Structure-based design of supercharged, highly thermoresistant antibodies

Enhancing Acid Resistance of Aspergillus niger Pectin Lyase through Surface Charge Design for Improved Application in Juice Clarification

Pectin lyases (PNLs) can enhance juice clarity and flavor by degrading pectin in highly esterified fruits, but their inadequate acid resistance leads to rapid activity loss in juice. This study aimed to improve the acid resistance of Aspergillus niger PNL pelA through surface charge design. A modification platform was established by fusing pelA with a protein tag and expressing the fusion enzyme in Escherichia coli. Four single-point mutants were identified to increase the surface charge using computational tools. Moreover, the combined mutant M6 (S514D/S538E) exhibited 99.8% residual activity at pH 3.0. The M6 gene was then integrated into the A. niger genome using a multigene integration system to obtain the recombinant PNL AM6. Notably, AM6 improved the light transmittance of orange juice to 45.3%, which was 8.39 times higher than that of pelA. In conclusion, AM6 demonstrated the best-reported acid resistance, making it a promising candidate for industrial juice clarification.

Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody-Antigen Interactions

This perspective sheds light on the transformative impact of recent computational advancements in the field of protein therapeutics, with a particular focus on the design and development of antibodies. Cutting-edge computational methods have revolutionized our understanding of protein-protein interactions (PPIs), enhancing the efficacy of protein therapeutics in preclinical and clinical settings. Central to these advancements is the application of machine learning and deep learning, which offers unprecedented insights into the intricate mechanisms of PPIs and facilitates precise control over protein functions. Despite these advancements, the complex structural nuances of antibodies pose ongoing challenges in their design and optimization. Our review provides a comprehensive exploration of the latest deep learning approaches, including language models and diffusion techniques, and their role in surmounting these challenges. We also present a critical analysis of these methods, offering insights to drive further progress in this rapidly evolving field. The paper includes practical recommendations for the application of these computational techniques, supplemented with independent benchmark studies. These studies focus on key performance metrics such as accuracy and the ease of program execution, providing a valuable resource for researchers engaged in antibody design and development. Through this detailed perspective, we aim to contribute to the advancement of antibody design, equipping researchers with the tools and knowledge to navigate the complexities of this field.

Assembly Requirements for the Construction of Large-Scale Binary Protein Structures

The precise assembly of multiple biomacromolecules into well-defined structures and materials is of great importance for various biomedical and nanobiotechnological applications. In this study, we investigate the assembly requirements for two-component materials using charged protein nanocages as building blocks. To achieve this, we designed several variants of ferritin nanocages to determine the surface characteristics necessary for the formation of large-scale binary three-dimensional (3D) assemblies. These nanocage variants were employed in protein crystallization experiments and macromolecular crystallography analyses, complemented by computational methods. Through the screening of nanocage variant combinations at various ionic strengths, we identified three essential features for successful assembly: (1) the presence of a favored crystal contact region, (2) the presence of a charged patch not involved in crystal contacts, and (3) sufficient distinctiveness between the nanocages. Surprisingly, the absence of noncrystal contact mediating patches had a detrimental effect on the assemblies, highlighting their unexpected importance. Intriguingly, we observed the formation of not only binary structures but also both negatively and positively charged unitary structures under previously exclusively binary conditions. Overall, our findings will inform future design strategies by providing some design rules, showcasing the utility of supercharging symmetric building blocks in facilitating the assembly of biomacromolecules into large-scale binary 3D assemblies.

Graphene Field Effect Biosensor for Concurrent and Specific Detection of SARS-CoV-2 and Influenza

The SARS-CoV-2 pandemic has highlighted the need for devices capable of carrying out rapid differential detection of viruses that may manifest similar physiological symptoms yet demand tailored treatment plans. Seasonal influenza may be exacerbated by COVID-19 infections, increasing the burden on healthcare systems. In this work, we demonstrate a technology based on liquid-gated graphene field-effect transistors (GFETs), for rapid and ultraprecise sensing and differentiation of influenza and SARS-CoV-2 surface protein. Most distinctively, the device consists of 4 onboard GFETs arranged in a quadruple architecture, where each quarter is functionalized individually (with either antibodies or chemically passivated control) but measured jointly. The sensor platform was tested against a range of concentrations of viral surface proteins from both viruses with the lowest tested and detected concentration at ∼50 ag/mL, or 88 zM for COVID-19 and 227 zM for Flu, which is 5-fold lower than the values reported previously on a similar platform. Unlike the classic real-time polymerase chain reaction test, which has a turnaround time of a few hours, the graphene technology presents an ultrafast response time of ∼10 s even in complex and clinically relevant media such as saliva. Thus, we have developed a multianalyte, highly sensitive, and fault-tolerant technology for rapid diagnostic of contemporary, emerging, and future pandemics.

Structural and oxidative investigation of a recombinant high-yielding fetal hemoglobin mutant

Human fetal hemoglobin (HbF) is an attractive starting protein for developing an effective agent for oxygen therapeutics applications. This requires that HbF can be produced in heterologous systems at high levels and in a homogeneous form. The introduction of negative charges on the surface of the α-chain in HbF can enhance the recombinant production yield of a functional protein in Escherichia coli. In this study, we characterized the structural, biophysical, and biological properties of an HbF mutant carrying four additional negative charges on each α-chain (rHbFα4). The 3D structure of the rHbFα4 mutant was solved with X-ray crystallography at 1.6 Å resolution. Apart from enabling a higher yield in recombinant protein production in E. coli, we observed that the normal DNA cleavage activity of the HbF was significantly lowered, with a four-time reduced rate constant for the rHbFα4 mutant. The oxygen-binding properties of the rHbFα4 mutant were identical to the wild-type protein. No significant difference between the wild-type and rHbFα4 was observed for the investigated oxidation rates (autoxidation and H2O2-mediated ferryl formation). However, the ferryl reduction reaction indicated some differences, which appear to be related to the reaction rates linked to the α-chain.

Crystalline Biohybrid Materials Based on Protein Cages

Highly ordered superstructures of nanomaterials can be synthesized using protein cages as templates for the assembly of inorganic nanoparticles. Here, we describe in detail the creation of these biohybrid materials. The approach involves computational redesign of ferritin cages, followed by recombinant protein production and purification of the new variants. Metal oxide nanoparticles are synthesized inside the surface-charged variants. The composites are assembled using protein crystallization to yield highly ordered superlattices, which are characterized, for example, with small angle X-ray scattering. This protocol provides a detailed and comprehensive account on our newly established strategy for the synthesis of crystalline biohybrid materials.

