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Despite the unique advantages of IgG3 over other IgG subclasses, such as mediating enhanced effector functions and increased flexibility in antigen binding due to a long hinge region, the therapeutic potential of IgG3 remains largely unexplored. This may be attributed to difficulties in recombinant expression and the reduced plasma half-life of most IgG3 allotypes. Here, we report plant expression of two SARS-CoV-2 neutralizing monoclonal antibodies (mAbs) that exhibit high (P5C3) and low (H4) antigen binding. P5C3 and H4-IgG1 mAbs were subclass-switched to IgG3 formats, designed for efficient production and increased PK values, carrying three allotypic variations, referred to as -WT, -H, and -KVH. A total of eight mAbs were produced in glycoengineered plants that synthesize fucose-free complex N-glycans with great homogeneity. Antigen, IgG-FcγR immune complex and complement binding studies demonstrated similar activities of all mAbs. In accordance, P5C3 Abs showed minor alterations in SARS-CoV-2 neutralization (NT) and antibody-dependent cell-mediated virus inhibition (ADCVI). Clear functional differences were observed between H4 variants with superior ADCVI and NT potencies of H4 IgG3 H. Our comparative study demonstrates the production of an IgG3 variant carrying an Fc domain with equivalent or enhanced functions compared to IgG3-WT, but with the stability and PK values ​​of IgG1. Our data also demonstrate that both allotypic variability and antibody specificity are important for fine-tuning of activities, an important information for the development of future therapeutics. [ABSTRACT FROM AUTHOR]

The evolving development landscape of biotherapeutics and their growing complexity from simple antibodies into bi- and multi-specific molecules necessitates sophisticated discovery and engineering platforms. This review focuses on mammalian display technology as a potential solution to the pressing challenges in biotherapeutic development. We provide a comparative analysis with established methodologies, highlighting key aspects of mammalian display technology, including genetic engineering, construction of display libraries, and its pivotal role in hit selection and/or developability engineering. The review delves into the mechanisms underpinning developability-driven selection via mammalian display and their broader implications. Applications beyond antibody discovery are also explored, alongside advancements towards function-first screening technologies, precision genome engineering and AI/MLenhanced libraries, situating them in the context of mammalian display. Overall, the review provides a comprehensive overview of the current mammalian display technology landscape, underscores the expansive potential of the technology for biotherapeutic development, addresses the critical challenges for the full realisation of this potential, and examines advances in related disciplines that might impact the future application of mammalian display technologies. [ABSTRACT FROM AUTHOR]

The humanization of camelid‐derived variable domain heavy chain antibodies (VHHs) poses challenges including immunogenicity, stability, and potential reduction of affinity. Critical to this process are complementarity‐determining regions (CDRs), Vernier and Hallmark residues, shaping the three‐dimensional fold and influencing VHH structure and function. Additionally, the presence of non‐canonical disulfide bonds further contributes to conformational stability and antigen binding. In this study, we systematically humanized two camelid‐derived VHHs targeting the natural cytotoxicity receptor NKp30. Key structural positions in Vernier and Hallmark regions were exchanged with residues from the most similar human germline sequences. The resulting variants were characterized for binding affinities, yield, and purity. Structural binding modes were elucidated through crystal structure determination and AlphaFold2 predictions, providing insights into differences in binding affinity. Comparative structural and molecular dynamics characterizations of selected variants were performed to rationalize their functional properties and elucidate the role of specific sequence motifs in antigen binding. Furthermore, systematic analyses of next‐generation sequencing (NGS) and Protein Data Bank (PDB) data was conducted, shedding light on the functional significance of Hallmark motifs and non‐canonical disulfide bonds in VHHs in general. Overall, this study provides valuable insights into the structural determinants governing the functional properties of VHHs, offering a roadmap for their rational design, humanization, and optimization for therapeutic applications. [ABSTRACT FROM AUTHOR]

Human-derived monoclonal antibodies (HD-mAbs) can be used to study neural proteotypes, cell populations defined by their proteome rather than their transcriptome. The human antibody repertoire is a nearly inexhaustible source of unique HD-mAbs that can be used to manipulate select proteotypes. Because autoantibodies can cause neuropsychiatric symptoms, some HD-mAbs may help map neural proteotypes to behavioral phenomena. HD-mAbs can traverse the placenta and are easily ported across model systems. Antibody engineering can be used to tune the functional properties of HD-mAbs, thereby increasing their versatility. A major aim of neuroscience is to identify and model the functional properties of neural cells whose dysfunction underlie neuropsychiatric illness. In this article, we propose that human-derived monoclonal autoantibodies (HD-mAbs) are well positioned to selectively target and manipulate neural subpopulations as defined by their protein expression; that is, cellular proteotypes. Recent technical advances allow for efficient cloning of autoantibodies from neuropsychiatric patients. These HD-mAbs can be introduced into animal models to gain biological and pathobiological insights about neural proteotypes of interest. Protein engineering can be used to modify, enhance, silence, or confer new functional properties to native HD-mAbs, thereby enhancing their versatility. Finally, we discuss the challenges and limitations confronting HD-mAbs as experimental research tools for neuroscience. [ABSTRACT FROM AUTHOR]

Therapeutic protein engineering has revolutionized medicine by enabling the development of highly specific and potent treatments for a wide range of diseases. This review examines recent advances in computational and experimental approaches for engineering improved protein therapeutics. Key areas of focus include antibody engineering, enzyme replacement therapies, and cytokine-based drugs. Computational methods like structure-based design, machine learning integration, and protein language models have dramatically enhanced our ability to predict protein properties and guide engineering efforts. Experimental techniques such as directed evolution and rational design approaches continue to evolve, with high-throughput methods accelerating the discovery process. Applications of these methods have led to breakthroughs in affinity maturation, bispecific antibodies, enzyme stability enhancement, and the development of conditionally active cytokines. Emerging approaches like intracellular protein delivery, stimulus-responsive proteins, and de novo designed therapeutic proteins offer exciting new possibilities. However, challenges remain in predicting in vivo behavior, scalable manufacturing, immunogenicity mitigation, and targeted delivery. Addressing these challenges will require continued integration of computational and experimental methods, as well as a deeper understanding of protein behavior in complex physiological environments. As the field advances, we can anticipate increasingly sophisticated and effective protein therapeutics for treating human diseases. [ABSTRACT FROM AUTHOR]

Spatial hindrance‐based pro‐antibodies (pro‐Abs) are engineered antibodies to reduce monoclonal antibodies' (mAbs) on‐target toxicity using universal designed blocking segments that mask mAb antigen‐binding sites through spatial hindrance. By linking through protease substrates and linkers, these blocking segments can be removed site‐specifically. Although many types of blocking segments have been developed, such as coiled‐coil and hinge‐based Ab locks, the molecular structure of the pro‐Ab, particularly the region showing how the blocking fragment blocks the mAb, has not been elucidated by X‐ray crystallography or cryo‐EM. To achieve maximal effect, a pro‐Ab must have high antigen‐blocking and protease‐restoring efficiencies, but the unclear structure limits its further optimization. Here, we utilized molecular dynamics (MD) simulations to study the dynamic structures of a hinge‐based Ab lock pro‐Ab, pro‐Nivolumab, and validated the simulated structures with small‐ and wide‐angle X‐ray scattering (SWAXS). The MD results were closely consistent with SWAXS data (χ2best‐fit = 1.845, χ2allMD = 3.080). The further analysis shows a pronounced flexibility of the Ab lock (root‐mean‐square deviation = 10.90 Å), yet it still masks the important antigen‐binding residues by 57.3%–88.4%, explaining its 250‐folded antigen‐blocking efficiency. The introduced protease accessible surface area method affirmed better protease efficiency for light chain (33.03 Å2) over heavy chain (5.06 Å2), which aligns with the experiments. Overall, we developed MD‐SWAXS validation method to study the dynamics of flexible blocking segments and introduced methodologies to estimate their antigen‐blocking and protease‐restoring efficiencies, which would potentially be advancing the clinical applications of any spatial hindrance‐based pro‐Ab. [ABSTRACT FROM AUTHOR]

