interface, resulting in a design that incorporated five mutations leading to a 20-fold increase in protein yield from heterologous expression and purification and a substantial increase in stability to environmental conditions. The addition of the designed PodA with tobramycin led to increased killing of P. aeruginosa cultures under oxic and hypoxic conditions in both the planktonic and biofilm states. This study highlights the potential for targeting extracellular metabolites to assist the control of P. aeruginosa biofilms that tolerate conventional antibiotic treatment., Competing Interests: Competing interest statement: C.M.V., R.L.-S., O.K., S.J.F., and D.K.N. are named inventors on patents filed by Caltech and the Weizmann Institute on the design methods.

The functional sites of many protein families are dominated by diverse backbone regions that lack secondary structure (loops) but fold stably into their functionally competent state. Nevertheless, the design of structured loop regions from scratch, especially in functional sites, has met with great difficulty. We therefore developed an approach, called AbDesign, to exploit the natural modularity of many protein families and computationally assemble a large number of new backbones by combining naturally occurring modular fragments. This strategy yielded large, atomically accurate, and highly efficient proteins, including antibodies and enzymes exhibiting dozens of mutations from any natural protein. The combinatorial backbone-conformation space that can be accessed by AbDesign even for a modestly sized family of homologs may exceed the diversity in the entire PDB, providing the sub-Ångstrom level of control over the positioning of active-site groups that is necessary for obtaining highly active proteins. This manuscript describes how to implement the pipeline using code that is freely available at https://github.com/Fleishman-Lab/AbDesign&#95;for&#95;enzymes., (© 2020 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Our ability to design new or improved biomolecular activities depends on understanding the sequence-function relationships in proteins. The large size and fold complexity of most proteins, however, obscure these relationships, and protein-optimization methods continue to rely on laborious experimental iterations. Recently, a deeper understanding of the roles of stability-threshold effects and biomolecular epistasis in proteins has led to the development of hybrid methods that combine phylogenetic analysis with atomistic design calculations. These methods enable reliable and even single-step optimization of protein stability, expressibility, and activity in proteins that were considered outside the scope of computational design. Furthermore, ancestral-sequence reconstruction produces insights on missing links in the evolution of enzymes and binders that may be used in protein design. Through the combination of phylogenetic and atomistic calculations, the long-standing goal of general computational methods that can be universally applied to study and optimize proteins finally seems within reach., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Many human pathogens use host cell-surface receptors to attach and invade cells. Often, the host-pathogen interaction affinity is low, presenting opportunities to block invasion using a soluble, high-affinity mimic of the host protein. The Plasmodium falciparum reticulocyte-binding protein homolog 5 (RH5) provides an exciting candidate for mimicry: it is highly conserved and its moderate affinity binding to the human receptor basigin (K D  ≥1 μM) is an essential step in erythrocyte invasion by this malaria parasite. We used deep mutational scanning of a soluble fragment of human basigin to systematically characterize point mutations that enhance basigin affinity for RH5 and then used Rosetta to design a variant within the sequence space of affinity-enhancing mutations. The resulting seven-mutation design exhibited 1900-fold higher affinity (K D approximately 1 nM) for RH5 with a very slow binding off rate (0.23 h -1 ) and reduced the effective Plasmodium growth-inhibitory concentration by at least 10-fold compared to human basigin. The design provides a favorable starting point for engineering on-rate improvements that are likely to be essential to reach therapeutically effective growth inhibition., (© 2019 Wiley Periodicals, Inc.)

Stabilization of the metastable envelope glycoprotein (Env) of HIV-1 is hypothesized to improve induction of broadly neutralizing antibodies. We improved the expression yield and stability of the HIV-1 envelope glycoprotein BG505SOSIP.664 gp140 by means of a previously described automated sequence and structure-guided computational thermostabilization approach, PROSS. This combines sequence conservation information with computational assessment of mutant stabilization, thus taking advantage of the extensive natural sequence variation present in HIV-1 Env. PROSS is used to design three gp140 variants with 17-45 mutations relative to the parental construct. One of the designs is experimentally observed to have a fourfold improvement in yield and a 4 °C increment in thermostability. In addition, the designed immunogens have similar antigenicity profiles to the native flexible linker version of wild type, BG505SOSIP.664 gp140 (NFL Wt) to major epitopes targeted by broadly neutralizing antibodies. PROSS eliminates the laborious process of screening many variants for stability and functionality, providing a proof of principle of the method for stabilization and improvement of yield without compromising antigenicity for next generation complex, highly glycosylated vaccine candidates., Competing Interests: Declaration of Competing Interest None declared