Analytical Method for Experimental Validation of Computer-Designed Antibody

In the computational design of antibodies, the interaction analysis between target antigen and antibody is an essential process to obtain feedback for validation and optimization of the design. Kinetic and thermodynamic parameters as well as binding affinity (K_D) allow for a more detailed evaluation and understanding of the molecular recognition. In this chapter, we summarize the conventional experimental methods which can calculate K_D value (ELISA, FP), analyze a binding activity to actual cells (FCM), and evaluate the kinetic and thermodynamic parameters (ITC, SPR, BLI), including high-throughput analysis and a recently developed experimental technique.

Antibody stabilization for thermally accelerated deep immunostaining

Antibodies have diverse applications due to their high reaction specificities but are sensitive to denaturation when a higher working temperature is required. We have developed a simple, highly scalable and generalizable chemical approach for stabilizing off-the-shelf antibodies against thermal and chemical denaturation. We demonstrate that the stabilized antibodies (termed SPEARs) can withstand up to 4 weeks of continuous heating at 55 °C and harsh denaturants, and apply our method to 33 tested antibodies. SPEARs enable flexible applications of thermocycling and denaturants to dynamically modulate their binding kinetics, reaction equilibrium, macromolecular diffusivity and aggregation propensity. In particular, we show that SPEARs permit the use of a thermally facilitated three-dimensional immunolabeling strategy (termed ThICK staining), achieving whole mouse brain immunolabeling within 72 h, as well as nearly fourfold deeper penetration with threefold less antibodies in human brain tissue. With faster deep-tissue immunolabeling and broad compatibility with tissue processing and clearing methods without the need for any specialized equipment, we anticipate the wide applicability of ThICK staining with SPEARs for deep immunostaining.

Thermostable antibodies called SPEARs enable rapid immunostaining with improved tissue penetration.

Quantitative regulation of the thermal stability of enveloped virus vaccines by surface charge engineering to prevent the self-aggregation of attachment glycoproteins

The development of thermostable vaccines can relieve the bottleneck of existing vaccines caused by thermal instability and subsequent poor efficacy, which is one of the predominant reasons for the millions of deaths caused by vaccine-preventable diseases. Research into the mechanism of viral thermostability may provide strategies for developing thermostable vaccines. Using Newcastle disease virus (NDV) as model, we identified the negative surface charge of attachment glycoprotein as a novel determinant of viral thermostability. It prevented the temperature-induced aggregation of glycoprotein and subsequent detachment from virion surface. Then structural stability of virion surface was improved and virus could bind to and infect cells efficiently after heat-treatment. Employing the approach of surface charge engineering, thermal stability of NDV and influenza A virus (IAV) vaccines was successfully improved. The increase in the level of vaccine thermal stability was determined by the value-added in the negative surface charge of the attachment glycoprotein. The engineered live and inactivated vaccines could be used efficiently after storage at 37°C for at least 10 and 60 days, respectively. Thus, our results revealed a novel surface-charge-mediated link between HN protein and NDV thermostability, which could be used to design thermal stable NDV and IAV vaccines rationally.

Charge Engineering Improves the Performance of Bst DNA Polymerase Fusions

The charge states of proteins can greatly influence their stabilities and interactions with substrates, and the addition of multiple charges (supercharging) has been shown to be a successful approach for engineering protein stability and function. The addition of a fast-folding fusion domain to the Bacillus stearothermophilus DNA polymerase improved its functionality in isothermal amplification assays, and further charge engineering of this domain has increased both protein stability and diagnostics performance. When combined with mutations that stabilize the core of the protein, the charge-engineered fusion domain leads to the ability to carry out loop-mediated isothermal amplification (LAMP) at temperatures up to 74° C or in the presence of high concentrations of urea, with detection times under 10 min. Adding both positive and negative charges to the fusion domain led to changes in the relative reverse transcriptase and DNA polymerase activities of the polymerase. Overall, the development of a modular fusion domain whose charged surface can be modified at will should prove to be of use in the engineering of other polymerases and, in general, may prove useful for protein stabilization.

Computational Design of Homotetrameric Peptide Bundle Variants Spanning a Wide Range of Charge States

With the ability to design their sequences and structures, peptides can be engineered to realize a wide variety of functionalities and structures. Herein, computational design was used to identify a set of 17 peptides having a wide range of putative charge states but the same tetrameric coiled-coil bundle structure. Calculations were performed to identify suitable locations for ionizable residues (D, E, K, and R) at the bundle's exterior sites, while interior hydrophobic interactions were retained. The designed bundle structures spanned putative charge states of -32 to +32 in units of electron charge. The peptides were experimentally investigated using spectroscopic and scattering techniques. Thermal stabilities of the bundles were investigated using circular dichroism. Molecular dynamics simulations assessed structural fluctuations within the bundles. The cylindrical peptide bundles, 4 nm long by 2 nm in diameter, were covalently linked to form rigid, micron-scale polymers and characterized using transmission electron microscopy. The designed suite of sequences provides a set of readily realized nanometer-scale structures of tunable charge that can also be polymerized to yield rigid-rod polyelectrolytes.

Accelerating therapeutic protein design

Protein structures provide for defined microenvironments that can support complex pharmacological functions, otherwise unachievable by small molecules. The advent of therapeutic proteins has thus greatly broadened the range of manageable disorders. Leveraging the knowledge and recent advances in de novo protein design methods has the prospect of revolutionizing how protein drugs are discovered and developed. This review lays out the main challenges facing therapeutic proteins discovery and development, and how present and future advancements of protein design can accelerate the protein drug pipelines.

NetSolP: predicting protein solubility in Escherichia coli using language models

MOTIVATION

Solubility and expression levels of proteins can be a limiting factor for large-scale studies and industrial production. By determining the solubility and expression directly from the protein sequence, the success rate of wet-lab experiments can be increased.

RESULTS

In this study, we focus on predicting the solubility and usability for purification of proteins expressed in Escherichia coli directly from the sequence. Our model NetSolP is based on deep learning protein language models called transformers and we show that it achieves state-of-the-art performance and improves extrapolation across datasets. As we find current methods are built on biased datasets, we curate existing datasets by using strict sequence-identity partitioning and ensure that there is minimal bias in the sequences.