Therapeutic antibodies have predominantly been IgG‐based. However, the ongoing clinical trial of MOv18 IgE has highlighted the potential of using IgE antibodies in cancer therapy. While extensive studies targeting IgG glycosylation resulted in a rational basis for the development of enhanced biotherapeutics, IgE glycosylation remains an area with limited analyses. Previous studies on the role of IgE glycosylation present conflicting data with one study emphasizing the importance of N275 and T277 residues for FcεRI binding whereas another asserts the nonsignificance of IgE glycosylation in receptor interaction. While existing literature underscores the significance of glycans at the N275 position for binding to FcεR1 receptor and initiation of anaphylaxis, the role of other IgE glycosylation sites in folding or receptor binding remains elusive. This study systematically investigates the functional significance of N‐linked glycosylation sites in the heavy chain of IgE which validates the pivotal role of N275 residue in IgE secretion and stability. Replacement of this asparagine to non‐amine group moieties does not affect IgE function in vitro, yet substitution with aspartic acid compromises antibody yield. The deglycosylated IgE variant exhibits superior efficacy, challenging the conventional importance of glycosylation for effector function. In summary, our study unveils an intricate relationship between N‐glycosylation sites and the structural–functional dynamics of IgE antibodies. Furthermore, it offers novel insights into the IgE scaffold, paving the way for the development of more effective and stable IgE‐based therapeutics. [ABSTRACT FROM AUTHOR]

Objective: The VEGF function blockage effectively reduces the progression of diabetic retinopathy. Ranibizumab and bevacizumab are some anti-VEGF monoclonal antibodies (mAb). Considering the importance of affinity maturation of ranibizumab, we aimed to find the essential amino acids of the ranibizumab antibody (Ab). Materials and Methods: We tried to find the important amino acids of this antibody via Paratome, Meta-PPISP, and the WESA web server. Subsequently, these amino acids were mutated to improve the binding affinity of the Ab variants to antigen (Ag). In this regard, the ranibizumab anti-VEGF-A was mutated. The structural docking prediction of the ranibizumab-VEGF-A complex was used for the design and validation of ranibizumab with a higher affinity for binding to VEGF-A. Finally, we measured the binding affinity of Ab variants to Ag by computational docking. Results: Bioinformatic analyzes such as molecular docking and dynamics showed that several mutant variants successfully improved the properties of Ab binding compared to the wild-type Ab. Conclusion: Consistent with the use of anti-VEGF monoclonal antibodies in the treatment of diabetic retinopathy, the mutant variants of ranibizumab may be potential candidates for stronger affinity binding to VEGF, which may affect the specificity and sensitivity of the antibody.

Objective: Bullous pemphigoid is a rare autoimmune skin disorder characterized by blistering, urticarial lesions, which are sometimes associated with adverse drug reactions. Vildagliptin is an oral anti-diabetic agent that selectively inhibits the dipeptidyl peptidase-4 (DPP-4) enzyme. Materials and Methods: A 75-year-old female with a known case of type 2 Diabetes Mellitus, hypertension, and hypothyroidism for the last 10 years presented with pruriginous tense bullous skin lesions over her both palms and soles. There was no mucosal involvement. Further interrogation revealed that she started taking Vildagliptin 5 days ago which was prescribed due to high levels of post-prandial blood sugar level despite already intake of Glimepiride-4 mg and Metformin-3 gm. Results: Vildagliptin was immediately advised to be stopped. She was treated with antihistamines, steroids, and conservative management which led to remission of the blisters. Conclusion: Vildagliptin is the probable causative drug for developing bullous pemphigoid skin lesion which shows temporal association in this case as other concomitant drugs has no direct correlation. Therefore physicians must be aware of this rare life-threatening side effect of this medicine and advice patients to visit the hospital even the slightest cutaneous manifestation. Bullous pemphigoid can result in fatal life-threatening conditions if not treated early.

Summary The Fc region of antibodies is vital for most of their physiological functions, many of which are engaged through binding to a range of Fc receptors. However, these same interactions are not always helpful or wanted when therapeutic antibodies are directed against self‐antigens, and can sometimes cause catastrophic adverse reactions. Over the past 40 years, there have been intensive efforts to “silence” unwanted binding to Fc‐gamma receptors, resulting in at least 45 different variants which have entered clinical trials. One of the best known is “LALA” (L234A/L235A). However, neither this, nor most of the other variants in clinical use are completely silenced, and in addition, the biophysical properties of many of them are compromised. I review the development of different variants to see what we can learn from their biological properties and use in the clinic. With the rise of powerful new uses of antibody therapy such as bispecific T‐cell engagers, antibody‐drug conjugates, and checkpoint inhibitors, it is increasingly important to optimize the Fc region as well as the antibody binding site in order to achieve the best combination of safety and efficacy. [ABSTRACT FROM AUTHOR]

Single-chain Fv (scFv) is a recombinant small antibody in which a polypeptide linker connects the variable regions of the light chain (VL) and the heavy chain (VH). The practical use of scFv, however, has been prevented by its tendency to aggregate due to interchain VL–VH interactions. We recently developed a cyclic scFv whose N-terminus and C-terminus were connected by protein ligation techniques. Biophysical comparisons between cyclic and linear scFv have been conducted, but cell biological evaluations remain unexplored. Here we studied the properties of cyclic and linear scFv derived from nivolumab. Biophysical studies revealed that the thermal stability was not changed but that the antigen-binding activity was approximately 3-fold higher as a result of circularization. A cell-based PD-1/PD-L1 interaction inhibitory assay revealed that the biological activity of scFv was markedly higher in the circularized form. In addition, biophysical analysis of scFv proteins incubated in the presence of serum revealed that circularization suppressed the decrease in antigen-binding activity. It could be assumed that circularization of scFv improved stability in the presence of serum, which in turn would suggest the applicability of cyclic scFv as a biopharmaceutical format. [ABSTRACT FROM AUTHOR]

In this work we have generated cattle-derived chimeric ultralong CDR-H3 antibodies targeting tumor necrosis factor α (TNF-α) via immunization and yeast surface display. We identified one particular ultralong CDR-H3 paratope that potently neutralized TNF-α. Interestingly, grafting of the knob architecture onto a peripheral loop of the CH3 domain of the Fc part of an IgG1 resulted in the generation of a TNF-α neutralizing Fc (Fcknob) that did not show any potency loss compared with the parental chimeric IgG format. Eventually, grafting this knob onto the CH3 region of adalimumab enabled the engineering of a novel TNF-α targeting antibody architecture displaying augmented TNF-α inhibition. [ABSTRACT FROM AUTHOR]

Objective: The VEGF function blockage effectively reduces the progression of diabetic retinopathy. Ranibizumab and bevacizumab are some anti-VEGF monoclonal antibodies (mAb). Considering the importance of affinity maturation of ranibizumab, we aimed to find the essential amino acids of the ranibizumab antibody (Ab). Materials and Methods: We tried to find the important amino acids of this antibody via Paratome, Meta-PPISP, and the WESA web server. Subsequently, these amino acids were mutated to improve the binding affinity of the Ab variants to antigen (Ag). In this regard, the ranibizumab anti-VEGF-A was mutated. The structural docking prediction of the ranibizumab-VEGF-A complex was used for the design and validation of ranibizumab with a higher affinity for binding to VEGF-A. Finally, we measured the binding affinity of Ab variants to Ag by computational docking. Results: Bioinformatic analyzes such as molecular docking and dynamics showed that several mutant variants successfully improved the properties of Ab binding compared to the wild-type Ab. Conclusion: Consistent with the use of anti-VEGF monoclonal antibodies in the treatment of diabetic retinopathy, the mutant variants of ranibizumab may be potential candidates for stronger affinity binding to VEGF, which may affect the specificity and sensitivity of the antibody. [ABSTRACT FROM AUTHOR]

