Antibody Structure and Function: The Basis for Engineering Therapeutics

Nanobody-based drug delivery systems for cancer therapy

Targeted delivery can elevate the local drug concentration within tumor tissues, while minimizing drug distribution to normal tissues, thus enhancing the effectiveness of anti-tumor medications and reducing adverse effects and systemic toxicities. Nanobodies, the novel molecular pattern of antibodies characterized by their small size, high stability, strong specificity, and low immunogenicity, have been extensively applied in targeted drug delivery for tumor therapy. This review discusses structural disparities and functional advantages of nanobodies compared to other antibody fragments and full-length antibody. It also highlights nanobody applications in targeted tumor therapy, focusing on their use in modifying delivery systems, e.g., liposomes, EVs, micelles, albumin nanoparticles, gold nanoparticles, polymeric nanoparticles, and as nanobody-drug conjugates. This review delves into the methods applied for integrating nanobodies into different drug delivery carriers, in order to provide useful information for researchers developing nanobody-based targeted drug delivery systems.

Post-translational assembly of multi-functional antibody

The advent of multi-specific antibodies has introduced a significant advantage over traditional monoclonal antibody therapeutics by engaging multiple targets and pathways. This review delves into the post-translational assembly techniques for multi-specific antibodies, highlighting the innovations and challenges associated with approaches of chemical conjugation, oligonucleotide-mediated assembly, and protein-protein interactions. Chemical conjugation methods have evolved to enhance the assembly process's specificity and flexibility, enabling transient engagement and versatile antibody formats. Meanwhile, oligonucleotide-mediated assembly leverages the precision of Watson-Crick base pairing, granting unmatched control over the antibody's structure and functional orientation. Additionally, protein-protein interaction strategies, notably through SpyTag/SpyCatcher systems, present a direct assembly approach without necessitating ancillary modifications, streamlining the production process. This review summarizes the significance of these methodologies in generating antibodies with diverse structures and multi-target engagement capabilities, underscoring their potential in improving therapeutic efficacy and reducing production complexity.

Structural characterization of antibody-responses following Zolgensma treatment for AAV capsid engineering to expand patient cohorts

Monoclonal antibodies are useful tools to dissect the neutralizing antibody response against the adeno-associated virus (AAV) capsids that are used as gene therapy delivery vectors. The presence of pre-existing neutralizing antibodies in large portions of the human population poses a significant challenge for AAV-mediated gene therapy, primarily targeting the capsid leading to vector inactivation and loss of treatment efficacy. This study structurally characterizes the interactions of 21 human-derived neutralizing antibodies from three patients treated with the AAV9 vector, Zolgensma®, utilizing high-resolution cryo-electron microscopy. The antibodies bound to the 2-fold depression or the 3-fold protrusions do not conform to the icosahedral symmetry of the capsid, thus requiring localized reconstructions. These complex structures provide unprecedented details of the mAbs binding interfaces, with many antibodies inducing structural perturbations of the capsid upon binding. Key surface capsid amino acid residues were identified facilitating the design of capsid variants with antibody escape phenotypes. These AAV9 capsid variants have the potential to expand the patient cohort to include those that were previously excluded due to their pre-existing neutralizing antibodies against the wtAAV9 capsid, and the possibly of further treatment to those requiring redosing.

Isoelectric point, net charge and amino acid analysis of experimentally validated therapeutic antibodies

The isoelectric point (pI) of an antibody is known to affect its non-specific interactions and repulsive self-interactions. However, analytical outcomes for the pI of a large number of therapeutic antibodies remain unexplored. In this study, we explored the pI and net charge of variable heavy (VH), variable light (VL), CDR (complementarity determining regions) and whole IgG on a large number of therapeutic antibodies, additionally amino acids distribution in the CDR regions were also analyzed. A total of 708 experimentally validated antibodies from the Thera-SAbDab database were analyzed in this study. Analysis of the antibody dataset showed that the pI of the whole IgG sequence is between 5 and 9, while the majority was in the intermediate range between 7 and 9 (86.7%). The charge had a wide range from - 10 to 12, with the majority falling between the charges 2-6 (53.4%). However, the combined pI score of the CDRs of light chains (60%) as well as for the heavy chains (67%) was observed in the range of 4-6. The amino acid composition analysis of CDR regions revealed that most of the amino acids in the light chain are uncharged-polar (46.3%) followed by hydrophobic-aliphatic (28.4%), while in the heavy chain; it is hydrophobic-aliphatic (35.2%) followed by uncharged-polar (24.6%). In conclusion, the pI and net charge analysis of therapeutic antibodies are crucial for understanding pharmacokinetic properties. Moreover, amino acid composition of the light and heavy chain CDR regions has a significant impact on the pI and charge of the entire IgG antibody.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-025-00356-y.

