Adaptive multi-epitope targeting and avidity-enhanced nanobody platform for ultrapotent, durable antiviral therapy.

Pathogens constantly evolve and can develop mutations that evade host immunity and treatment. Addressing these escape mechanisms requires targeting evolutionarily conserved vulnerabilities, as mutations in these regions often impose fitness costs. We introduce adaptive multi-epitope targeting with enhanced avidity (AMETA), a modular and multivalent nanobody platform that conjugates potent bispecific nanobodies to a human immunoglobulin M (IgM) scaffold. AMETA can display 20+ nanobodies, enabling superior avidity binding to multiple conserved and neutralizing epitopes. By leveraging multi-epitope SARS-CoV-2 nanobodies and structure-guided design, AMETA constructs exponentially enhance antiviral potency, surpassing monomeric nanobodies by over a million-fold. These constructs demonstrate ultrapotent, broad, and durable efficacy against pathogenic sarbecoviruses, including Omicron sublineages, with robust preclinical results. Structural analysis through cryoelectron microscopy and modeling has uncovered multiple antiviral mechanisms within a single construct. At picomolar to nanomolar concentrations, AMETA efficiently induces inter-spike and inter-virus cross-linking, promoting spike post-fusion and striking viral disarmament. AMETA's modularity enables rapid, cost-effective production and adaptation to evolving pathogens.

An Allosteric Anti-tryptase Antibody for the Treatment of Mast Cell-Mediated Severe Asthma.

Severe asthma patients with low type 2 inflammation derive less clinical benefit from therapies targeting type 2 cytokines and represent an unmet need. We show that mast cell tryptase is elevated in severe asthma patients independent of type 2 biomarker status. Active ß-tryptase allele count correlates with blood tryptase levels, and asthma patients carrying more active alleles benefit less from anti-IgE treatment. We generated a noncompetitive inhibitory antibody against human ß-tryptase, which dissociates active tetramers into inactive monomers. A 2.15 Å crystal structure of a ß-tryptase/antibody complex coupled with biochemical studies reveal the molecular basis for allosteric destabilization of small and large interfaces required for tetramerization. This anti-tryptase antibody potently blocks tryptase enzymatic activity in a humanized mouse model, reducing IgE-mediated systemic anaphylaxis, and inhibits airway tryptase in Ascaris-sensitized cynomolgus monkeys with favorable pharmacokinetics. These data provide a foundation for developing anti-tryptase as a clinical therapy for severe asthma.

A Fc engineering approach to define functional humoral correlates of immunity against Ebola virus.

Protective Ebola virus (EBOV) antibodies have neutralizing activity and induction of antibody constant domain (Fc)-mediated innate immune effector functions. Efforts to enhance Fc effector functionality often focus on maximizing antibody-dependent cellular cytotoxicity, yet distinct combinations of functions could be critical for antibody-mediated protection. As neutralizing antibodies have been cloned from EBOV disease survivors, we sought to identify survivor Fc effector profiles to help guide Fc optimization strategies. Survivors developed a range of functional antibody responses, and we therefore applied a rapid, high-throughput Fc engineering platform to define the most protective profiles. We generated a library of Fc variants with identical antigen-binding fragments (Fabs) from an EBOV neutralizing antibody. Fc variants with antibody-mediated complement deposition and moderate natural killer (NK) cell activity demonstrated complete protective activity in a stringent in vivo mouse model. Our findings highlight the importance of specific effector functions in antibody-mediated protection, and the experimental platform presents a generalizable resource for identifying correlates of immunity to guide therapeutic antibody design.

Living in LALA land? Forty years of attenuating Fc effector functions.

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.

Conversion of monoclonal IgG to dimeric and secretory IgA restores neutralizing ability and prevents infection of Omicron lineages.

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.

Complement contributes to antibody-mediated protection against repeated SHIV challenge.

The first clinical efficacy trials of a broadly neutralizing antibody (bNAb) resulted in less benefit than expected and suggested that improvements are needed to prevent HIV infection. While considerable effort has focused on optimizing neutralization breadth and potency, it remains unclear whether augmenting the effector functions elicited by broadly neutralizing antibodies (bNAbs) may also improve their clinical potential. Among these effector functions, complement-mediated activities, which can culminate in the lysis of virions or infected cells, have been the least well studied. Here, functionally modified variants of the second-generation bNAb 10-1074 with ablated and enhanced complement activation profiles were used to examine the role of complement-associated effector functions. When administered prophylactically against simian-HIV challenge in rhesus macaques, more bNAb was required to prevent plasma viremia when complement activity was eliminated. Conversely, less bNAb was required to protect animals from plasma viremia when complement activity was enhanced. These results suggest that complement-mediated effector functions contribute to in vivo antiviral activity, and that their engineering may contribute to the further improvements in the efficacy of antibody-mediated prevention strategies.