AVAILABILITY AND IMPLEMENTATION

The predictor and data are available at https://services.healthtech.dtu.dk/service.php?NetSolP and the open-sourced code is available at https://github.com/tvinet/NetSolP-1.0.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

Significantly Improving the Thermostability and Catalytic Efficiency of Streptomyces mobaraenesis Transglutaminase through Combined Rational Design

Streptomyces mobaraenesis transglutaminase has been widely used in food processing. We here significantly improved the catalytic properties of S2P-S23V-Y24N-S199A-K294L (TGm1), a highly stabilized variant of the transglutaminase. First, a virtual proline scan was performed based on folding free energy changes to obtain TGm1 variants with enhanced thermostability. Second, the residues within 15 Å of Cys64 in the enzyme-substrate complex of TGm1 were subjected to virtual saturation mutagenesis to generate the variants with reduced binding free energy and increased activity. After combining the favorable mutations, we obtained the variant FRAPD-TGm1-E28T-A265P-A287P (FRAPD-TGm2), exhibiting 66.9 min of half-life at 60 °C (t_1/2(60 °C)), 67.8 °C of melting temperature (T_m), and 71.8 U/mg of specific activity, which are 2-fold, 2.6 °C, and 43.8% higher than those of FRAPD-TGm1, respectively. At last, to increase the surface negative net charge of FRAPD-TGm2, we introduced the mutations N96E-S144E-N163D-R183E-R208E-K325E, yielding FRAPD-TGm3. The latter's t_1/2(60 °C), T_m, and specific activity were 122.9 min, 68.6 °C, and 83.7 U/mg, which are 83.8%, 0.8 °C, and 16.6% higher than the former, respectively. FRAPD-TGm3 is thus a robust candidate for transglutaminase application.

Design of a Superpositively Charged Enzyme: Human Carbonic Anhydrase II Variant with Ferritin Encapsulation and Immobilization

Supercharged proteins exhibit high solubility and other desirable properties, but no engineered superpositively charged enzymes have previously been made. Superpositively charged variants of proteins such as green fluorescent protein have been efficiently encapsulated within Archaeoglobus fulgidus thermophilic ferritin (AfFtn). Encapsulation by supramolecular ferritin can yield systems with a variety of sequestered cargo. To advance applications in enzymology and green chemistry, we sought a general method for supercharging an enzyme that retains activity and is compatible with AfFtn encapsulation. The zinc metalloenzyme human carbonic anhydrase II (hCAII) is an attractive encapsulation target based on its hydrolytic activity and physiologic conversion of carbon dioxide to bicarbonate. A computationally designed variant of hCAII contains positively charged residues substituted at 19 sites on the protein's surface, resulting in a shift of the putative net charge from -1 to +21. This designed hCAII(+21) exhibits encapsulation within AfFtn without the need for fusion partners or additional reagents. The hCAII(+21) variant retains esterase activity comparable to the wild type and spontaneously templates the assembly of AfFtn 24mers around itself. The AfFtn-hCAII(+21) host-guest complex exhibits both greater activity and thermal stability when compared to hCAII(+21). Upon immobilization on a solid support, AfFtn-hCAII(+21) retains enzymatic activity and exhibits an enhancement of activity at elevated temperatures.

ATP and Tri-Polyphosphate (TPP) Suppress Protein Aggregate Growth by a Supercharging Mechanism

A common strategy to increase aggregation resistance is through rational mutagenesis to supercharge proteins, which leads to high colloidal stability, but often has the undesirable effect of lowering conformational stability. We show this trade-off can be overcome by using small multivalent polyphosphate ions, adenosine triphosphate (ATP) and tripolyphosphate (TPP) as excipients. These ions are equally effective at suppressing aggregation of ovalbumin and bovine serum albumin (BSA) upon thermal stress as monitored by dynamic and static light scattering. Monomer loss kinetic studies, combined with measurements of native state protein–protein interactions and ζ-potentials, indicate the ions reduce aggregate growth by increasing the protein colloidal stability through binding and overcharging the protein. Out of three additional proteins studied, ribonuclease A (RNaseA), α-chymotrypsinogen (α-Cgn), and lysozyme, we only observed a reduction in aggregate growth for RNaseA, although overcharging by the poly-phosphate ions still occurs for lysozyme and α-Cgn. Because the salts do not alter protein conformational stability, using them as excipients could be a promising strategy for stabilizing biopharmaceuticals once the protein structural factors that determine whether multivalent ion binding will increase colloidal stability are better elucidated. Our findings also have biological implications. Recently, it has been proposed that ATP also plays an important role in maintaining intracellular biological condensates and preventing protein aggregation in densely packed cellular environments. We expect electrostatic interactions are a significant factor in determining the stabilizing ability of ATP towards maintaining proteins in non-dispersed states in vivo.

Redesigning an antibody H3 loop by virtual screening of a small library of human germline-derived sequences

The design of superior biologic therapeutics, including antibodies and engineered proteins, involves optimizing their specific ability to bind to disease-related molecular targets. Previously, we developed and applied the Assisted Design of Antibody and Protein Therapeutics (ADAPT) platform for virtual affinity maturation of antibodies (Vivcharuk et al. in PLoS One 12(7):e0181490, 10.1371/journal.pone.0181490, 2017). However, ADAPT is limited to point mutations of hot-spot residues in existing CDR loops. In this study, we explore the possibility of wholesale replacement of the entire H3 loop with no restriction to maintain the parental loop length. This complements other currently published studies that sample replacements for the CDR loops L1, L2, L3, H1 and H2. Given the immense sequence space theoretically available to H3, we focused on the virtual grafting of over 5000 human germline-derived H3 sequences from the IGMT/LIGM database increasing the diversity of the sequence space when compared to using crystalized H3 loop sequences. H3 loop conformations are generated and scored to identify optimized H3 sequences. Experimental testing of high-ranking H3 sequences grafted into the framework of the bH1 antibody against human VEGF-A led to the discovery of multiple hits, some of which had similar or better affinities relative to the parental antibody. In over 75% of the tested designs, the re-designed H3 loop contributed favorably to overall binding affinity. The hits also demonstrated good developability attributes such as high thermal stability and no aggregation. Crystal structures of select re-designed H3 variants were solved and indicated that although some deviations from predicted structures were seen in the more solvent accessible regions of the H3 loop, they did not significantly affect predicted affinity scores.

