Rational affinity maturation of anti-amyloid antibodies with high conformational and sequence specificity

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.

Cholesterol inhibits assembly and activation of the EphA2 receptor

The receptor tyrosine kinase EphA2 drives cancer malignancy by facilitating metastasis. EphA2 can be found in different self-assembly states: as a monomer, dimer, and oligomer. However, our understanding remains limited regarding which EphA2 state is responsible for driving pro-metastatic signaling. To address this limitation, we have developed SiMPull-POP, a single-molecule method for accurate quantification of membrane protein self-assembly. Our experiments revealed that a reduction of plasma membrane cholesterol strongly promoted EphA2 self-assembly. Indeed, low cholesterol caused a similar effect to the EphA2 ligand ephrinA1-Fc. These results indicate that cholesterol inhibits EphA2 assembly. Phosphorylation studies in different cell lines revealed that low cholesterol increased phospho-serine levels, the signature of oncogenic signaling. Investigation of the mechanism that cholesterol uses to inhibit the assembly and activity of EphA2 indicate an in-trans effect, where EphA2 is phosphorylated by protein kinase A downstream of beta-adrenergic receptor activity, which cholesterol also inhibits. Our study not only provides new mechanistic insights on EphA2 oncogenic function, but also suggests that cholesterol acts as a molecular safeguard mechanism that prevents uncontrolled self-assembly and activation of EphA2.

Native ion mobility-mass spectrometry reveals the binding mechanisms of anti-amyloid therapeutic antibodies

One of the most important attributes of anti-amyloid antibodies is their selective binding to oligomeric and amyloid aggregates. However, current methods of examining the binding specificities of anti-amyloid β (Aβ) antibodies have limited ability to differentiate between complexes that form between antibodies and monomeric or oligomeric Aβ species during the dynamic Aβ aggregation process. Here, we present a high-resolution native ion-mobility mass spectrometry (nIM-MS) method to investigate complexes formed between a variety of Aβ oligomers and three Aβ-specific IgGs, namely two antibodies with relatively high conformational specificity (aducanumab and A34) and one antibody with low conformational specificity (crenezumab). We found that crenezumab primarily binds Aβ monomers, while aducanumab preferentially binds Aβ monomers and dimers and A34 preferentially binds Aβ dimers, trimers, and tetrameters. Through collision induced unfolding (CIU) analysis, our data indicate that antibody stability is increased upon Aβ binding and, surprisingly, this stabilization involves the Fc region. Together, we conclude that nIM-MS and CIU enable the identification of Aβ antibody binding stoichiometries and provide important details regarding antibody binding mechanisms.

Unveiling the Molecular Mechanisms of the Type-IX Secretion System's Response Regulator: Structural and Functional Insights

The Type-IX secretion system (T9SS) is a nanomachinery utilized by bacterial pathogens to facilitate infection. The system is regulated by a signaling cascade serving as its activation switch. A pivotal member in this cascade, the response regulator protein PorX, represents a promising drug target to prevent the secretion of virulence factors. Here, we provide a comprehensive characterization of PorX both in vitro and in vivo . First, our structural studies revealed PorX harbours a unique enzymatic effector domain, which, surprisingly, shares structural similarities with the alkaline phosphatase superfamily, involved in nucleotide and lipid signaling pathways. Importantly, such pathways have not been associated with the T9SS until now. Enzymatic characterization of PorX's effector domain revealed a zinc-dependent phosphodiesterase activity, with active site dimensions suitable to accommodate a large substrate. Unlike typical response regulators that dimerize via their receiver domain upon phosphorylation, we found that zinc can also induce conformational changes and promote PorX's dimerization via an unexpected interface. These findings suggest that PorX can serve as a cellular zinc sensor, broadening our understanding of its regulatory mechanisms. Despite the strict conservation of PorX in T9SS-utilizing bacteria, we demonstrate that PorX is essential for virulence factors secretion in Porphyromonas gingivalis and affects metabolic enzymes secretion in the non-pathogenic Flavobacterium johnsoniae , but not for the secretion of gliding adhesins. Overall, this study advances our structural and functional understanding of PorX, highlighting its potential as a druggable target for intervention strategies aimed at disrupting the T9SS and mitigating virulence in pathogenic species.