A new generation of nanobody research tools using improved mass spectrometry-based discovery methods.

Single-domain antibodies ("nanobodies") derived from the variable region of camelid heavy-chain only antibody variants have proven to be widely useful tools for research, therapeutic, and diagnostic applications. In addition to traditional display techniques, methods to generate nanobodies using direct detection by mass spectrometry and DNA sequencing have been highly effective. However, certain technical challenges have limited widespread application. We have optimized a new pipeline for this approach that greatly improves screening sensitivity, depth of antibody coverage, antigen compatibility, and overall hit rate and affinity. We have applied this improved methodology to generate significantly higher affinity nanobody repertoires against widely used targets in biological research-i.e., GFP, tdTomato, GST, and mouse, rabbit, and goat immunoglobulin G. We have characterized these reagents in affinity isolations and tissue immunofluorescence microscopy, identifying those that are optimal for these particularly demanding applications, and engineering dimeric constructs for ultra-high affinity. This study thus provides new nanobody tools directly applicable to a wide variety of research problems, and improved techniques enabling future nanobody development against diverse targets.

Epitope-specific antibody fragments block aggregation of AGelD187N, an aberrant peptide in gelsolin amyloidosis.

Aggregation of aberrant fragment of plasma gelsolin, AGelD187N, is a crucial event underlying the pathophysiology of Finnish gelsolin amyloidosis, an inherited form of systemic amyloidosis. The amyloidogenic gelsolin fragment AGelD187N does not play any physiological role in the body, unlike most aggregating proteins related to other protein misfolding diseases. However, no therapeutic agents that specifically and effectively target and neutralize AGelD187N exist. We used phage display technology to identify novel single-chain variable fragments that bind to different epitopes in the monomeric AGelD187N that were further maturated by variable domain shuffling and converted to antigen-binding fragment (Fab) antibodies. The generated antibody fragments had nanomolar binding affinity for full-length AGelD187N, as evaluated by biolayer interferometry. Importantly, all four Fabs selected for functional studies efficiently inhibited the amyloid formation of full-length AGelD187N as examined by thioflavin fluorescence assay and transmission electron microscopy. Two Fabs, neither of which bound to the previously proposed fibril-forming region of AGelD187N, completely blocked the amyloid formation of AGelD187N. Moreover, no small soluble aggregates, which are considered pathogenic species in protein misfolding diseases, were formed after successful inhibition of amyloid formation by the most promising aggregation inhibitor, as investigated by size-exclusion chromatography combined with multiangle light scattering. We conclude that all regions of the full-length AGelD187N are important in modulating its assembly into fibrils and that the discovered epitope-specific anti-AGelD187N antibody fragments provide a promising starting point for a disease-modifying therapy for gelsolin amyloidosis, which is currently lacking.

A selection and optimization strategy for single-domain antibodies targeting the PHF6 linear peptide within the tau intrinsically disordered protein.

The use of variable domain of the heavy-chain of the heavy-chain-only antibodies (VHHs) as disease-modifying biomolecules in neurodegenerative disorders holds promises, including targeting of aggregation-sensitive proteins. Exploitation of their clinical values depends however on the capacity to deliver VHHs with optimal physico-chemical properties for their specific context of use. We described previously a VHH with high therapeutic potential in a family of neurodegenerative diseases called tauopathies. The activity of this promising parent VHH named Z70 relies on its binding within the central region of the tau protein. Accordingly, we carried out random mutagenesis followed by yeast two-hybrid screening to obtain optimized variants. The VHHs selected from this initial screen targeted the same epitope as VHH Z70 as shown using NMR spectroscopy and had indeed improved binding affinities according to dissociation constant values obtained by surface plasmon resonance spectroscopy. The improved affinities can be partially rationalized based on three-dimensional structures and NMR data of three complexes consisting of an optimized VHH and a peptide containing the tau epitope. Interestingly, the ability of the VHH variants to inhibit tau aggregation and seeding could not be predicted from their affinity alone. We indeed showed that the in vitro and in cellulo VHH stabilities are other limiting key factors to their efficacy. Our results demonstrate that only a complete pipeline of experiments, here described, permits a rational selection of optimized VHH variants, resulting in the selection of VHH variants with higher affinities and/or acting against tau seeding in cell models.