Structure-guided disulfide engineering restricts antibody conformation to elicit TNFR agonism

A promising strategy in cancer immunotherapy is activation of immune signalling pathways through antibodies that target co-stimulatory receptors. hIgG2, one of four human antibody isotypes, is known to deliver strong agonistic activity, and modification of hIgG2 hinge disulfides can influence immune-stimulating activity. This was shown for antibodies directed against the hCD40 receptor, where cysteine-to-serine exchange mutations caused changes in antibody conformational flexibility. Here we demonstrate that the principles of increasing agonism by restricting antibody conformation through disulfide modification can be translated to the co-stimulatory receptor h4-1BB, another member of the tumour necrosis factor receptor superfamily. Furthermore, we explore structure-guided design of the anti-hCD40 antibody ChiLob7/4 and show that engineering additional disulfides between opposing F(ab') arms can elicit conformational restriction, concomitant with enhanced agonism. These results support a mode where subtle increases in rigidity can deliver significant improvements in immunostimulatory activity, thus providing a strategy for the rational design of more powerful antibody therapeutics.

The Molecular Toolbox for Linkage Type-Specific Analysis of Ubiquitin Signaling

Modification of proteins and other biomolecules with ubiquitin regulates virtually all aspects of eukaryotic cell biology. Ubiquitin can be attached to substrates as a monomer or as an array of polyubiquitin chains with defined linkages between the ubiquitin moieties. Each ubiquitin linkage type adopts a distinct structure, enabling the individual linkage types to mediate specific functions or outcomes in the cell. The dynamics, heterogeneity, and in some cases low abundance, make analysis of linkage type-specific ubiquitin signaling a challenging and complex task. Herein, the strategies and molecular tools available for enrichment, detection, and characterization of linkage type-specific ubiquitin signaling, are reviewed. The molecular "toolbox" consists of a range of molecularly different affinity reagents, including antibodies and antibody-like molecules, affimers, engineered ubiquitin-binding domains, catalytically inactive deubiquitinases, and macrocyclic peptides, each with their unique characteristics and binding modes. The molecular engineering of these ubiquitin-binding molecules makes them useful tools and reagents that can be coupled to a range of analytical methods, such as immunoblotting, fluorescence microscopy, mass spectrometry-based proteomics, or enzymatic analyses to aid in deciphering the ever-expanding complexity of ubiquitin modifications.

Protein sequence modelling with Bayesian flow networks

Exploring the vast and largely uncharted territory of amino acid sequences is crucial for understanding complex protein functions and the engineering of novel therapeutic proteins. Whilst generative machine learning has advanced protein sequence modelling, no existing approach is proficient in both unconditional and conditional generation. In this work, we propose that Bayesian Flow Networks (BFNs), a recently introduced framework for generative modelling, can address these challenges. We present ProtBFN, a 650M parameter model trained on protein sequences curated from UniProtKB, which generates natural-like, diverse, structurally coherent, and novel protein sequences, significantly outperforming leading autoregressive and discrete diffusion models. Further, we fine-tune ProtBFN on heavy chains from the Observed Antibody Space to obtain an antibody-specific model, AbBFN, which we use to evaluate zero-shot conditional generation capabilities. AbBFN is found to be competitive with or better than antibody-specific BERT-style models when applied to predicting individual framework or complimentary determining regions.