In vivo Auto-tuning of Antibody-Drug Conjugate Delivery for Effective Immunotherapy using High-Avidity, Low-Affinity Antibodies

Antibody-drug conjugates (ADCs) have experienced a surge in clinical approvals in the past five years. Despite this success, a major limitation to ADC efficacy in solid tumors is poor tumor penetration, which leaves many cancer cells untargeted. Increasing antibody doses or co-administering ADC with an unconjugated antibody can improve tumor penetration and increase efficacy when target receptor expression is high. However, it can also reduce efficacy in low-expression tumors where ADC delivery is limited by cellular uptake. This creates an intrinsic problem because many patients express different levels of target between tumors and even within the same tumor. Here, we generated High-Avidity, Low-Affinity (HALA) antibodies that can automatically tune the cellular ADC delivery to match the local expression level. Using HER2 ADCs as a model, HALA antibodies were identified with the desired HER2 expression-dependent competitive binding with ADCs in vitro. Multi-scale distribution of trastuzumab emtansine and trastuzumab deruxtecan co-administered with the HALA antibody were analyzed in vivo, revealing that the HALA antibody increased ADC tumor penetration in high-expression systems with minimal reduction in ADC uptake in low-expression tumors. This translated to greater ADC efficacy in immunodeficient mouse models across a range of HER2 expression levels. Furthermore, Fc-enhanced HALA antibodies showed improved Fc-effector function at both high and low expression levels and elicited a strong response in an immunocompetent mouse model. These results demonstrate that HALA antibodies can expand treatment ranges beyond high expression targets and leverage strong immune responses.

Development of a pan-tau multivalent nanobody that binds tau aggregation motifs and recognizes pathological tau aggregates

Alzheimer's disease and other tauopathies are characterized by the misfolding and aggregation of the tau protein into oligomeric and fibrillar structures. Antibodies against tau play an increasingly important role in studying these neurodegenerative diseases and the generation of tools to diagnose and treat them. The development of antibodies that recognize tau protein aggregates, however, is hindered by complex immunization and antibody selection strategies and limitations to antigen presentation. Here, we have taken a facile approach to identify single-domain antibodies, or nanobodies, that bind to many forms of tau by screening a synthetic yeast surface display nanobody library against monomeric tau and creating multivalent versions of our lead nanobody, MT3.1, to increase its avidity for tau aggregates. We demonstrate that MT3.1 binds to tau monomer, oligomers, and fibrils, as well as pathogenic tau from a tauopathy mouse model, despite being identified through screens against monomeric tau. Through epitope mapping, we discovered binding epitopes of MT3.1 contain the key motif VQIXXK which drives tau aggregation. We show that our bivalent and tetravalent versions of MT3.1 have greatly improved binding ability to tau oligomers and fibrils compared to monovalent MT3.1. Our results demonstrate the utility of our nanobody screening and multivalent design approach in developing nanobodies that bind amyloidogenic protein aggregates. This approach can be extended to the generation of multivalent nanobodies that target other amyloid proteins and has the potential to advance the research and treatment of neurodegenerative diseases.

Functional characterization of all CDKN2A missense variants and comparison to in silico models of pathogenicity

Interpretation of variants identified during genetic testing is a significant clinical challenge. In this study, we developed a high-throughput CDKN2A functional assay and characterized all possible CDKN2A missense variants. We found that 40% of all missense variants were functionally deleterious. We also used our functional classification to assess the performance of in silico models that predict the effect of variants, including recently reported models based on machine learning. Notably, we found that all in silico models similarly when compared to our functional classifications with accuracies of 54.6 - 70.9%. Furthermore, while we found that functionally deleterious variants were enriched within ankyrin repeats, rarely were all missense variants at a single residue functionally deleterious. Our functional classifications are a resource to aid the interpretation of CDKN2A variants and have important implications for the application of variant interpretation guidelines, particularly the use of in silico models for clinical variant interpretation.

Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors

The spread of cancer from organ to organ (metastasis) is responsible for the vast majority of cancer deaths; however, most current anti-cancer drugs are designed to arrest or reverse tumor growth without directly addressing disease spread. It was recently discovered that tumor cell-secreted interleukin-6 (IL-6) and interleukin-8 (IL-8) synergize to enhance cancer metastasis in a cell-density dependent manner, and blockade of the IL-6 and IL-8 receptors (IL-6R and IL-8R) with a novel bispecific antibody, BS1, significantly reduced metastatic burden in multiple preclinical mouse models of cancer. Bispecific antibodies (BsAbs), which combine two different antigen-binding sites into one molecule, are a promising modality for drug development due to their enhanced avidity and dual targeting effects. However, while BsAbs have tremendous therapeutic potential, elucidating the mechanisms underlying their binding and inhibition will be critical for maximizing the efficacy of new BsAb treatments. Here, we describe a quantitative, computational model of the BS1 BsAb, exhibiting how modeling multivalent binding provides key insights into antibody affinity and avidity effects and can guide therapeutic design. We present detailed simulations of the monovalent and bivalent binding interactions between different antibody constructs and the IL-6 and IL-8 receptors to establish how antibody properties and system conditions impact the formation of binary (antibody-receptor) and ternary (receptor-antibody-receptor) complexes. Model results demonstrate how the balance of these complex types drives receptor inhibition, providing important and generalizable predictions for effective therapeutic design.

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

MOTIVATION

Deep sequencing of antibody and related protein libraries after phage or yeast-surface display sorting is widely used to identify variants with increased affinity, specificity, and/or improvements in key biophysical properties. Conventional approaches for identifying optimal variants typically use the frequencies of observation in enriched libraries or the corresponding enrichment ratios. However, these approaches disregard the vast majority of deep sequencing data and often fail to identify the best variants in the libraries.

RESULTS

Here, we present a method, Position-Specific Enrichment Ratio Matrix (PSERM) scoring, that uses entire deep sequencing datasets from pre- and post-selections to score each observed protein variant. The PSERM scores are the sum of the site-specific enrichment ratios observed at each mutated position. We find that PSERM scores are much more reproducible and correlate more strongly with experimentally measured properties than frequencies or enrichment ratios, including for multiple antibody properties (affinity and non-specific binding) for a clinical-stage antibody (emibetuzumab). We expect that this method will be broadly applicable to diverse protein engineering campaigns.

AVAILABILITY AND IMPLEMENTATION

All deep sequencing datasets and code to perform the analyses presented within are available via https://github.com/Tessier-Lab-UMich/PSERM_paper.

Antibody-Mediated Clearance of Brain Amyloid-β: Mechanisms of Action, Effects of Natural and Monoclonal Anti-Aβ Antibodies, and Downstream Effects

Immunotherapeutic efforts to slow the clinical progression of Alzheimer's disease (AD) by lowering brain amyloid-β (Aβ) have included Aβ vaccination, intravenous immunoglobulin (IVIG) products, and anti-Aβ monoclonal antibodies. Neither Aβ vaccination nor IVIG slowed disease progression. Despite conflicting phase III results, the monoclonal antibody Aducanumab received Food and Drug Administration (FDA) approval for treatment of AD in June 2021. The only treatments unequivocally demonstrated to slow AD progression to date are the monoclonal antibodies Lecanemab and Donanemab. Lecanemab received FDA approval in January 2023 based on phase II results showing lowering of PET-detectable Aβ; phase III results released at that time indicated slowing of disease progression. Topline results released in May 2023 for Donanemab's phase III trial revealed that primary and secondary end points had been met. Antibody binding to Aβ facilitates its clearance from the brain via multiple mechanisms including promoting its microglial phagocytosis, activating complement, dissolving fibrillar Aβ, and binding of antibody-Aβ complexes to blood-brain barrier receptors. Antibody binding to Aβ in peripheral blood may also promote cerebral efflux of Aβ by a peripheral sink mechanism. According to the amyloid hypothesis, for Aβ targeting to slow AD progression, it must decrease downstream neuropathological processes including tau aggregation and phosphorylation and (possibly) inflammation and oxidative stress. This review discusses antibody-mediated mechanisms of Aβ clearance, findings in AD trials involving Aβ vaccination, IVIG, and anti-Aβ monoclonal antibodies, downstream effects reported in those trials, and approaches which might improve the Aβ-clearing ability of monoclonal antibodies.