As the demand for immunotherapy to treat and manage cancers, infectious diseases and other disorders grows, a comprehensive understanding of amino acids and their intricate role in antibody engineering has become a prime requirement. Naturally produced antibodies may not have the most suitable amino acids at the complementarity determining regions (CDR) and framework regions, for therapeutic purposes. Therefore, to enhance the binding affinity and therapeutic properties of an antibody, the specific impact of certain amino acids on the antibody's architecture must be thoroughly studied. In antibody engineering, it is crucial to identify the key amino acid residues that significantly contribute to improving antibody properties. Therapeutic antibodies with higher binding affinity and improved functionality can be achieved through modifications or substitutions with highly suitable amino acid residues. Here, we have indicated the frequency of amino acids and their association with the binding free energy in CDRs. The review also analyzes the experimental outcome of two studies that reveal the frequency of amino acids in CDRs and provides their significant correlation between the outcomes. Additionally, it discusses the various bond interactions within the antibody structure and antigen binding. A detailed understanding of these amino acid properties should assist in the analysis of antibody sequences and structures needed for designing and enhancing the overall performance of therapeutic antibodies. [ABSTRACT FROM AUTHOR]

The vast majority of antibodies generated against a virus will be non-neutralising. However, this does not denote an absence of protective capacity. Yet, within the field, there is typically a large focus on antibodies capable of directly blocking infection (neutralising antibodies, NAbs) of either specific viral strains or multiple viral strains (broadly-neutralising antibodies, bNAbs). More recently, a focus on non-neutralising antibodies (nNAbs), or neutralisation-independent effects of NAbs, has emerged. These can have additive effects on protection or, in some cases, be a major correlate of protection. As their name suggests, nNAbs do not directly neutralise infection but instead, through their Fc domains, may mediate interaction with other immune effectors to induce clearance of viral particles or virally infected cells. nNAbs may also interrupt viral replication within infected cells. Developing technologies of antibody modification and functionalisation may lead to innovative biologics that harness the activities of nNAbs for antiviral prophylaxis and therapeutics. In this review, we discuss specific examples of nNAb actions in viral infections where they have known importance. We also discuss the potential detrimental effects of such responses. Finally, we explore new technologies for nNAb functionalisation to increase efficacy or introduce favourable characteristics for their therapeutic applications. [ABSTRACT FROM AUTHOR]

Despite the unique advantages of IgG3 over other IgG subclasses, such as mediating enhanced effector functions and increased flexibility in antigen binding due to a long hinge region, the therapeutic potential of IgG3 remains largely unexplored. This may be attributed to difficulties in recombinant expression and the reduced plasma half-life of most IgG3 allotypes. Here, we report plant expression of two SARS-CoV-2 neutralizing monoclonal antibodies (mAbs) that exhibit high (P5C3) and low (H4) antigen binding. P5C3 and H4-IgG1 mAbs were subclass-switched to IgG3 formats, designed for efficient production and increased PK values, carrying three allotypic variations, referred to as -WT, -H, and -KVH. A total of eight mAbs were produced in glycoengineered plants that synthesize fucose-free complex N-glycans with great homogeneity. Antigen, IgG-FcγR immune complex and complement binding studies demonstrated similar activities of all mAbs. In accordance, P5C3 Abs showed minor alterations in SARS-CoV-2 neutralization (NT) and antibody-dependent cell-mediated virus inhibition (ADCVI). Clear functional differences were observed between H4 variants with superior ADCVI and NT potencies of H4 IgG3 H. Our comparative study demonstrates the production of an IgG3 variant carrying an Fc domain with equivalent or enhanced functions compared to IgG3-WT, but with the stability and PK values ​​of IgG1. Our data also demonstrate that both allotypic variability and antibody specificity are important for fine-tuning of activities, an important information for the development of future therapeutics.

The evolving development landscape of biotherapeutics and their growing complexity from simple antibodies into bi- and multi-specific molecules necessitates sophisticated discovery and engineering platforms. This review focuses on mammalian display technology as a potential solution to the pressing challenges in biotherapeutic development. We provide a comparative analysis with established methodologies, highlighting key aspects of mammalian display technology, including genetic engineering, construction of display libraries, and its pivotal role in hit selection and/or developability engineering. The review delves into the mechanisms underpinning developability-driven selection via mammalian display and their broader implications. Applications beyond antibody discovery are also explored, alongside advancements towards function-first screening technologies, precision genome engineering and AI/ML-enhanced libraries, situating them in the context of mammalian display. Overall, the review provides a comprehensive overview of the current mammalian display technology landscape, underscores the expansive potential of the technology for biotherapeutic development, addresses the critical challenges for the full realisation of this potential, and examines advances in related disciplines that might impact the future application of mammalian display technologies.

Abstract Background Nanobodies, also known as VHH or single-domain antibodies, are unique antibody fragments derived solely from heavy chains. They offer advantages of small molecules and conventional antibodies, making them promising therapeutics. The paratope is the specific region on an antibody that binds to an antigen. Paratope prediction involves the identification and characterization of the antigen-binding site on an antibody. This process is crucial for understanding the specificity and affinity of antibody-antigen interactions. Various computational methods and experimental approaches have been developed to predict and analyze paratopes, contributing to advancements in antibody engineering, drug development, and immunotherapy. However, existing predictive models trained on traditional antibodies may not be suitable for nanobodies. Additionally, the limited availability of nanobody datasets poses challenges in constructing accurate models. Methods To address these challenges, we have developed a novel nanobody prediction model, named NanoBERTa-ASP (Antibody Specificity Prediction), which is specifically designed for predicting nanobody-antigen binding sites. The model adopts a training strategy more suitable for nanobodies, based on an advanced natural language processing (NLP) model called BERT (Bidirectional Encoder Representations from Transformers). To be more specific, the model utilizes a masked language modeling approach named RoBERTa (Robustly Optimized BERT Pretraining Approach) to learn the contextual information of the nanobody sequence and predict its binding site. Results NanoBERTa-ASP achieved exceptional performance in predicting nanobody binding sites, outperforming existing methods, indicating its proficiency in capturing sequence information specific to nanobodies and accurately identifying their binding sites. Furthermore, NanoBERTa-ASP provides insights into the interaction mechanisms between nanobodies and antigens, contributing to a better understanding of nanobodies and facilitating the design and development of nanobodies with therapeutic potential. Conclusion NanoBERTa-ASP represents a significant advancement in nanobody paratope prediction. Its superior performance highlights the potential of deep learning approaches in nanobody research. By leveraging the increasing volume of nanobody data, NanoBERTa-ASP can further refine its predictions, enhance its performance, and contribute to the development of novel nanobody-based therapeutics. Github repository: https://github.com/WangLabforComputationalBiology/NanoBERTa-ASP

Abstract Synthetic antibodies (Abs) represent a category of artificial proteins capable of closely emulating the functions of natural Abs. Their in vitro production eliminates the need for an immunological response, streamlining the process of Ab discovery, engineering, and development. These artificially engineered Abs offer novel approaches to antigen recognition, paratope site manipulation, and biochemical/biophysical enhancements. As a result, synthetic Abs are fundamentally reshaping conventional methods of Ab production. This mirrors the revolution observed in molecular biology and genomics as a result of deep sequencing, which allows for the swift and cost-effective sequencing of DNA and RNA molecules at scale. Within this framework, deep sequencing has enabled the exploration of whole genomes and transcriptomes, including particular gene segments of interest. Notably, the fusion of synthetic Ab discovery with advanced deep sequencing technologies is redefining the current approaches to Ab design and development. Such combination offers opportunity to exhaustively explore Ab repertoires, fast-tracking the Ab discovery process, and enhancing synthetic Ab engineering. Moreover, advanced computational algorithms have the capacity to effectively mine big data, helping to identify Ab sequence patterns/features hidden within deep sequencing Ab datasets. In this context, these methods can be utilized to predict novel sequence features thereby enabling the successful generation of de novo Ab molecules. Hence, the merging of synthetic Ab design, deep sequencing technologies, and advanced computational models heralds a new chapter in Ab discovery, broadening our comprehension of immunology and streamlining the advancement of biological therapeutics.