Resurfacing receptor binding domain of Colicin N to enhance its cytotoxic effect on human lung cancer cells

Colicin N (ColN) is a bacteriocin secreted by Escherichia coli (E. coli) to kill other Gram-negative bacteria by forcefully generating ion channels in the inner membrane. In addition to its bactericidal activity, ColN have been reported to selectively induce apoptosis in human lung cancer cells via the suppression of integrin modulated survival pathway. However, ColN showed mild toxicity against human lung cancer cells which could be improved for further applications. The protein resurfacing strategy was chosen to engineer ColN by extensive mutagenesis at solvent­-exposed residues on ColN. The highly accessible Asp and Glu on wild­type ColN (ColN^WT) were replaced by Lys to create polycationic ColN (ColN⁺¹²). Previous studies have shown that increase of positive charges on proteins leads to the enhancement of mammalian cell penetration as well as increased interaction with negatively charged surface of cancer cells. Those solvent­-exposed residues of ColN were identified by Rosetta and AvNAPSA (Average number of Neighboring Atoms Per Side­chain Atom) approaches. The findings revealed that the structural features and stability of ColN⁺¹² determined by circular dichroism were similar to ColN^WT. Furthermore, the toxicity of ColN⁺¹² was cancer ­selective. Human lung cancer cells, H460 and H23, were sensitive to ColN but human dermal papilla cells were not. ColN⁺¹² also showed more potent toxicity than ColN^WT in cancer cells. This confirmed that polycationic resurfacing method has enabled us to improve the anticancer activity of ColN towards human lung cancer cells.

An accelerated surface-mediated stress assay of antibody instability for developability studies

High physical stability is required for the development of monoclonal antibodies (mAbs) into successful therapeutic products. Developability assays are used to predict physical stability issues such as high viscosity and poor conformational stability, but protein aggregation remains a challenging property to predict. Among different types of stresses, air–water and solid–liquid interfaces are well known to potentially trigger protein instability and induce aggregation. Yet, in contrast to the increasing number of developability assays to evaluate bulk properties, there is still a lack of experimental methods to evaluate antibody stability against interfaces. Here, we investigate the potential of a hydrophobic nanoparticle surface-mediated stress assay to assess the stability of mAbs during the early stages of development. We evaluate this surface-mediated accelerated stability assay on a rationally designed library of 14 variants of a humanized IgG4, featuring a broad span of solubility values and other developability properties. The assay could identify variants characterized by high instability against agitation in the presence of air–water interfaces. Remarkably, for the set of investigated molecules, we observe strong correlations between the extent of aggregation induced by the surface-mediated stress assay and other developability properties of the molecules, such as aggregation upon storage at 45°C, self-association (evaluated by affinity-capture self-interaction nanoparticle spectroscopy) and nonspecific interactions (estimated by cross-interaction chromatography, stand-up monolayer chromatography (SMAC), SMAC*). This highly controlled surface-mediated stress assay has the potential to complement and increase the ability of the current set of screening techniques to assess protein aggregation and developability potential of mAbs during the early stages of drug development.

Abbreviations:AC-SINS: Affinity-Capture Self-Interaction Nanoparticle Spectroscopy; AMS: Ammonium sulfate precipitation; ANS: 1-anilinonaphtalene-8-sulfonate; CIC: Cross-interaction chromatography; DLS: Dynamic light scattering; HIC: Hydrophobic interaction chromatography; HNSSA: Hydrophobic nanoparticles surface-stress assay; mAb: Monoclonal antibody; NP: Nanoparticle; SEC: Size exclusion chromatography; SMAC: Stand-up monolayer chromatography; WT: Wild type

Positive charge in the complementarity-determining regions of synthetic nanobody prevents aggregation

In the past, specificity and affinity were the priority for synthetic antibody library. However, therapeutic antibodies need good stability for medical use. Through carefully adjust the chemical diversity in CDRs, one hopes to design a synthetic antibody library with good developability. Here we thoroughly analyzed 296 nanobody sequences and structures, constructed a fully-functional synthetic nanobody library, evaluated the relationship between aggregation and isoelectric point, and found that high-pI nanobodies were more resistant to aggregation than low-pIs. As we used the same framework for constructing the library, CDRs charge played a crucial role in mediating nanobody aggregation. We also analyzed the theoretical pI of 296 nanobodies from PDB, about 75% had basic pI, only 25% were acidic. Those results provided useful guidelines for designing next-generation synthetic nanobody libraries and for identifying potent and safe nanobody therapeutics.

Challenges for design of aggregation-resistant variants of granulocyte colony-stimulating factor

Non-native protein aggregation is a long-standing issue in pharmaceutical biotechnology. A rational design approach was used in order to identify variants of recombinant human granulocyte colony-stimulating factor (rhG-CSF) with lower aggregation propensity at solution conditions that are typical of commercial formulation. The approach used aggregation-prone-region (APR) predictors to select single amino acid substitutions that were predicted to decrease intrinsic aggregation propensity (IAP). The results of static light scattering temperature-ramps and chemical unfolding experiments demonstrated that none of the selected variants exhibited improved aggregation resistance, and the apparent conformational stability of each variant was lower than that of WT. Aggregation studies under partly denaturing conditions suggested that the IAP of at least one variant remained unaltered. Overall, this study highlights a general challenge in designing aggregation resistance for proteins, due to the need to accurately predict both APRs and conformational stability.

Anion solvation enhanced by positive supercharging mutations preserves thermal stability of an antibody in a wide pH range

Proteins function through interactions with other molecules. In protein engineering, scientists often engineer proteins by mutating their amino acid sequences on the protein surface to improve various physicochemical properties. "Supercharging" is a method to design proteins by mutating surface residues with charged amino acids. Previous studies demonstrated that supercharging mutations conferred better thermal resistance, solubility, and cell penetration to proteins. Likewise, antibodies recognize antigens through the antigen-binding site on the surface. The genetic and structural diversity of antibodies leads to high specificity and affinity toward antigens, enabling antibodies to be versatile tools in various applications. When assessing therapeutic antibodies, surface charge is an important factor to consider because the isoelectric point plays a role in protein clearance inside the body. In this study, we explored how supercharging mutations affect physicochemical properties of antibodies. Starting from a crystal structure of an antibody with the net charge of -4, we computationally designed a supercharged variant possessing the net charge of +10. The positive-supercharged antibody exhibited marginal improvement in thermal stability, but the secondary structure and the binding affinity to the antigen (net charge of +8) were preserved. We also used physicochemical measurements and molecular dynamics simulations to analyze the effects of supercharging mutations in sodium phosphate buffer with different pH and ion concentrations, which revealed preferential solvation of phosphate ions to the supercharged surface relative to the wild-type surface. These results suggest that supercharging would be a useful approach to preserving thermal stability of antibodies in a wide range of pH, which may enable further diversification of antibody repertoires beyond natural evolution.