Quantitative flow cytometric selection of tau conformational nanobodies specific for pathological aggregates

Single-domain antibodies, also known as nanobodies, are broadly important for studying the structure and conformational states of several classes of proteins, including membrane proteins, enzymes, and amyloidogenic proteins. Conformational nanobodies specific for aggregated conformations of amyloidogenic proteins are particularly needed to better target and study aggregates associated with a growing class of associated diseases, especially neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. However, there are few reported nanobodies with both conformational and sequence specificity for amyloid aggregates, especially for large and complex proteins such as the tau protein associated with Alzheimer's disease, due to difficulties in selecting nanobodies that bind to complex aggregated proteins. Here, we report the selection of conformational nanobodies that selectively recognize aggregated (fibrillar) tau relative to soluble (monomeric) tau. Notably, we demonstrate that these nanobodies can be directly isolated from immune libraries using quantitative flow cytometric sorting of yeast-displayed libraries against tau aggregates conjugated to quantum dots, and this process eliminates the need for secondary nanobody screening. The isolated nanobodies demonstrate conformational specificity for tau aggregates in brain samples from both a transgenic mouse model and human tauopathies. We expect that our facile approach will be broadly useful for isolating conformational nanobodies against diverse amyloid aggregates and other complex antigens.

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

Motivation

Deep sequencing of antibody and related protein libraries after phage or yeast-surface display sorting is widely used to identify variants with increased affinity, specificity and/or improvements in key biophysical properties. Conventional approaches for identifying optimal variants typically use the frequencies of observation in enriched libraries or the corresponding enrichment ratios. However, these approaches disregard the vast majority of deep sequencing data and often fail to identify the best variants in the libraries.

Results

Here, we present a method, Position-Specific Enrichment Ratio Matrix (PSERM) scoring, that uses entire deep sequencing datasets from pre- and post-selections to score each observed protein variant. The PSERM scores are the sum of the site-specific enrichment ratios observed at each mutated position. We find that PSERM scores are much more reproducible and correlate more strongly with experimentally measured properties than frequencies or enrichment ratios, including for multiple antibody properties (affinity and non-specific binding) for a clinical-stage antibody (emibetuzumab). We expect that this method will be broadly applicable to diverse protein engineering campaigns.

Availability

All deep sequencing datasets and code to do the analyses presented within are available via GitHub.

Contact

Peter Tessier, ptessier@umich.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Flow cytometric isolation of drug-like conformational antibodies specific for amyloid fibrils

Antibodies that recognize specific protein conformational states are broadly important for research, diagnostic and therapeutic applications, yet they are difficult to generate in a predictable and systematic manner using either immunization or in vitro antibody display methods. This problem is particularly severe for conformational antibodies that recognize insoluble antigens such as amyloid fibrils associated with many neurodegenerative disorders. Here we report a quantitative fluorescence-activated cell sorting (FACS) method for directly selecting high-quality conformational antibodies against different types of insoluble (amyloid fibril) antigens using a single, off-the-shelf human library. Our approach uses quantum dots functionalized with antibodies to capture insoluble antigens, and the resulting quantum dot conjugates are used in a similar manner as conventional soluble antigens for multi-parameter FACS selections. Notably, we find that this approach is robust for isolating high-quality conformational antibodies against tau and α-synuclein fibrils from the same human library with combinations of high affinity, high conformational specificity and, in some cases, low off-target binding that rival or exceed those of clinical-stage antibodies specific for tau (zagotenemab) and α-synuclein (cinpanemab). This approach is expected to enable conformational antibody selection and engineering against diverse types of protein aggregates and other insoluble antigens (e.g., membrane proteins) that are compatible with presentation on the surface of antibody-functionalized quantum dots.

Development of a human antibody fragment cross-neutralizing scorpion toxins

Previously, it was demonstrated that from the single chain fragment variable (scFv) 3F it is possible to generate variants capable of neutralizing the Cn2 and Css2 toxins, as well as their respective venoms (Centruroides noxius and Centruroides suffusus). Despite this success, it has not been easy to modify the recognition of this family of scFvs toward other dangerous scorpion toxins. The analysis of toxin-scFv interactions and in vitro maturation strategies allowed us to propose a new maturation pathway for scFv 3F to broaden recognition toward other Mexican scorpion toxins. From maturation processes against toxins CeII9 from C. elegans and Ct1a from C. tecomanus, the scFv RAS27 was developed. This scFv showed an increased affinity and cross-reactivity for at least 9 different toxins while maintaining recognition for its original target, the Cn2 toxin. In addition, it was confirmed that it can neutralize at least three different toxins. These results constitute an important advance since it was possible to improve the cross-reactivity and neutralizing capacity of the scFv 3F family of antibodies.