Antibody homotypic interactions are encoded by germline light chain complementarity determining region 2.

The utilization of avidity to drive and tune functional responses is fundamental to antibody biology and often underlies the mechanisms of action of monoclonal antibody drugs. There is increasing evidence that antibodies leverage homotypic interactions to enhance avidity, often through weak transient interfaces whereby self-association is coupled with target binding. Here, we comprehensively map the Fab­Fab interfaces of antibodies targeting DR5 and 4-1BB that utilize homotypic interaction to promote receptor activation and demonstrate that both antibodies have similar self-association determinants primarily encoded within a germline light chain complementarity determining region 2 (CDRL2). We further show that these determinants can be grafted onto antibodies of distinct target specificity to substantially enhance their activity. An expanded characterization of all unique germline CDRL2 sequences reveals additional self-association sequence determinants encoded in the human germline repertoire. Our results suggest that this phenomenon is unique to CDRL2, and is correlated with the less frequent antigen interaction and lower somatic hypermutation associated with this loop. This work reveals a previously unknown avidity mechanism in antibody native biology that can be exploited for the engineering of biotherapeutics.

Engineering therapeutic monoclonal antibodies.

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.

NanoBERTa-ASP: predicting nanobody paratope based on a pretrained RoBERTa model.

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.

Antibody-guided proteases enable selective and catalytic degradation of challenging therapeutic targets.

The exquisite specificity, natural biological functions, and favorable development properties of antibodies make them highly effective agents as drugs. Monoclonal antibodies are particularly strong as inhibitors of systemically accessible targets where trough-level concentrations can sustain full target occupancy. Yet beyond this pharmacologic wheelhouse, antibodies perform suboptimally for targets of high abundance and those not easily accessible from circulation. Fundamentally, this restraint on broader application is due largely to the stoichiometric nature of their activity-one drug molecule is generally able to inhibit a maximum of two target molecules at a time. Enzymes in contrast are able to catalytically turnover multiple substrates, making them a natural sub-stoichiometric solution for targets of high abundance or in poorly accessible sites of action. However, enzymes have their own limitations as drugs, including, in particular, the polypharmacology and broad specificity often seen with native enzymes. In this study, we introduce antibody-guided proteolytic enzymes to enable selective sub-stoichiometric turnover of therapeutic targets. We demonstrate that antibody-mediated substrate targeting can enhance enzyme activity and specificity, with proof of concept for two challenging target proteins, amyloid-ß and immunoglobulin G. This work advances a new biotherapeutic platform that combines the favorable properties of antibodies and proteolytic enzymes to more effectively suppress high-bar therapeutic targets.

Engineered polyspecific antibodies: A new frontier in the field of immunotherapeutics.

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.

Bovine ultralong CDR-H3 derived knob paratopes elicit potent TNF-α neutralization and enable the generation of novel adalimumab-based antibody architectures with augmented features.

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.

Rationalizing Random Walks: Replicating Protective Antibody Trajectories.

'Reverse vaccinology 2.0' aims to rationally reproduce template antibody responses, such as broadly neutralizing antibodies against human immunodeficiency virus-1. While observations of antibody convergence across individuals support the assumption that responses may be replicated, the diversity of humoral immunity and the process of antibody selection are rooted in stochasticity. Drawing from experience with in vitro antibody engineering by directed evolution, we consider how antibody selection may be driven, as in germline-targeting vaccine approaches to elicit broadly neutralizing antibodies and illustrate the potential consequences of over-defining a template antibody response. We posit that the prospective definition of template antibody responses and the odds of replicating them must be considered within the randomness of humoral immunity.

The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design.

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.

Systematic mutational analysis reveals an essential role of N275 in IgE stability.

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.

Development of an effective single-chain variable fragment recognizing a novel epitope in the hepatitis C virus E2 protein that restricts virus entry into hepatocytes.

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.

Deep learning in preclinical antibody drug discovery and development.

Antibody drugs have become a key part of biotherapeutics. Patients suffering from various diseases have benefited from antibody therapies. However, its development process is rather long, expensive and risky. To speed up the process, reduce cost and improve success rate, artificial intelligence, especially deep learning methods, have been widely used in all aspects of preclinical antibody drug development, from library generation to hit identification, developability screening, lead selection and optimization. In this review, we systematically summarize antibody encodings, deep learning architectures and models used in preclinical antibody drug discovery and development. We also critically discuss challenges and opportunities, problems and possible solutions, current applications and future directions of deep learning in antibody drug development.