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.

Stabilization of a Broadly Neutralizing Anti-Chikungunya Virus Single Domain Antibody

A single domain antibody (clone CC3) previously found to neutralize a vaccine strain of the chikungunya virus (PRNT₅₀ = 2. 5 ng/mL) was found to be broadly neutralizing. Clone CC3 is not only able to neutralize a wild-type (WT) strain of chikungunya virus (CHIKV), but also neutralizes WT strains of Mayaro virus (MAYV) and Ross River virus (RRV); both arthralgic, Old World alphaviruses. Interestingly, CC3 also demonstrated a degree of neutralizing activity against the New World alphavirus, Venezuelan equine encephalitis virus (VEEV); albeit both the vaccine strain, TC-83, and the parental, WT Trinidad donkey strain had PRNT₅₀ values ~1,000-fold higher than that of CHIKV. However, no neutralization activity was observed with Western equine encephalitis virus (WEEV). Ten CC3 variants designed to possess a range of isoelectric points, both higher and lower, were constructed. This approach successfully identified several lower pI mutants which possessed improved thermal stabilities by as much as 10°C over the original CC3 (T_m = 62°C), and excellent refolding abilities while maintaining their capacity to bind and neutralize CHIKV.

Local environment effects on charged mutations for developing aggregation-resistant monoclonal antibodies

Protein aggregation is a major concern in biotherapeutic applications of monoclonal antibodies. Introducing charged mutations is among the promising strategies to improve aggregation resistance. However, the impact of such mutations on solubilizing activity depends largely on the inserting location, whose mechanism is still not well understood. Here, we address this issue from a solvation viewpoint, and this is done by analyzing how the change in solvation free energy upon charged mutation is composed of individual contributions from constituent residues. To this end, we perform molecular dynamics simulations for a number of antibody mutants and carry out the residue-wise decomposition of the solvation free energy. We find that, in addition to the previously identified “global” principle emphasizing the key role played by the protein total net charge, a local net charge within \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim$$\end{document}∼15 Å from the mutation site exerts significant effects. For example, when the net charge of an antibody is positive, the global principle states that introducing a positively charged mutation will lead to more favorable solvation. Our finding further adds that an even more optimal mutation can be done at the site around which more positively charged residues and fewer negatively charged residues are present. Such a “local” design principle accounts for the location dependence of charged mutations, and will be useful in producing aggregation-resistant antibodies.

Investigation of Supercharging as A Strategy to Enhance the Solubility and Plasminogen Cleavage Activity of Reteplase

Background

Reteplase, the recombinant form of tissue plasminogen activator, is a thrombolytic drug with outstanding characteristics, while demonstrating limited solubility and reduced plasminogen activation. Previously, we in silico designed a variant of Reteplase with positively supercharged surface, which showed promising stability, solubility and activity. This study was devoted to evaluation of the utility of supercharging technique for enhancing these characteristics in Reteplase.

Objective

To test the hypothesis that reinforced surface charge of a rationally-designed Reteplase variant will not compromise its stability, will increase its solubility, and will enhance its plasminogen cleavage activity.

Materials and Methods

Supercharged Reteplase coding sequence was cloned in pDest527 vector and expressed in E. coli BL21 (DE3). The expressed protein was extracted by cell disruption. Inclusion bodies were solubilized using guanidine hydrochloride, followed by dialysis for protein refolding. After confirmation with SDS-PAGE and western blotting, extracted proteins were assayed for solubility and tested for bioactivity.

Results

SDS-PAGE and western blot analysis confirmed the successful expression of Reteplase. Western blot experiments showed most of Reteplase expressed in the insoluble form. Plasminogen cleavage assay showed significantly higher activity of the supercharged variant than the wild type protein (P < 0.001). The stability of the supercharged variant was also comparable to the wild type.

Conclusion

Our findings, i.e. the contribution of the surface supercharging technique to retained stability, enhanced plasminogen cleavage activity, while inefficiently changed solubility of Reteplase, contain implications for future designs of soluble variants of this fibrinolytic protein drug.

Solubility, Stability, and Avidity of Recombinant Antibody Fragments Expressed in Microorganisms

Solubility of recombinant proteins (i.e., the extent of soluble versus insoluble expression in heterogeneous hosts) is the first checkpoint criterion for determining recombinant protein quality. However, even soluble proteins often fail to represent functional activity because of the involvement of non-functional, misfolded, soluble aggregates, which compromise recombinant protein quality. Therefore, screening of solubility and folding competence is crucial for improving the quality of recombinant proteins, especially for therapeutic applications. The issue is often highlighted especially in bacterial recombinant hosts, since bacterial cytoplasm does not provide an optimal environment for the folding of target proteins of mammalian origin. Antibody fragments, such as single-chain variable fragment (scFv), single-chain antibody (scAb), and fragment antigen binding (Fab), have been utilized for numerous applications such as diagnostics, research reagents, or therapeutics. Antibody fragments can be efficiently expressed in microorganisms so that they offer several advantages for diagnostic applications such as low cost and high yield. However, scFv and scAb fragments have generally lower stability to thermal stress than full-length antibodies, necessitating a judicious combination of designer antibodies, and bacterial hosts harnessed with robust chaperone function. In this review, we discuss efforts on not only the production of antibodies or antibody fragments in microorganisms but also scFv stabilization via (i) directed evolution of variants with increased stability using display systems, (ii) stabilization of the interface between variable regions of heavy (V_H) and light (V_L) chains through the introduction of a non-native covalent bond between the two chains, (iii) rational engineering of V_H-V_L pair, based on the structure, and (iv) computational approaches. We also review recent advances in stability design, increase in avidity by multimerization, and maintaining the functional competence of chimeric proteins prompted by various types of chaperones.