A cationic amphiphilic peptide chaperone rescues Aβ42 aggregation and cytotoxicity

Directing Aβ₄₂ to adopt a conformation that is free from aggregation and cell toxicity is an attractive and viable strategy to design therapeutics for Alzheimer's disease. Over the years, extensive efforts have been made to disrupt the aggregation of Aβ₄₂ using various types of inhibitors but with limited success. Herein, we report the inhibition of aggregation of Aβ₄₂ and disintegration of matured fibrils of Aβ₄₂ into smaller assemblies by a 15-mer cationic amphiphilic peptide. The biophysical analysis comprising thioflavin T (ThT) mediated amyloid aggregation kinetic analysis, dynamic light scattering, ELISA, AFM, and TEM suggested that the peptide effectively disrupts Aβ₄₂ aggregation. The circular dichroism (CD) and 2D-NMR HSQC analysis reveal that upon interaction, the peptide induces a conformational change in Aβ₄₂ that is free from aggregation. Further, the cell assay experiments revealed that this peptide is non-toxic to cells and also rescues the cells from the toxicity of Aβ₄₂. Peptides with a shorter length displayed either weak or no inhibitory effect on Aβ₄₂ aggregation and cytotoxicity. These results suggest that the 15-residue cationic amphiphilic peptide reported here may serve as a potential therapeutic candidate for Alzheimer's disease.

Monitoring α-synuclein aggregation

Synucleinopathies, including Parkinson's disease (PD), dementia with Lewy Bodies (DLB), and multiple system atrophy (MSA), are characterized by the misfolding and subsequent aggregation of alpha-synuclein (α-syn) that accumulates in cytoplasmic inclusions bodies in the cells of affected brain regions. Since the seminal report of likely-aggregated α-syn presence within the Lewy bodies by Spillantini et al. in 1997, the keyword "synuclein aggregation" has appeared in over 6000 papers (Source: PubMed October 2022). Studying, observing, describing, and quantifying α-syn aggregation is therefore of paramount importance, whether it happens in tubo, in vitro, in post-mortem samples, or in vivo. The past few years have witnessed tremendous progress in understanding aggregation mechanisms and identifying various polymorphs. In this context of growing complexity, it is of utmost importance to understand what tools we possess, what exact information they provide, and in what context they may be applied. Nonetheless, it is also crucial to rationalize the relevance of the information and the limitations of these methods for gauging the final result. In this review, we present the main techniques that have shaped the current views about α-syn structure and dynamics, with particular emphasis on the recent breakthroughs that may change our understanding of synucleinopathies.

An in silico method to assess antibody fragment polyreactivity

Antibodies are essential biological research tools and important therapeutic agents, but some exhibit non-specific binding to off-target proteins and other biomolecules. Such polyreactive antibodies compromise screening pipelines, lead to incorrect and irreproducible experimental results, and are generally intractable for clinical development. Here, we design a set of experiments using a diverse naïve synthetic camelid antibody fragment (nanobody) library to enable machine learning models to accurately assess polyreactivity from protein sequence (AUC > 0.8). Moreover, our models provide quantitative scoring metrics that predict the effect of amino acid substitutions on polyreactivity. We experimentally test our models' performance on three independent nanobody scaffolds, where over 90% of predicted substitutions successfully reduced polyreactivity. Importantly, the models allow us to diminish the polyreactivity of an angiotensin II type I receptor antagonist nanobody, without compromising its functional properties. We provide a companion web-server that offers a straightforward means of predicting polyreactivity and polyreactivity-reducing mutations for any given nanobody sequence.

Methodological advances and strategies for high resolution structure determination of cellular protein aggregates

Aggregation of proteins is at the nexus of molecular processes crucial to aging, disease, and employing proteins for biotechnology and medical applications. There has been much recent progress in determining the structural features of protein aggregates that form in cells; yet, owing to prevalent heterogeneity in aggregation, many aspects remain obscure and often experimentally intractable to define. Here, we review recent results of structural studies for cell-derived aggregates of normally globular proteins, with a focus on high-resolution methods for their analysis and prediction. Complementary results obtained by solid-state NMR spectroscopy, FTIR spectroscopy and microspectroscopy, cryo-EM, and amide hydrogen/deuterium exchange measured by NMR and mass spectrometry, applied to bacterial inclusion bodies and disease inclusions, are uncovering novel information on in-cell aggregation patterns as well as great diversity in the structural features of useful and aberrant protein aggregates. Using these advances as a guide, this review aims to advise the reader on which combination of approaches may be the most appropriate to apply to their unique system.