Phage Display Selected Chicken Antibodies Targeting Surface Alpha Enolase in Staphylococcus aureus

Staphylococcus aureus, a prevalent gram-positive bacterium in human populations, poses a significant risk for causing serious opportunistic infections and increasing antibiotic resistance. Alpha-enolase in S. aureus plays important roles in extracellular matrix binding and biofilm formation. These functions enable S. aureus to invade host tissues and cause infections. The aim of this study was to develop specific alpha-enolase chicken antibodies through phage display technology targeting S. aureus surface proteins as a potential alternative to antibiotic therapy. A chicken was immunized with recombinant S. aureus alpha-enolase, leading to the construction of two phage display single-chain variable fragment libraries of 3.32 × 106 and 8.60×105 transformants with different linker lengths. After four rounds of biopanning, five single-chain variable fragment antibody clones, including three with high binding affinities (SaS1, SaS2, and SaL2), were selected. These clones exhibited distinct binding patterns in epitope mapping and cross-reaction assays, with SaS1 and SaS2 specifically recognizing S. aureus alpha-enolase and SaL2 cross-reacting with Streptococcus pneumoniae alpha-enolase. Furthermore, the specificity of these antibody clones toward clinical S. aureus strains, including methicillin-sensitive and methicillin-resistant strains, was validated through cell-based enzyme-linked immunosorbent assays (ELISA) and flow cytometry assays. The identification of SaS1, SaS2, and SaL2 underscores their diagnostic and therapeutic potential, offering promising alternatives to traditional antibiotic therapies.

De Novo Antibody Design with SE(3) Diffusion

We introduce IgDiff, an antibody variable domain diffusion model based on a general protein backbone diffusion framework, which was extended to handle multiple chains. Assessing the designability and novelty of the structures generated with our model, we find that IgDiff produces highly designable antibodies that can contain novel binding regions. The backbone dihedral angles of sampled structures show good agreement with a reference antibody distribution. We verify these designed antibodies experimentally and find that all express with high yield. Finally, we compare our model with a state-of-the-art generative backbone diffusion model on a range of antibody design tasks, such as the design of the complementarity determining regions or the pairing of a light chain to an existing heavy chain, and show improved properties and designability.

Toward Antibody Production in Genome-Minimized Bacillus subtilis Strains

Bacillus subtilis is a bacterial cell factory with outstanding protein secretion capabilities that has been deployed as a workhorse for the production of industrial enzymes for more than a century. Nevertheless, the production of other proteins with B. subtilis, such as antibody formats, has thus far been challenging due to specific requirements that relate to correct protein folding and disulfide bond formation upon export from the cytoplasm. In the present study, we explored the possibility of producing functional antibody formats, such as scFvs and scFabs, using the genome-reduced Midi- and MiniBacillus strain lineage. The applied workflow included selection of optimal chassis strains, appropriate expression vectors, signal peptides, growth media, and analytical methods to verify the functionality of the secreted antibody fragments. The production of scFv fragments was upscaled to the 1 L bioreactor level. As demonstrated for a human C-reactive protein-binding scFv antibody by mass spectrometry, biolayer interferometry, circular dichroism, free thiol cross-linking with N-ethylmaleimide, and nano-differential scanning fluorimetry, MidiBacillus strains can secrete fully functional, natively folded, disulfide-bonded, and thermostable antibody fragments. We therefore conclude that genome-reduced B. subtilis chassis strains are capable of secreting high-quality antibody fragments.

New insights into antibody structure with implications for specificity, variable region restriction and isotype choice

The mystery surrounding the mechanisms by which antibody diversity is generated was largely settled in the 1970s by the discoveries of variable gene rearrangements and somatic hypermutation. This led to the paradigm that immunoglobulins are composed of two independent domains - variable and constant - that confer specificity and effector functions, respectively. However, since these early discoveries, there have been a series of observations of communication between the variable and constant domains that affects the overall antibody structure, which suggests that immunoglobulins have a more complex, interconnected functionality than previously thought. Another unresolved issue has been the genesis of 'restricted' antibody responses, characterized by the use of only a few variable region gene segments, despite the enormous potential combinatorial diversity. In this Perspective, we place recent findings related to immunoglobulin structure and function in the context of these immunologically important, historically unsolved problems to propose a new model for how antibody specificity is achieved without autoreactivity.