Supercharged Proteins and Polypeptides

Electrostatic interactions play a vital role in nature. Biomacromolecules such as proteins are orchestrated by electrostatics, among other intermolecular forces, to assemble and organize biochemistry. Natural proteins with a high net charge exist in a folded state or are unstructured and can be an inspiration for scientists to artificially supercharge other protein entities. Recent findings show that supercharging proteins allows for control of their properties such as temperature resistance and catalytic activity. One elegant method to transfer the favorable properties of supercharged proteins to other proteins is the fabrication of fusions. Genetically engineered, supercharged unstructured polypeptides (SUPs) are just one promising fusion tool. SUPs can also be complexed with artificial entities to yield thermotropic and lyotropic liquid crystals and liquids. These architectures represent novel bulk materials that are sensitive to external stimuli. Interestingly, SUPs undergo fluid-fluid phase separation to form coacervates. These coacervates can even be directly generated in living cells or can be combined with dissipative fiber assemblies that induce life-like features. Supercharged proteins and SUPs are developed into exciting classes of materials. Their synthesis, structures, and properties are summarized. Moreover, potential applications are highlighted and challenges are discussed.

Exploration and Modulation of Antibody Fragment Biophysical Properties by Replacing the Framework Region Sequences

In order to increase the successful development of recombinant antibodies and fragments, it seems fundamental to enhance their expression and/or biophysical properties, such as the thermal, chemical, and pH stabilities. In this study, we employed a method bases on replacing the antibody framework region sequences, in order to promote more particularly single-chain Fragment variable (scFv) product quality. We provide evidence that mutations of the VH- C-C′ loop might significantly improve the prokaryote production of well-folded and functional fragments with a production yield multiplied by 27 times. Additional mutations are accountable for an increase in the thermal (+19.6 °C) and chemical (+1.9 M) stabilities have also been identified. Furthermore, the hereby-produced fragments have shown to remain stable at a pH of 2.0, which avoids molecule functional and structural impairments during the purification process. Lastly, this study provides relevant information to the understanding of the relationship between the antibodies amino acid sequences and their respective biophysical properties.

Computer-based Engineering of Thermostabilized Antibody Fragments

We used the molecular modeling program Rosetta to identify clusters of amino acid substitutions in antibody fragments (scFvs and scAbs) that improve global protein stability and resistance to thermal deactivation. Using this methodology, we increased the melting temperature (T_m) and resistance to heat treatment of an antibody fragment that binds to the Clostridium botulinum hemagglutinin protein (anti-HA33). Two designed antibody fragment variants with two amino acid replacement clusters, designed to stabilize local regions, were shown to have both higher T_m compared to the parental scFv and importantly, to retain full antigen binding activity after 2 hours of incubation at 70 °C. The crystal structure of one thermostabilized scFv variants was solved at 1.6 Å and shown to be in close agreement with the RosettaAntibody model prediction.

Using protein engineering to understand and modulate aggregation

Protein aggregation occurs through a variety of mechanisms, initiated by the unfolded, non-native, or even the native state itself. Understanding the molecular mechanisms of protein aggregation is challenging, given the array of competing interactions that control solubility, stability, cooperativity and aggregation propensity. An array of methods have been developed to interrogate protein aggregation, spanning computational algorithms able to identify aggregation-prone regions, to deep mutational scanning to define the entire mutational landscape of a protein's sequence. Here, we review recent advances in this exciting and emerging field, focussing on protein engineering approaches that, together with improved computational methods, hold promise to predict and control protein aggregation linked to human disease, as well as facilitating the manufacture of protein-based therapeutics.

Computationally Aided Discovery of LysEFm5 Variants with Improved Catalytic Activity and Stability

Bacteriophage-derived lysin proteins are potentially effective antimicrobials that would benefit from engineered improvements to their bioavailability and specific activity. Here, the catalytic domain of LysEFm5, a lysin with activity against vancomycin-resistant Enterococcus faecium (VRE), was subjected to site-saturation mutagenesis at positions whose selection was guided by sequence and structural information from homologous proteins. A second-order Potts model with parameters inferred from large sets of homologous sequence information was used to predict the average change in the statistical fitness for mutant libraries with diversity at pairs of sites within the secondary catalytic shell. Guided by the statistical fitness, nine double mutant saturation libraries were created and plated on agar containing autoclaved VRE to quickly identify and segregate catalytically active (halo-forming) and inactive (non-halo-forming) variants. High-throughput DNA sequencing of 873 unique variants showed that the statistical fitness was predictive of the retention or loss of catalytic activity (area under the curve [AUC], 0.840 to 0.894), with the inclusion of more diverse sequences in the starting multiple-sequence alignment improving the classification accuracy when pairwise amino acid couplings (epistasis) were considered. Of eight random halo-forming variants selected for more sensitive testing, one showed a 1.8 (±0.4)-fold improvement in specific activity and an 11.5 ± 0.8°C increase in melting temperature compared to those of the wild type. Our results demonstrate that a computationally informed approach employing homologous protein information coupled with a mid-throughput screening assay allows for the expedited discovery of lysin variants with improved properties.IMPORTANCE Broad-spectrum antibiotics can indiscriminately kill most bacteria, including commensal species that are a part of the normal human flora. This can potentially lead to the proliferation of drug-resistant bacteria upon elimination of competing species and to unwanted autoimmune effects in patients. Bacteriophage-derived lysin proteins are an alternative to conventional antibiotics that have coevolved alongside specific bacterial hosts. Lysins are capable of targeting conserved substrates in the bacterial cell wall essential for its viability. To engineer these proteins to exhibit improved therapeutically relevant properties, homology-guided statistical approaches can be used to identify compelling sites for mutation and to quantify the functional constraints acting on these sites to direct mutagenic library creation. The platform described herein couples this informed approach with a visual plate assay that can be used to simultaneously screen hundreds of mutants for catalytic activity, allowing for the streamlined identification of improved lysin variants.

Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces

Antibodies developed for research and clinical applications may exhibit suboptimal stability, expressibility, or affinity. Existing optimization strategies focus on surface mutations, whereas natural affinity maturation also introduces mutations in the antibody core, simultaneously improving stability and affinity. To systematically map the mutational tolerance of an antibody variable fragment (Fv), we performed yeast display and applied deep mutational scanning to an anti-lysozyme antibody and found that many of the affinity-enhancing mutations clustered at the variable light-heavy chain interface, within the antibody core. Rosetta design combined enhancing mutations, yielding a variant with tenfold higher affinity and substantially improved stability. To make this approach broadly accessible, we developed AbLIFT, an automated web server that designs multipoint core mutations to improve contacts between specific Fv light and heavy chains (http://AbLIFT.weizmann.ac.il). We applied AbLIFT to two unrelated antibodies targeting the human antigens VEGF and QSOX1. Strikingly, the designs improved stability, affinity, and expression yields. The results provide proof-of-principle for bypassing laborious cycles of antibody engineering through automated computational affinity and stability design.