A critical attribute of therapeutic antibodies is their ability to engage with humoral or cellular effector mechanisms, and this depends on the ability of the Fc region to bind to complement (C1q) or Fc receptors. Investigators have sought to optimize these effects by engineering the Fc region to bind to a greater or lesser extent to individual receptors. Different approaches have been used in the clinic, but they have not been systematically compared. We have now produced a matched set of anti-CD20 antibodies representing a range of variants and compared their activity in cell-based assays for complement-dependent cytotoxicity, antibody-dependent cell-mediated cytotoxicity, and antibody-dependent phagocytosis using a range of individual Fc receptors. We have also compared the thermal stability of the variants by differential scanning fluorimetry (DSF). The results reveal a spectrum of activities which may be appropriate for different applications.

Elimination of the binding of immunoglobulin Fc to Fc gamma receptors is highly desirable for the avoidance of unwanted inflammatory responses to therapeutic antibodies and fusion proteins. Many different approaches have been used in the clinic, but they have not been systematically compared. We have now produced a matched set of anti-CD20 antibodies with different Fc subclasses and variants and compared their activity for binding to C1q, Fc-gamma receptors and in cell-based assays. Most of the variants still have significant levels of activity in one or more of these assays and many of them have impaired temperature stability compared with the corresponding wild-type antibody.

T cell engagers (TCEs) are becoming an integral class of biological therapeutic owing to their highly potent ability to eradicate cancer cells. Nevertheless, the widespread utility of classical CD3-targeted TCEs has been limited by narrow therapeutic index (TI) linked to systemic CD4+ T cell activation and aberrant cytokine release. One attractive approach to circumvent the systemic activation of pan CD3+ T cells and reduce the risk of cytokine release syndrome is to redirect specific subsets of T cells. A promising strategy is the use of peptide-major histocompatibility class I bispecific antibodies (pMHC-IgGs), which have emerged as an intriguing modality of TCE, based on their ability to selectively redirect highly reactive viral-specific effector memory cytotoxic CD8+ T cells to eliminate cancer cells. However, the relatively low frequency of these effector memory cells in human peripheral blood mononuclear cells (PBMCs) may hamper their redirection as effector cells for clinical applications. To mitigate this potential limitation, we report here the generation of a pMHC-IgG derivative known as guided-pMHC-staging (GPS) carrying a covalent fusion of a monovalent interleukin-2 (IL-2) mutein (H16A, F42A). Using an anti-epidermal growth factor receptor (EGFR) arm as a proof-of-concept, tumor-associated antigen paired with a single-chain HLA-A *02:01/CMVpp65 pMHC fusion moiety, we demonstrate in vitro that the IL-2-armored GPS modality robustly expands CMVpp65-specific CD8+ effector memory T cells and induces potent cytotoxic activity against target cancer cells. Similar to GPS, IL-2-armored GPS molecules induce modulated T cell activation and reduced cytokine release profile compared to an analogous CD3-targeted TCE. In vivo we show that IL-2-armored GPS, but not the corresponding GPS, effectively expands grafted CMVpp65 CD8+ T cells from unstimulated human PBMCs in an NSG mouse model. Lastly, we demonstrate that the IL-2-armored GPS modality exhibits a favorable developability profile and monoclonal antibody-like pharmacokinetic properties in human neonatal Fc receptor transgenic mice. Overall, IL-2-armored GPS represents an attractive approach for treating cancer with the potential for inducing vaccine-like antiviral T cell expansion, immune cell redirection as a TCE, and significantly widened TI due to reduced cytokine release.

T-cell engaging (TCE) bispecific antibodies are potent drugs that trigger the immune system to eliminate cancer cells, but administration can be accompanied by toxic side effects that limit dosing. TCEs function by binding to cell surface receptors on T cells, frequently CD3, with one arm of the bispecific antibody while the other arm binds to cell surface antigens on cancer cells. On-target, off-tumor toxicity can arise when the target antigen is also present on healthy cells. The toxicity of TCEs may be ameliorated through the use of pro-drug forms of the TCE, which are not fully functional until recruited to the tumor microenvironment. This can be accomplished by masking the anti-CD3 arm of the TCE with an autoinhibitory motif that is released by tumor-enriched proteases. Here, we solve the crystal structure of the antigen-binding fragment of a novel anti-CD3 antibody, E10, in complex with its epitope from CD3 and use this information to engineer a masked form of the antibody that can activate by the tumor-enriched protease matrix metalloproteinase 2 (MMP-2). We demonstrate with binding experiments and in vitro T-cell activation and killing assays that our designed prodrug TCE is capable of tumor-selective T-cell activity that is dependent upon MMP-2. Furthermore, we demonstrate that a similar masking strategy can be used to create a pro-drug form of the frequently used anti-CD3 antibody SP34. This study showcases an approach to developing immune-modulating therapeutics that prioritizes safety and has the potential to advance cancer immunotherapy treatment strategies.

ABSTRACTEarly identification of antibody candidates with drug-like properties is essential for simplifying the development of safe and effective antibody therapeutics. For subcutaneous administration, it is important to identify candidates with low self-association to enable their formulation at high concentration while maintaining low viscosity, opalescence, and aggregation. Here, we report an interpretable machine learning model for predicting antibody (IgG1) variants with low viscosity using only the sequences of their variable (Fv) regions. Our model was trained on antibody viscosity data (>100 mg/mL mAb concentration) obtained at a common formulation pH (pH 5.2), and it identifies three key Fv features of antibodies linked to viscosity, namely their isoelectric points, hydrophobic patch sizes, and numbers of negatively charged patches. Of the three features, most predicted antibodies at risk for high viscosity, including antibodies with diverse antibody germlines in our study (79 mAbs) as well as clinical-stage IgG1s (94 mAbs), are those with low Fv isoelectric points (Fv pIs

ABSTRACTEpithelial cell adhesion molecule (EpCAM) is a transmembrane glycoprotein that plays several roles in cancer biology. EpCAM is an attractive therapeutic target because of its expression in most solid tumors. However, targeting EpCAM has been challenging because it is also highly expressed in normal epithelial tissues. Initial attempts to develop EpCAM-specific T-cell engagers were unsuccessful due to severe cytokine release effects, as well as serious on-target, off-tumor drug-related toxicities. We developed novel, conditionally active biological (CAB) bispecific antibodies that bind to both EpCAM and CD3 in an acidic tumor microenvironment. In healthy tissues, binding to EpCAM and CD3 is greatly reduced by a novel, dual CAB selection, where each binding domain is independently blocked by the presence of physiological chemicals known as Protein-associated Chemical Switches (PaCS). The CAB anti-EpCAM T-cell engagers displayed the anticipated bispecific binding properties and mediated the potent lysis of EpCAM-positive cancer cell lines through the recruitment of T cells in the tumor microenvironment. Xenograft studies showed that the efficacy of CAB bispecific antibodies is similar to that of a non-CAB anti-EpCAM bispecific antibody, but they have markedly reduced toxicity in non-human primates, indicating an unprecedentedly widened therapeutic index of over 100-fold. These preclinical results indicate that the dual CAB bispecific antibody is potentially both a powerful and safe therapeutic platform and a promising T cell-engaging treatment for patients with EpCAM-expressing tumors.