Computational electrostatic engineering of nanobodies for enhanced SARS-CoV-2 receptor binding domain recognition

This study presents a novel computational approach for engineering nanobodies (Nbs) for improved interaction with receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Using Protein Structure Reliability reports, RBD (7VYR_R) was selected and refined for subsequent Nb-RBD interactions. By leveraging electrostatic complementarity (EC) analysis, we engineered and characterized five Electrostatically Complementary Nbs (ECSb1-ECSb5) based on the CeVICA library's SR6c3 Nb. Through targeted modifications in the complementarity-determining regions (CDR) and framework regions (FR), we optimized electrostatic interactions to improve binding affinity and specificity. The engineered Nbs (ECSb3, ECSb4, and ECSb5) demonstrated high binding specificity for AS3, CA1, and CA2 epitopes. Interestingly, ECSb1 and ECSb2 selectively engaged with AS3 and CA1 instead of AS1 and AS2, respectively, due to a preference for residues that conferred superior binding complementarities. Furthermore, ECSbs significantly outperformed SR6c3 Nb in MM/GBSA results, notably, ECSb4 and ECSb3 exhibited superior binding free energies of -182.58 kcal.mol-1 and -119.07 kcal.mol-1, respectively, compared to SR6c3 (-105.50 kcal.mol-1). ECSbs exhibited significantly higher thermostability (100.4-148.3 kcal·mol⁻1) compared to SR6c3 (62.6 kcal·mol⁻1). Similarly, enhanced electrostatic complementarity was also observed for ECSb4-RBD and ECSb3-RBD (0.305 and 0.390, respectively) relative to SR6c3-RBD (0.233). Surface analyses confirmed optimized electrostatic patches and reduced aggregation propensity in the engineered Nb. This integrated EC and structural engineering approach successfully developed engineered Nbs with enhanced binding specificity, increased thermostability, and reduced aggregation, laying the groundwork for novel therapeutic applications targeting the SARS-CoV-2 spike protein.

Epitope and Paratope Mapping of a SUMO-Remnant Antibody Using Cross-Linking Mass Spectrometry and Molecular Docking

The small ubiquitin-like modifier (SUMO) is an important post-translational modification that regulates the function of various proteins essential for DNA damage repair, genome integrity, and cell homeostasis. To identify protein SUMOylation effectively, an enrichment step is necessary, often requiring exogenous gene expression in cells and immunoaffinity purification of SUMO-remnant peptides following tryptic digestion. Previously, an antibody was developed to enrich tryptic peptides containing the remnant NQTGG on the receptor lysine, although the specifics of the structural interaction motif remained unclear. This study integrates de novo sequencing, intact mass spectrometry, cross-linking mass spectrometry, and molecular docking to elucidate the structural interaction motifs of a SUMO-remnant antibody. Additional cross-linking experiments were performed using SUMOylated peptides and high-field asymmetric waveform ion mobility spectrometry (FAIMS) to enhance the sensitivity and confirm interactions at the paratope interface. This study establishes a robust framework for characterizing antibody-antigen interactions, offering valuable insights into the structural basis of SUMO-remnant peptide recognition.

A conformational fingerprint for amyloidogenic light chains

Both immunoglobulin light-chain (LC) amyloidosis (AL) and multiple myeloma (MM) share the overproduction of a clonal LC. However, while LCs in MM remain soluble in circulation, AL LCs misfold into toxic-soluble species and amyloid fibrils that accumulate in organs, leading to distinct clinical manifestations. The significant sequence variability of LCs has hindered the understanding of the mechanisms driving LC aggregation. Nevertheless, emerging biochemical properties, including dimer stability, conformational dynamics, and proteolysis susceptibility, distinguish AL LCs from those in MM under native conditions. This study aimed to identify a2 conformational fingerprint distinguishing AL from MM LCs. Using small-angle X-ray scattering (SAXS) under native conditions, we analyzed four AL and two MM LCs. We observed that AL LCs exhibited a slightly larger radius of gyration and greater deviations from X-ray crystallography-determined or predicted structures, reflecting enhanced conformational dynamics. SAXS data, integrated with molecular dynamics simulations, revealed a conformational ensemble where LCs adopt multiple states, with variable and constant domains either bent or straight. AL LCs displayed a distinct, low-populated, straight conformation (termed H state), which maximized solvent accessibility at the interface between constant and variable domains. Hydrogen-deuterium exchange mass spectrometry experimentally validated this H state. These findings reconcile diverse experimental observations and provide a precise structural target for future drug design efforts.