Facile isolation of high-affinity nanobodies from synthetic libraries using CDR-swapping mutagenesis

The generation of high-affinity nanobodies for diverse biomedical applications typically requires immunization or affinity maturation. Here, we report a simple protocol using complementarity-determining region (CDR)-swapping mutagenesis to isolate high-affinity nanobodies from common framework libraries. This approach involves shuffling the CDRs of low-affinity variants during the sorting of yeast-displayed libraries to directly isolate high-affinity nanobodies without the need for lead isolation and optimization. We expect this approach, which we demonstrate for SARS-CoV-2 neutralizing nanobodies, will simplify the generation of high-affinity nanobodies.

For complete details on the use and execution of this profile, please refer to Zupancic et al. (2021).

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Protocol enables direct isolation of high-affinity nanobodies from synthetic libraries

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Individual CDRs are amplified and recombined to obtain nanobodies with shuffled CDRs

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Libraries of CDR-shuffled nanobodies are rapidly sorted to obtain high-affinity clones

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Monovalent and bivalent nanobody affinities are determined using flow cytometry

Isolating Anti-amyloid Antibodies from Yeast-Displayed Libraries

Conformational antibodies specific for amyloid-forming peptides and proteins are important for a range of biomedical applications, including detecting, inhibiting, and potentially treating protein aggregation disorders ranging from Alzheimer's to Parkinson's diseases. Generation of anti-amyloid antibodies is greatly complicated by the complex, heterogeneous and insoluble nature of amyloid antigens. Here we describe systematic methods for isolating and affinity maturing anti-amyloid antibodies using yeast surface display. Magnetic-activated cell sorting is used to sort single-chain antibody libraries positively for binding to amyloid antigens and negatively against the corresponding disaggregated antigens to remove antibodies that bind in a conformation-independent manner. Isolated lead antibody clones with conformational specificity are affinity matured via targeted CDR mutagenesis and magnetic-activated cell sorting.

Recombinant antibodies recognize conformation-dependent epitopes of the leucine zipper of misfolding-prone myocilin

Recombinant antibodies with well-characterized epitopes and known conformational specificities are critical reagents to support robust interpretation and reproducibility of immunoassays across biomedical research. For myocilin, a protein prone to misfolding that is associated with glaucoma and an emerging player in other human diseases, currently available antibodies are unable to differentiate among the numerous disease-associated protein states. This fundamentally constrains efforts to understand the connection between myocilin structure, function, and disease. To address this concern, we used protein engineering methods to develop new recombinant antibodies that detect the N-terminal leucine zipper structural domain of myocilin and that are cross-reactive for human and mouse myocilin. After harvesting spleens from immunized mice and in vitro library panning, we identified two antibodies, 2A4 and 1G12. 2A4 specifically recognizes a folded epitope while 1G12 recognizes a range of conformations. We matured antibody 2A4 for improved biophysical properties, resulting in variant 2H2. In a human IgG1 format, 2A4, 1G12, and 2H2 immunoprecipitate full-length folded myocilin present in the spent media of human trabecular meshwork (TM) cells, and 2H2 can visualize myocilin in fixed human TM cells using fluorescence microscopy. These new antibodies should find broad application in glaucoma and other research across multiple species platforms.

Engineered Multivalent Nanobodies Potently and Broadly Neutralize SARS-CoV-2 Variants

The COVID-19 pandemic continues to be a severe threat to human health, especially due to current and emerging SARS-CoV-2 variants with potential to escape humoral immunity developed after vaccination or infection. The development of broadly neutralizing antibodies that engage evolutionarily conserved epitopes on coronavirus spike proteins represents a promising strategy to improve therapy and prophylaxis against SARS-CoV-2 and variants thereof. Herein, a facile multivalent engineering approach is employed to achieve large synergistic improvements in the neutralizing activity of a SARS-CoV-2 cross-reactive nanobody (VHH-72) initially generated against SARS-CoV. This synergy is epitope specific and is not observed for a second high-affinity nanobody against a non-conserved epitope in the receptor-binding domain. Importantly, a hexavalent VHH-72 nanobody retains binding to spike proteins from multiple highly transmissible SARS-CoV-2 variants (B.1.1.7 and B.1.351) and potently neutralizes them. Multivalent VHH-72 nanobodies also display drug-like biophysical properties, including high stability, high solubility, and low levels of non-specific binding. The unique neutralizing and biophysical properties of VHH-72 multivalent nanobodies make them attractive as therapeutics against SARS-CoV-2 variants.