ABSTRACTBiparatopic antibodies (bpAbs) bind distinct, non-overlapping epitopes on an antigen. This unique binding mode enables new mechanisms of action beyond monospecific and bispecific antibodies (bsAbs) that can make bpAbs effective therapeutics for various indications, including oncology and infectious diseases. Biparatopic binding can lead to superior affinity and specificity, promote antagonism, lock target conformation, and result in higher-order target clustering. Such antibody-target complexes can elicit strong agonism, increase immune effector function, or result in rapid target downregulation and lysosomal trafficking. These are not only attractive properties for therapeutic antibodies but are increasingly being explored for other modalities such as antibody-drug conjugates, T-cell engagers and chimeric antigen receptors. Recent advances in bpAb engineering have enabled the construction of ever more sophisticated formats that are starting to show promise in the clinic.

ABSTRACTA major driver for the recent investment surge in bispecific antibody (bsAb) platforms and products is the multitude of distinct mechanisms of action that bsAbs offer compared to a combination of two monoclonal antibodies. Four bsAb products were granted first regulatory approvals in the US or EU during 2023 and the biopharmaceutical industry pipeline is brimming with bsAb candidates across a broad range of therapeutic applications. In previously reported bsAb discovery campaigns, following a hypothesis-based choice of two specific target proteins, selections and screening activities have often been performed in mono-specific formats. The conversion to bispecific modalities has usually been positioned toward the end of the discovery process and has involved small numbers of lead molecules, largely due to challenges in expressing, purifying, and analyzing large numbers of bsAbs. In this review, we discuss emerging strategies to facilitate the production of expanded bsAb panels, focusing particularly upon combinatorial methods to generate bsAb matrices. Such technologies will enable screening in. bispecific formats at earlier stages of discovery campaigns, not only widening the accessible protein space to maximize chances of success, but also advancing empirical bi-target validation activities to assess initial target selection hypotheses.

ABSTRACTNatural killer (NK) cells emerged as a promising effector population that can be harnessed for anti-tumor therapy. In this work, we constructed NK cell engagers (NKCEs) based on NKp30-targeting single domain antibodies (sdAbs) that redirect the cytotoxic potential of NK cells toward epidermal growth factor receptor (EGFR)-expressing tumor cells. We investigated the impact of crucial parameters such as sdAb location, binding valencies, the targeted epitope on NKp30, and the overall antibody architecture on the redirection capacity. Our study exploited two NKp30-specific sdAbs, one of which binds a similar epitope on NKp30 as its natural ligand B7-H6, while the other sdAb addresses a non-competing epitope. For EGFR-positive tumor targeting, humanized antigen-binding domains of therapeutic antibody cetuximab were used. We demonstrate that NKCEs bivalently targeting EGFR and bivalently engaging NKp30 are superior to monovalent NKCEs in promoting NK cell-mediated tumor cell lysis and that the architecture of the NKCE can substantially influence killing capacities depending on the NKp30-targeting sdAb utilized. While having a pronounced impact on NK cell killing efficacy, the capabilities of triggering antibody-dependent cellular phagocytosis or complement-dependent cytotoxicity were not significantly affected comparing the bivalent IgG-like NKCEs with cetuximab. However, the fusion of sdAbs can have a slight impact on the NK cell release of immunomodulatory cytokines, as well as on the pharmacokinetic profile of the NKCE due to unfavorable spatial orientation within the molecule architecture. Ultimately, our findings reveal novel insights for the engineering of potent NKCEs triggering the NKp30 axis.

ABSTRACTOff-target biodistribution of biologics bears important toxicological consequences. Antibody fragments intended for use as vectors of cytotoxic payloads (e.g. antibody-drug conjugates, radiotherapy) can accumulate at clearance organs like kidneys and liver, where they can cause dose-limiting toxicities. Renal and hepatic uptakes are known to be affected by protein electrostatics, which promote protein internalization through pinocytosis. Using minibodies as a model of an antibody fragment lacking FcRn recycling, we compared the biodistributions of leads with different degrees of accumulation at the kidney and liver. We identified a positive electrostatic patch highly conserved in a germline family very commonly used in the humanization of approved biologics. Neutralization of this patch led to a drastic reduction in the kidney uptake, leading to a biodistribution more favorable to the delivery of highly cytotoxic payloads. Next, we conducted a high throughput study of the electrostatic properties for all combinations of VH and VL germlines. This analysis shows how different VH/VL combinations exhibit varying tendencies to create electrostatic patches, resulting in Fv variants with different isoelectric points. Our work emphasizes the importance of carefully selecting germlines for humanization with optimal electrostatic properties in order to control the unspecific tissue uptake of low molecular weight biologics.

ABSTRACTOptimal combinations of paratopes assembled into a biparatopic antibody have the capacity to mediate high-grade target cross-linking on cell membranes, leading to degradation of the target, as well as antibody and payload delivery in the case of an antibody-drug conjugate (ADC). In the work presented here, molecular docking suggested a suitable paratope combination targeting c-MET, but hydrophobic patches in essential binding regions of one moiety necessitated engineering. In addition to rational design of HCDR2 and HCDR3 mutations, site-specific spiking libraries were generated and screened in yeast and mammalian surface display approaches. Comparative analyses revealed similar positions amendable for hydrophobicity reduction, with a broad combinatorial diversity obtained from library outputs. Optimized variants showed high stability, strongly reduced hydrophobicity, retained affinities supporting the desired functionality and enhanced producibility. The resulting biparatopic anti-c-MET ADCs were comparably active on c-MET expressing tumor cell lines as REGN5093 exatecan DAR6 ADC. Structural molecular modeling of paratope combinations for preferential inter-target binding combined with protein engineering for manufacturability yielded deep insights into the capabilities of rational and library approaches. The methodologies of in silico hydrophobicity identification and sequence optimization could serve as a blueprint for rapid development of optimal biparatopic ADCs targeting further tumor-associated antigens in the future.

Equine-derived antitoxin (BAT®) is the only treatment for botulism from botulinum neurotoxin serotype G (BoNT/G). BAT® is a foreign protein with potentially severe adverse effects and is not renewable. To develop a safe, more potent, and renewable antitoxin, humanized monoclonal antibodies (mAbs) were generated. Yeast displayed single chain Fv (scFv) libraries were prepared from mice immunized with BoNT/G and BoNT/G domains and screened with BoNT/G using fluorescence-activated cell sorting (FACS). Fourteen scFv-binding BoNT/G were isolated with KD values ranging from 3.86 nM to 103 nM (median KD 20.9 nM). Five mAb-binding non-overlapping epitopes were humanized and affinity matured to create antibodies hu6G6.2, hu6G7.2, hu6G9.1, hu6G10, and hu6G11.2, with IgG KD values ranging from 51 pM to 8 pM. Three IgG combinations completely protected mice challenged with 10,000 LD50s of BoNT/G at a total mAb dose of 6.25 μg per mouse. The mAb combinations have the potential for use in the diagnosis and treatment of botulism due to serotype G and, along with antibody combinations to BoNT/A, B, C, D, E, and F, provide the basis for a fully recombinant heptavalent botulinum antitoxin to replace the legacy equine product.