Antibodies are highly important in research, biotechnology, and medical applications. Despite their great utility, however, many antibodies exhibit suboptimal stability and affinity, raising production costs and limiting their practical usefulness. To tackle this general limitation, we used deep mutational scanning to characterize the effects of mutations in an antibody variable fragment on its antigen-binding affinity. Surprisingly, many of the affinity-enhancing mutations clustered at the variable light-heavy chain interface. We, therefore, developed an automated method, called AbLIFT (http://AbLIFT.weizmann.ac.il) to optimize this interface through design. Two unrelated antibodies were tested and showed improvements in expression levels, stability, and antigen-binding affinity. Since AbLIFT requires testing of only a few dozen specific designs, it may dramatically accelerate the development of promising antibodies into useful research and clinical tools.

Computational Assessment of Bacterial Protein Structures Indicates a Selection Against Aggregation

The aggregation of proteins compromises cell fitness, either because it titrates functional proteins into non-productive inclusions or because it results in the formation of toxic assemblies. Accordingly, computational proteome-wide analyses suggest that prevention of aggregation upon misfolding plays a key role in sequence evolution. Most proteins spend their lifetimes in a folded state; therefore, it is conceivable that, in addition to sequences, protein structures would have also evolved to minimize the risk of aggregation in their natural environments. By exploiting the AGGRESCAN3D structure-based approach to predict the aggregation propensity of >600 Escherichia coli proteins, we show that the structural aggregation propensity of globular proteins is connected with their abundance, length, essentiality, subcellular location and quaternary structure. These data suggest that the avoidance of protein aggregation has contributed to shape the structural properties of proteins in bacterial cells.

Improving the solubility, activity, and stability of reteplase using in silico design of new variants

Reteplase (recombinant plasminogen activator, r-PA) is a thrombolytic agent recombined from tissue-type plasminogen activator (t-PA), which has several prominent features such as strong thrombolytic ability and E. coli expressibility. Despite these outstanding features, it demonstrates reduced fibrin binding affinity, reduced stimulation of protease activity, and lower solubility, hence higher aggregation propensity, compared to t-PA. The present study was devoted to design r-PA variants with comparable structural stability, enhanced biological activity, and high solubility. For this purpose, computational molecular modeling techniques were utilized. The supercharging technique was applied for r-PA to designing new species of the protein. Based on the results from in silico evaluation of selected mutations in comparison to the wild-type r-PA, the designed supercharged mutant (S7 variant) exhibited augmented stability, decreased solvation energy, as well as enhanced binding affinity to fibrin. The data also implied increased plasminogen cleavage activity of the new variant. These findings have implications to therapies which involve removal of intravascular blood clots, including the treatment of acute myocardial infarction.

SODA: prediction of protein solubility from disorder and aggregation propensity

Solubility is an important, albeit not well understood, feature determining protein behavior. It is of paramount importance in protein engineering, where similar folded proteins may behave in very different ways in solution. Here we present SODA, a novel method to predict the changes of protein solubility based on several physico-chemical properties of the protein. SODA uses the propensity of the protein sequence to aggregate as well as intrinsic disorder, plus hydrophobicity and secondary structure preferences to estimate changes in solubility. It has been trained and benchmarked on two different datasets. The comparison to other recently published methods shows that SODA has state-of-the-art performance and is particularly well suited to predict mutations decreasing solubility. The method is fast, returning results for single mutations in seconds. A usage example estimating the full repertoire of mutations for a human germline antibody highlights several solubility hotspots on the surface. The web server, complete with RESTful interface and extensive help, can be accessed from URL: http://protein.bio.unipd.it/soda.

High-Throughput Antibody Structure Modeling and Design Using ABodyBuilder

Antibodies are proteins of the adaptive immune system; they can be designed to bind almost any molecule, and are increasingly being used as biotherapeutics. Experimental antibody design is an expensive and time-consuming process, and computational antibody design methods can now be used to help develop new therapeutics and diagnostics. Within the design pipeline, accurate antibody structure modeling is essential, as it provides the basis for antibody-antigen docking, binding affinity prediction, and estimating thermal stability. Ideally, models should be rapidly generated, allowing the exploration of the breadth of antibody space. This allows methods to replicate the natural processes of antibody diversification (e.g., V(D)J recombination and somatic hypermutation), and cope with large volumes of data that are typical of next-generation sequencing datasets. Here we describe ABodyBuilder and PEARS, algorithms that build and mutate antibody model structures. These methods take ~30 s to generate a model antibody structure.

Rational re-design of Lactobacillus reuteri 121 inulosucrase for product chain length control

Fructooligosaccharides (FOSs) are well-known prebiotics that are widely used in the food, beverage and pharmaceutical industries. Inulosucrase (E.C. 2.4.1.9) can potentially be used to synthesise FOSs from sucrose. In this study, inulosucrase from Lactobacillus reuteri 121 was engineered by site-directed mutagenesis to change the FOS chain length. Three variants (R483F, R483Y and R483W) were designed, and their binding free energies with 1,1,1-kestopentaose (GF4) were calculated with the Rosetta software. R483F and R483Y were predicted to bind with GF4 better than the wild type, suggesting that these engineered enzymes should be able to effectively extend GF4 by one residue and produce a greater quantity of GF5 than the wild type. MALDI-TOF MS analysis showed that R483F, R483Y and R483W variants could synthesise shorter chain FOSs with a degree of polymerization (DP) up to 11, 10, and 10, respectively, while wild type produced longer FOSs and in polymeric form. Although the decrease in catalytic activity and the increase of hydrolysis/transglycosylation activity ratio was observed, the variants could effectively synthesise FOSs with the yield up to 73% of substrate. Quantitative analysis demonstrated that these variants produced a larger quantity of GF5 than wild type, which was in good agreement with the predicted binding free energy results. Our findings demonstrate the success of using aromatic amino acid residues, at position D418, to block the oligosaccharide binding track of inulosucrase in controlling product chain length.

What Are We Missing by Not Measuring the Net Charge of Proteins?