Nanobody fusion enhances production of difficult-to-produce secretory proteins

Secretory protein expression in mammalian cells is widely used in various fields, including biomedical research and biopharmaceutical production. However, achieving high-level expression of certain secretory proteins/peptides can be challenging. The naturally occurring N1 fragment of the prion protein is one of these difficult-to-produce secretory proteins, which hinders our understanding of its biological functions and limits its potential as a therapeutic molecule. To improve N1 production, we screened several well-folded protein domains and found that fusing N1 with a camelid nanobody (Nb) improved its translocation into the endoplasmic reticulum and significantly enhanced its secretion. Nb fusion does not alter the translocation mechanism, which remains dependent on the Sec61-Sec62-Sec63 complex. This approach also resulted in a significant increase in N1 production in the mouse brain using recombinant adeno-associated virus. Furthermore, fusing Nb to another unstructured protein, Shadoo (without glycosylphosphatidylinositol anchor), or a peptide hormone, somatostatin, also greatly increased their production, demonstrating the applicability of this approach to other proteins and peptides. The enhancement of N1 production is comparable or better than Fc fusion, and the effect is observed with all tested camelid Nb but not with a shark Nb and to a lesser extent with a human immunoglobulin heavy chain variable region. Importantly, the Nb in the fusion protein retained its antigen-binding capability, paving the way for the development of a dual-functional protein. Collectively, we present a novel strategy for enhancing the production of secretory proteins, which holds great promise in creating functional biological molecules for a wide range of applications.

Heavy chain variants affect light and heavy chains assembly of monoclonal antibody expressed by Pichia pastoris

Monoclonal Antibody accounts for the largest share of recombinant protein drugs and is the primary choice for the treatment of various diseases. In this study, the monoclonal antibody Eptinezumab was expressed by a yeast host Pichia pastoris. Although the expression and secretion of light chain was efficient, the assembly efficiency between light and heavy chains was low. As the retention of the heavy chain in endoplasmic reticulum may trigger protein degradation, ERAD ubiquitination-related genes were then knocked out separately but it only led to minor improvement effect. Expression of splitted heavy chain variants further revealed that although endoplasmic reticulum retention of the heavy chain upregulated KAR2 expression, it did not affect the assembly efficiency of the light and heavy chains. It was inferred that binding of complete heavy chains to KAR2 spatially affected the assembly between light and heavy chains. Design and screening of KAR2 variants that facilitating full-length antibody assembly could be preferentially considered in future.

Design of intrinsically disordered region binding proteins

Intrinsically disordered proteins and peptides play key roles in biology, but the lack of defined structures and the high variability in sequence and conformational preferences has made targeting such systems challenging. We describe a general approach for designing proteins that bind intrinsically disordered protein regions in diverse extended conformations with side chains fitting into complementary binding pockets. We used the approach to design binders for 39 highly diverse unstructured targets and obtain designs with pM to 100 nM affinities in 34 cases, testing ∼22 designs per target (including polar targets). The designs function in cells and as detection reagents, and are specific for their intended targets in all-by-all binding experiments. Our approach is a major step towards a general solution to the intrinsically disordered protein and peptide recognition problem.

Unveiling the new chapter in nanobody engineering: advances in traditional construction and AI-driven optimization

Nanobodies (Nbs), miniature antibodies consisting solely of the variable region of heavy chains, exhibit unique properties such as small size, high stability, and strong specificity, making them highly promising for disease diagnosis and treatment. The engineering production of Nbs has evolved into a mature process, involving library construction, screening, and expression purification. Different library types, including immune, naïve, and synthetic/semi-synthetic libraries, offer diverse options for various applications, while display platforms like phage display, cell surface display, and non-surface display provide efficient screening of target Nbs. Recent advancements in artificial intelligence (AI) have opened new avenues in Nb engineering. AI's exceptional performance in protein structure prediction and molecular interaction simulation has introduced novel perspectives and tools for Nb design and optimization. Integrating AI with traditional experimental methods is anticipated to enhance the efficiency and precision of Nb development, expediting the transition from basic research to clinical applications. This review comprehensively examines the latest progress in Nb engineering, emphasizing library construction strategies, display platform technologies, and AI applications. It evaluates the strengths and weaknesses of various libraries and display platforms and explores the potential and challenges of AI in predicting Nb structure, antigen-antibody interactions, and optimizing physicochemical properties.