Previously, we reported a neutralizing monoclonal antibody, A8A11, raised against a novel conserved epitope within the hepatitis C virus (HCV) E2 protein, that could significantly reduce HCV replication. Here, we report the nucleotide sequence of A8A11 and demonstrate the efficacy of a single-chain variable fragment (scFv) protein that mimics the antibody, inhibits the binding of an HCV virus-like particle to hepatocytes, and reduces viral RNA replication in a cell culture system. More importantly, scFv A8A11 was found to effectively restrict the increase of viral RNA levels in the serum of HCV-infected chimeric mice harbouring human hepatocytes. These results suggest a promising approach to neutralizing-antibody-based therapeutic interventions against HCV infection. [ABSTRACT FROM AUTHOR]

The 21st‐century beginning remarked with the huge success of monospecific MAbs, however, in the last couple of years, polyspecific MAbs (PsAbs) have been an interesting topic and show promise of being biobetter than monospecific MAbs. Polyspecificity, in which a single antibody serves multiple specific target binding, has been hypothesized to contribute to the development of a highly effective antibody repertoire for immune defence. This polyspecific MAb trend represents an explosion that is gripping the whole pharmaceutical industry. This review is concerned with the current development and quality enforcement of PsAbs. All provided literature on monospecific MAbs and polyspecific MAbs (PsAbs) were searched using various electronic databases such as PubMed, Google Scholar, Web of Science, Elsevier, Springer, ACS, Google Patent and books via the keywords Antibody engineering, Polyspecific antibody, Conventional antibody, non‐conventional antibody, and Single domain antibody. In the literature, there are more than 100 different formats to construct PsAb by quadroma technology, chemical conjugation and genetic engineering. Till March 2023, nine PsAb have been approved around the world, and around 330 are in advanced developmental stages, showing the dominancy of PsAb in the growing health sector. Recent advancements in protein engineering techniques and the fusion of non‐conventional antibodies have made it possible to create complex PsAbs that demonstrate higher stability and enhanced potency. This marks the most significant achievement for cancer immunotherapy, in which PsAbs have immense promise. It is worth mentioning that seven out of the nine PsAbs have been approved as anti‐cancer therapy. As PsAbs continue to acquire prominence, they could pave the way for the development of novel immunotherapies for multiple diseases. [ABSTRACT FROM AUTHOR]

Background: Nanobodies, also known as VHH or single-domain antibodies, are unique antibody fragments derived solely from heavy chains. They offer advantages of small molecules and conventional antibodies, making them promising therapeutics. The paratope is the specific region on an antibody that binds to an antigen. Paratope prediction involves the identification and characterization of the antigen-binding site on an antibody. This process is crucial for understanding the specificity and affinity of antibody-antigen interactions. Various computational methods and experimental approaches have been developed to predict and analyze paratopes, contributing to advancements in antibody engineering, drug development, and immunotherapy. However, existing predictive models trained on traditional antibodies may not be suitable for nanobodies. Additionally, the limited availability of nanobody datasets poses challenges in constructing accurate models. Methods: To address these challenges, we have developed a novel nanobody prediction model, named NanoBERTa-ASP (Antibody Specificity Prediction), which is specifically designed for predicting nanobody-antigen binding sites. The model adopts a training strategy more suitable for nanobodies, based on an advanced natural language processing (NLP) model called BERT (Bidirectional Encoder Representations from Transformers). To be more specific, the model utilizes a masked language modeling approach named RoBERTa (Robustly Optimized BERT Pretraining Approach) to learn the contextual information of the nanobody sequence and predict its binding site. Results: NanoBERTa-ASP achieved exceptional performance in predicting nanobody binding sites, outperforming existing methods, indicating its proficiency in capturing sequence information specific to nanobodies and accurately identifying their binding sites. Furthermore, NanoBERTa-ASP provides insights into the interaction mechanisms between nanobodies and antigens, contributing to a better understanding of nanobodies and facilitating the design and development of nanobodies with therapeutic potential. Conclusion: NanoBERTa-ASP represents a significant advancement in nanobody paratope prediction. Its superior performance highlights the potential of deep learning approaches in nanobody research. By leveraging the increasing volume of nanobody data, NanoBERTa-ASP can further refine its predictions, enhance its performance, and contribute to the development of novel nanobody-based therapeutics. Github repository: https://github.com/WangLabforComputationalBiology/NanoBERTa-ASP [ABSTRACT FROM AUTHOR]

Synthetic antibodies (Abs) represent a category of artificial proteins capable of closely emulating the functions of natural Abs. Their in vitro production eliminates the need for an immunological response, streamlining the process of Ab discovery, engineering, and development. These artificially engineered Abs offer novel approaches to antigen recognition, paratope site manipulation, and biochemical/biophysical enhancements. As a result, synthetic Abs are fundamentally reshaping conventional methods of Ab production. This mirrors the revolution observed in molecular biology and genomics as a result of deep sequencing, which allows for the swift and cost-effective sequencing of DNA and RNA molecules at scale. Within this framework, deep sequencing has enabled the exploration of whole genomes and transcriptomes, including particular gene segments of interest. Notably, the fusion of synthetic Ab discovery with advanced deep sequencing technologies is redefining the current approaches to Ab design and development. Such combination offers opportunity to exhaustively explore Ab repertoires, fast-tracking the Ab discovery process, and enhancing synthetic Ab engineering. Moreover, advanced computational algorithms have the capacity to effectively mine big data, helping to identify Ab sequence patterns/features hidden within deep sequencing Ab datasets. In this context, these methods can be utilized to predict novel sequence features thereby enabling the successful generation of de novo Ab molecules. Hence, the merging of synthetic Ab design, deep sequencing technologies, and advanced computational models heralds a new chapter in Ab discovery, broadening our comprehension of immunology and streamlining the advancement of biological therapeutics. [ABSTRACT FROM AUTHOR]

The use of human antibodies as biologic therapeutics has revolutionized patient care throughout fields of medicine. As our understanding of the many roles antibodies play within our natural immune responses continues to advance, so will the number of therapeutic indications for which an mAb will be developed. The great breadth of function, long half-life, and modular structure allow for nearly limitless therapeutic possibilities. Human antibodies can be rationally engineered to enhance their desired immune functions and eliminate those that may result in unwanted effects. Antibody therapeutics now often start with fully human variable regions, either acquired from genetically engineered humanized mice or from the actual human B cells. These variable genes can be further engineered by widely used methods for optimization of their specificity through affinity maturation, random mutagenesis, targeted mutagenesis, and use of in silico approaches. Antibody isotype selection and deliberate mutations are also used to improve efficacy and tolerability by purposeful fine-tuning of their immune effector functions. Finally, improvements directed at binding to the neonatal Fc receptor can endow therapeutic antibodies with unbelievable extensions in their circulating half-life. The future of engineered antibody therapeutics is bright, with the global mAb market projected to exhibit compound annual growth, forecasted to reach a revenue of nearly half a trillion dollars in 2030. [ABSTRACT FROM AUTHOR]

ABSTRACT Monoclonal antibodies (mAbs) are an attractive therapeutic platform for the prevention and treatment of influenza virus infection. There are two major glycoproteins on the influenza virion surface: hemagglutinin (HA), which is responsible for viral attachment and entry, and neuraminidase (NA), which mediates viral egress by enzymatically cleaving sialic acid to release budding particles from the host cell surface. Broadly neutralizing antibodies (bNAbs) that target the conserved HA central stalk region, such as CR9114, can inhibit both viral entry and egress. More recently, broadly binding mAbs that engage and inhibit the NA active site, such as 1G01, have been described to prevent viral egress. Here, we engineered bispecific antibodies (bsAbs) that combine the variable domains of CR9114 and 1G01 into a single molecule and evaluated if simultaneous targeting of two different glycoproteins improved antiviral properties in vitro and in vivo. Several CR9114/1G01 bsAbs were generated with various configurations of the two sets of the variable domains (“bsAb formats”). We found that combinations employing the addition of a single-chain variable fragment in the hinge region of an IgG scaffold had the best properties in terms of expression, stability, and binding. Further characterization of selected bsAbs showed potent neutralizing and egress-inhibiting activity. One such bsAb (“hSC_CR9114_1G01”) provided higher levels of prophylactic protection from mortality and morbidity upon challenge with H1N1 than either of the parental mAbs at low dosing (1 mg/kg). These results highlight the potential use of bsAbs that simultaneously target HA and NA as new influenza immunotherapeutics.IMPORTANCEInfection by the influenza virus remains a global health burden. The approaches utilized here to augment the activity of broadly protective influenza virus antibodies may lead to a new class of immunotherapies with enhanced activity.