The net electrostatic charge (Z) of a folded protein in solution represents a bird's eye view of its surface potentials-including contributions from tightly bound metal, solvent, buffer, and cosolvent ions-and remains one of its most enigmatic properties. Few tools are available to the average biochemist to rapidly and accurately measure Z at pH≠pI. Tools that have been developed more recently seem to go unnoticed. Most scientists are content with this void and estimate the net charge of a protein from its amino acid sequence, using textbook values of pK_a . Thus, Z remains unmeasured for nearly all folded proteins at pH≠pI. When marveling at all that has been learned from accurately measuring the other fundamental property of a protein-its mass-one wonders: what are we missing by not measuring the net charge of folded, solvated proteins? A few big questions immediately emerge in bioinorganic chemistry. When a single electron is transferred to a metalloprotein, does the net charge of the protein change by approximately one elementary unit of charge or does charge regulation dominate, that is, do the pK_a values of most ionizable residues (or just a few residues) adjust in response to (or in concert with) electron transfer? Would the free energy of charge regulation (ΔΔG_z ) account for most of the outer sphere reorganization energy associated with electron transfer? Or would ΔΔG_z contribute more to the redox potential? And what about metal binding itself? When an apo-metalloprotein, bearing minimal net negative charge (e.g., Z=-2.0) binds one or more metal cations, is the net charge abolished or inverted to positive? Or do metalloproteins regulate net charge when coordinating metal ions? The author's group has recently dusted off a relatively obscure tool-the "protein charge ladder"-and used it to begin to answer these basic questions.

Protein engineering: the potential of remote mutations

Engineered proteins, especially enzymes, are now commonly used in many industries owing to their catalytic power, specific binding of ligands, and properties as materials and food additives. As the number of potential uses for engineered proteins has increased, the interest in engineering or designing proteins to have greater stability, activity and specificity has increased in turn. With any rational engineering or design pursuit, the success of these endeavours relies on our fundamental understanding of the systems themselves; in the case of proteins, their structure-dynamics-function relationships. Proteins are most commonly rationally engineered by targeting the residues that we understand to be functionally important, such as enzyme active sites or ligand-binding sites. This means that the majority of the protein, i.e. regions remote from the active- or ligand-binding site, is often ignored. However, there is a growing body of literature that reports on, and rationalises, the successful engineering of proteins at remote sites. This minireview will discuss the current state of the art in protein engineering, with a particular focus on engineering regions that are remote from active- or ligand-binding sites. As the use of protein technologies expands, exploiting the potential improvements made possible through modifying remote regions will become vital if we are to realise the full potential of protein engineering and design.

Exploring designability of electrostatic complementarity at an antigen-antibody interface directed by mutagenesis, biophysical analysis, and molecular dynamics simulations

Antibodies protect organisms from a huge variety of foreign antigens. Antibody diversity originates from both genetic and structural levels. Antigen recognition relies on complementarity between antigen-antibody interfaces. Recent methodological advances in structural biology and the accompanying rapid increase of the number of crystal structures of proteins have enabled atomic-level manipulation of protein structures to effect alterations in function. In this study, we explored the designability of electrostatic complementarity at an antigen-antibody interface on the basis of a crystal structure of the complex. We designed several variants with altered charged residues at the interface and characterized the designed variants by surface plasmon resonance, circular dichroism, differential scanning calorimetry, and molecular dynamics simulations. Both successes and failures of the structure-based design are discussed. The variants that compensate electrostatic interactions can restore the interface complementarity, enabling the cognate antigen-antibody binding. Retrospectively, we also show that these mutational effects could be predicted by the simulations. Our study demonstrates the importance of charged residues on the physical properties of this antigen-antibody interaction and suggests that computational approaches can facilitate design of antibodies that recognize a weakly immunogenic antigen.

Custom selenoprotein production enabled by laboratory evolution of recoded bacterial strains

Incorporation of the rare amino acid selenocysteine to form diselenide bonds can improve stability and function of synthetic peptide therapeutics. However, application of this approach to recombinant proteins has been hampered by heterogeneous incorporation, low selenoprotein yields, and poor fitness of bacterial producer strains. We report the evolution of recoded Escherichia coli strains with improved fitness that are superior hosts for recombinant selenoprotein production. We apply an engineered β-lactamase containing an essential diselenide bond to enforce selenocysteine dependence during continuous evolution of recoded E. coli strains. Evolved strains maintain an expanded genetic code indefinitely. We engineer a fluorescent reporter to quantify selenocysteine incorporation in vivo and show complete decoding of UAG codons as selenocysteine. Replacement of native, labile disulfide bonds in antibody fragments with diselenide bonds vastly improves resistance to reducing conditions. Highly seleno-competent bacterial strains enable industrial-scale selenoprotein expression and unique diselenide architecture, advancing our ability to customize the selenoproteome.

An iterative computational design approach to increase the thermal endurance of a mesophilic enzyme

BACKGROUND

Strategies for maximizing the microbial production of bio-based chemicals and fuels include eliminating branched points to streamline metabolic pathways. While this is often achieved by removing key enzymes, the introduction of nonnative enzymes can provide metabolic shortcuts, bypassing branched points to decrease the production of undesired side-products. Pyruvate decarboxylase (PDC) can provide such a shortcut in industrially promising thermophilic organisms; yet to date, this enzyme has not been found in any thermophilic organism. Incorporating nonnative enzymes into host organisms can be challenging in cases such as this, where the enzyme has evolved in a very different environment from that of the host.

RESULTS

In this study, we use computational protein design to engineer the Zymomonas mobilis PDC to resist thermal denaturation at the growth temperature of a thermophilic host. We generate thirteen PDC variants using the Rosetta protein design software. We measure thermal stability of the wild-type PDC and PDC variants using circular dichroism. We then measure and compare enzyme endurance for wild-type PDC with the PDC variants at an elevated temperature of 60 °C (thermal endurance) using differential interference contrast imaging.

CONCLUSIONS

We find that increases in melting temperature (T_m) do not directly correlate with increases in thermal endurance at 60 °C. We also do not find evidence that any individual mutation or design approach is the major contributor to the most thermostable PDC variant. Rather, remarkable cooperativity among sixteen thermostabilizing mutations is key to rationally designing a PDC with significantly enhanced thermal endurance. These results suggest a generalizable iterative computational protein design approach to improve thermal stability and endurance of target enzymes.