Targeted degradation of pathological proteins is a promising approach to enhance the effectiveness of therapeutic monoclonal antibodies (mAbs) in cancer therapy. In this study, we demonstrate that this objective can be efficiently achieved by the grafting of mannose 6-phosphate analogues called AMFAs22 AMFA: Analogues of the Mannose 6-phosphate Functionalized at Anomeric Position onto the therapeutic antibodies trastuzumab and cetuximab, both directed against membrane antigens. The grafting of AMFAs confers to these antibodies the novel property of being internalized via the mannose 6-phosphate receptor (M6PR) pathway. AMFA conjugation to these mAbs significantly increases their cellular uptake and leads to enhanced degradation of the target antigens in cancer cells. This results in a drastic inhibition of cancer cell proliferation compared to unconjugated mAbs, as demonstrated in various cancer cell lines, and an increased therapeutic efficacy in mouse and zebrafish xenografted models. These findings highlight the potential of this technology to improve therapeutic outcomes in cancer treatment.

The emergence of Omicron lineages and descendent subvariants continues to present a severe threat to the effectiveness of vaccines and therapeutic antibodies. We have previously suggested that an insufficient mucosal immunoglobulin A (IgA) response induced by the mRNA vaccines is associated with a surge in breakthrough infections. Here, we further show that the intramuscular mRNA and/or inactivated vaccines cannot sufficiently boost the mucosal secretory IgA response in uninfected individuals, particularly against the Omicron variant. We thus engineered and characterized recombinant monomeric, dimeric, and secretory IgA1 antibodies derived from four neutralizing IgG monoclonal antibodies (mAbs 01A05, rmAb23, DXP-604, and XG014) targeting the receptor-binding domain of the spike protein. Compared to their parental IgG antibodies, dimeric and secretory IgA1 antibodies showed a higher neutralizing activity against different variants of concern (VOCs), in part due to an increased avidity. Importantly, the dimeric or secretory IgA1 form of the DXP-604 antibody significantly outperformed its parental IgG antibody, and neutralized the Omicron lineages BA.1, BA.2, and BA.4/5 with a 25-to 75-fold increase in potency. In human angiotensin converting enzyme 2 (ACE2) transgenic mice, a single intranasal dose of the dimeric IgA DXP-604 conferred prophylactic and therapeutic protection against Omicron BA.5. Thus, dimeric or secretory IgA delivered by nasal administration may potentially be exploited for the treatment and prevention of Omicron infection, thereby providing an alternative tool for combating immune evasion by the current circulating subvariants and, potentially, future VOCs. [ABSTRACT FROM AUTHOR]

Recent years have seen an uptick in the use of computational applications in antibody engineering. These tools have enhanced our ability to predict interactions with antigens and immunogenicity, facilitate humanization, and serve other critical functions. However, several studies highlight the concern of potential trade-offs between antibody affinity and stability in antibody engineering. In this study, we analyzed anti-measles virus antibodies as a case study, to examine the relationship between binding affinity and stability, upon identifying the binding hotspots. We leverage in silico tools like Rosetta and FoldX, along with molecular dynamics (MD) simulations, offering a cost-effective alternative to traditional in vitro mutagenesis. We introduced a pattern in identifying key residues in pairs, shedding light on hotspots identification. Experimental physicochemical analysis validated the predicted key residues by confirming significant decrease in binding affinity for the high-affinity antibodies to measles virus hemagglutinin. Through the nature of the identified pairs, which represented the relative hydropathy of amino acid side chain, a connection was proposed between affinity and stability. The findings of the study enhance our understanding of the interactions between antibody and measles virus hemagglutinin. Moreover, the implications of the observed correlation between binding affinity and stability extend beyond the field of anti-measles virus antibodies, thereby opening doors for advancements in antibody research.

Therapeutic protein engineering has revolutionized medicine by enabling the development of highly specific and potent treatments for a wide range of diseases. This review examines recent advances in computational and experimental approaches for engineering improved protein therapeutics. Key areas of focus include antibody engineering, enzyme replacement therapies, and cytokine-based drugs. Computational methods like structure-based design, machine learning integration, and protein language models have dramatically enhanced our ability to predict protein properties and guide engineering efforts. Experimental techniques such as directed evolution and rational design approaches continue to evolve, with high-throughput methods accelerating the discovery process. Applications of these methods have led to breakthroughs in affinity maturation, bispecific antibodies, enzyme stability enhancement, and the development of conditionally active cytokines. Emerging approaches like intracellular protein delivery, stimulus-responsive proteins, and de novo designed therapeutic proteins offer exciting new possibilities. However, challenges remain in predicting in vivo behavior, scalable manufacturing, immunogenicity mitigation, and targeted delivery. Addressing these challenges will require continued integration of computational and experimental methods, as well as a deeper understanding of protein behavior in complex physiological environments. As the field advances, we can anticipate increasingly sophisticated and effective protein therapeutics for treating human diseases.

Secretory IgA (SIgA) presents a promising avenue for mucosal immunotherapy yet faces challenges in expression, purification, and stability. IgA exists in two primary isotypes, IgA1 and IgA2, with IgA2 further subdivided into two common allotypes: IgA2m(1) and IgA2m(2). The major differences between IgA1 and IgA2 are located in the hinge region, with IgA1 featuring a 13-amino acid elongation that includes up to six O-glycosylation sites. Furthermore, the IgA2m(1) allotype lacks a covalent disulfide bond between heavy and light chains, which is present in IgA1 and IgA2m(2). While IgA1 demonstrates superior epitope binding and pathogen neutralization, IgA2 exhibits enhanced effector functions and stability against mucosal bacterial degradation. However, the noncovalent linkage in the IgA2m(1) allotype raises production and stability challenges. The introduction of distinct single mutations aims to facilitate an alternate disulfide bond formation to mitigate these challenges. We compare four different IgA2 versions with IgA1 to further develop secretory IgA antibodies against SARS-CoV-2 for topical delivery to mucosal surfaces. Our results indicate significantly improved expression levels and assembly efficacy of SIgA2 (P221R) in Nicotiana benthamiana. Moreover, engineered SIgA2 displays heightened thermal stability under physiological as well as acidic conditions and can be aerosolized using a mesh nebulizer. In summary, our study elucidates the benefits of stability-enhancing mutations in overcoming hurdles associated with SIgA expression and stability.

Human botulism can be caused by botulinum neurotoxin (BoNT) serotypes A to G. Here, we present an antibody-based antitoxin composed of four human monoclonal antibodies (mAbs) against BoNT/C, BoNT/D, and their mosaic toxins. This work built on our success in generating protective mAbs to BoNT /A, B and E serotypes. We generated mAbs from human immune single-chain Fv (scFv) yeast-display libraries and isolated scFvs with high affinity for BoNT/C, BoNT/CD, BoNT/DC and BoNT/D serotypes. We identified four mAbs that bound non-overlapping epitopes on multiple serotypes and mosaic BoNTs. Three of the mAbs underwent molecular evolution to increase affinity. A four-mAb combination provided high-affinity binding and BoNT neutralization of both serotypes and their mosaic toxins. The mAbs have potential utility as therapeutics and as diagnostics capable of recognizing and neutralizing BoNT/C and BoNT/D serotypes and their mosaic toxins. A derivative of the four-antibody combination (NTM-1634) completed a Phase 1 clinical trial (Snow et al., Antimicrobial Agents and Chemotherapy, 2019) with no drug-related serious adverse events.

Abstract Immune cell engagers are engineered antibodies with at least one arm binding a tumor-associated antigen and at least another one directed against an activating receptor in immune effector cells: CD3 for recruitment of T cells and CD16a for NK cells. The first T cell engager (the anti-CD19 blinatumomab) was approved by the FDA in 2014, but no other one hit the market until 2022. Now the field is gaining momentum, with three approvals in 2022 and 2023 (as of May): the anti-CD20 × anti-CD3 mosunetuzumab and epcoritamab and the anti-B cell maturation antigen (BCMA) × anti-CD3 teclistamab, and another three molecules in regulatory review. T cell engagers will likely revolutionize the treatment of hematological malignancies in the short term, as they are considerably more potent than conventional monoclonal antibodies recognizing the same tumor antigens. The field is thriving, with a plethora of different formats and targets, and around 100 bispecific T cell engagers more are already in clinical trials. Bispecific NK cell engagers are also in early-stage clinical studies and may offer similar efficacy with milder side effects. Trispecific antibodies (engaging either T cell or NK cell receptors) raise the game even further with a third binding moiety, which allows either the targeting of an additional tumor-associated antigen to increase specificity and avoid immune escape or the targeting of additional costimulatory receptors on the immune cell to improve its effector functions. Altogether, these engineered molecules may change the paradigm of treatment for relapsed or refractory hematological malignancies.

Antibody maturation is the central function of the adaptive immune response. This process is driven by the repetitive selection of mutations that increase the affinity toward antigens. We hypothesized that a precise observation of this process by high-throughput sequencing along the time course of immunization will enable us to predict the antibodies reacting to the immunized antigen without any additional in vitro screening. An alpaca was immunized with IgG fragments using multiple antigen injections, and the antibody repertoire development was traced via high-throughput sequencing periodically for months. The sequences were processed into clusters, and the antibodies in the 16 most abundant clusters were generated to determine whether the clusters included antigen-binding antibodies. The sequences of most antigen-responsive clusters resembled those of germline cells in the early stages. These sequences were observed to accumulate significant mutations and also showed a continuous sequence turnover throughout the experimental period. The foregoing characteristics gave us >80% successful prediction of clusters composed of antigen-responding VHHs against IgG fragment. Furthermore, when the prediction method was applied to the data from other alpaca immunized with epidermal growth factor receptor, the success rate exceeded 80% as well, confirming the general applicability of the prediction method. Superior to previous studies, we identified the immune-responsive but very rare clusters or sequences from the immunized alpaca without any empirical screening data.

ABSTRACTIn this study, we generated a novel library approach for high throughput de novo identification of humanized single-domain antibodies following camelid immunization. To achieve this, VHH-derived complementarity-determining regions-3 (CDR3s) obtained from an immunized llama (Lama glama) were grafted onto humanized VHH backbones comprising moderately sequence-diversified CDR1 and CDR2 regions similar to natural immunized and naïve antibody repertoires. Importantly, these CDRs were tailored toward favorable in silico developability properties, by considering human-likeness as well as excluding potential sequence liabilities and predicted immunogenic motifs. Target-specific humanized single-domain antibodies (sdAbs) were readily obtained by yeast surface display. We demonstrate that, by exploiting this approach, high affinity sdAbs with an optimized in silico developability profile can be generated. These sdAbs display favorable biophysical, biochemical, and functional attributes and do not require any further sequence optimization. This approach is generally applicable to any antigen upon camelid immunization and has the potential to significantly accelerate candidate selection and reduce risks and attrition rates in sdAb development.

ABSTRACTTherapeutic antibodies sometimes elicit anti-drug antibodies (ADAs) that can affect efficacy and safety. Engineered antibodies that contain artificial amino acid sequences are potentially highly immunogenic, but this is currently difficult to predict. Therefore, it is important to efficiently assess immunogenicity during the development of complex antibody-based formats. Here, we present an in vitro peripheral blood mononuclear cell-based assay that can be used to assess immunogenicity potential within 3 days. This method involves examining the frequency and function of interleukin (IL)-2-secreting CD4+ T cells induced by therapeutic antibodies. IL-2-secreting CD4+ T cells seem to be functionally relevant to the immunogenic potential due to their proliferative activity and the expression of several cytokines. The rates of the donors responding to low and high immunogenic proteins, mAb1, and keyhole limpet hemocyanin were 1.3% and 93.5%, respectively. Seven antibodies with known rates of immunogenicity (etanercept, emicizumab, abciximab, romosozumab, blosozumab, humanized anti-human A33 antibody, and bococizumab) induced responses in 1.9%, 3.8%, 6.4%, 10.0%, 29.2%, 43.8%, and 89.5% of donors, respectively. These data are comparable with ADA incidences in clinical settings. Our results show that this assay can contribute to the swift assessment and mechanistic understanding of the immunogenicity of therapeutic antibodies.

ABSTRACTAntibody-cytokine fusions targeted against tumor-associated antigens (TAAs) are promising cancer immunotherapy agents, with many such molecules currently undergoing clinical trials. However, due to the limited number of tumor-specific targets, on-target off-tumor effects can lead to systemic toxicity. Additionally, targeted cytokines can be scavenged by cytokine receptors on peripheral cells, decreasing tumor penetration. This study aims at overcoming these issues by engineering a platform for targeted conditionally active type I cytokines. Building on our previously reported PACE (Prodrug-Activating Chain Exchange) platform, we split the type I cytokine interleukin-4 (IL-4) to create two inactive IL-4 prodrugs, and fused these split IL-4 counterparts to the C-termini of antibody-like molecules that undergo proximity-induced chain exchange. In doing so, we developed IL-4 prodrugs that preferentially reconstitute into active IL-4 on target cells. We demonstrate that pre-assembled split IL-4 (without additional inactivation) retains activity and present two different strategies of splitting and inactivating IL-4. Using an IL-4 responsive cell-line, we show that IL-4 prodrugs are targeted to TAAs on target cells and regain activity upon chain exchange, primarily in a cis-activation setting. Furthermore, we demonstrate that split IL-4 complementation is also possible in a trans-activation setting, which opens up the possibility for activation of immune cells in the tumor vicinity. We demonstrate that targeted on-cell prodrug conversion is more efficient than nonspecific activation in-solution. Due to the structural similarity between IL-4 and other type I cytokines relevant in cancer immunotherapy such as IL-2, IL-15, and IL-21, cytokine-PACE may be expanded to develop a variety of targeted conditionally active cytokines for cancer immunotherapy.

ABSTRACTAntibodies are one of the predominant treatment modalities for various diseases. To improve the characteristics of a lead antibody, such as antigen-binding affinity and stability, we conducted comprehensive substitutions and exhaustively explored their sequence space. However, it is practically unfeasible to evaluate all possible combinations of mutations owing to combinatorial explosion when multiple amino acid residues are incorporated. It was recently reported that a machine-learning guided protein engineering approach such as Thompson sampling (TS) has been used to efficiently explore sequence space in the framework of Bayesian optimization. For TS, over-exploration occurs when the initial data are biasedly distributed in the vicinity of the lead antibody. We handle a large-scale virtual library that includes numerous mutations. When the number of experiments is limited, this over-exploration causes a serious issue. Thus, we conducted Monte Carlo Thompson sampling (MTS) to balance the exploration-exploitation trade-off by defining the posterior distribution via the Monte Carlo method and compared its performance with TS in antibody engineering. Our results demonstrated that MTS largely outperforms TS in discovering desirable candidates at an earlier round when over-exploration occurs on TS. Thus, the MTS method is a powerful technique for efficiently discovering antibodies with desired characteristics when the number of rounds is limited.