Targeted Therapies: The Role of Monoclonal Antibodies in Disease Management

Monoclonal antibodies (mAbs) are a key class of biotherapeutic medicines used to treat a wide range of diseases, such as cancer, infectious diseases, autoimmune disorders, cardiovascular diseases, and hemophilia. They can be engineered for greater effectiveness and specific applications while maintaining their structural elements for immune targeting. Traditional immunoglobulin treatments have limited therapeutic uses and various adverse effects. That makes mAbs show rapid growth in the pharmaceutical market, with over 250 mAbs in clinical studies. Although mAbs offer higher specificity, they are less effective against complex antigens. They have become essential in treating diseases with limited medical options, providing innovative solutions that improve patients' quality of life through increasing survival rates, shortening the length of stay in hospitals with an improved treatment outcome, and reducing side effects. This review outlines the mechanisms, applications, and advancements of mAbs, highlighting their transformative role in modern medicine and their potential to shape future therapeutic interventions.

Escherichia coli and Pichia pastoris: microbial cell-factory platform for -full-length IgG production

Owing to the unmet demand, the pharmaceutical industry is investigating an alternative host to mammalian cells to produce antibodies for a variety of therapeutic and research applications. Regardless of some disadvantages, Escherichia coli and Pichia pastoris are the preferred microbial hosts for antibody production. Despite the fact that the production of full-length antibodies has been successfully demonstrated in E. coli, which has mostly been used to produce antibody fragments, such as: antigen-binding fragments (Fab), single-chain fragment variable (scFv), and nanobodies. In contrast, Pichia, a eukaryotic microbial host, is mostly used to produce glycosylated full-length antibodies, though hypermannosylated glycan is a major challenge. Advanced strategies, such as the introduction of human-like glycosylation in endotoxin-edited E. coli and cell-free system-based glycosylation, are making progress in creating human-like glycosylation profiles of antibodies in these microbes. This review begins by explaining the structural and functional requirements of antibodies and continues by describing and analyzing the potential of E. coli and P. pastoris as hosts for providing a favorable environment to create a fully functional antibody. In addition, authors compare these microbes on certain features and predict their future in antibody production. Briefly, this review analyzes, compares, and highlights E. coli and P. pastoris as potential hosts for antibody production.

Natural killer cell engagers for cancer immunotherapy

This review article explores the rapidly evolving field of bi-, tri-, and multi-specific NK cell engagers (NKCEs), highlighting their potential as a cutting-edge approach in cancer immunotherapy. NKCEs offer a significant advancement over conventional monoclonal antibodies (mAbs) by enhancing Antibody-Dependent Cellular Cytotoxicity (ADCC). They achieve this by stably and selectively binding to both NK cell activating receptors and tumor-associated antigens (TAAs). Unlike traditional mAbs, which depend on the relatively transient interaction between their Fc region and CD16a, NKCEs establish more robust connections with a range of activating receptors (e.g., CD16a, NKG2D, NKp30, NKp46, NKG2C) and inhibitory receptors (e.g., Siglec-7) on NK cells, thereby increasing cancer cell killing efficacy and specificity. This review article critically examines the strategies for engineering bi-, tri-, and multi-specific NKCEs for cancer immunotherapy, providing an in-depth analysis of the latest advancements in NKCE platform technologies currently under development by pharmaceutical and biotech companies and discussing the preclinical and clinical progress of these products. While NKCEs show great promise, the review underscores the need for continued research to optimize their therapeutic efficacy and to overcome obstacles related to NK cell functionality in cancer patients. Ultimately, this article presents an overview of the current landscape and future prospects of NKCE-based cancer immunotherapy, emphasizing its potential to revolutionize cancer treatment.

In Situ Ag-Seeded Lamellar Ti3C2 Nanosheets: An Electroactive Interface for Noninvasive Diagnosis of Oral Carcinoma via Salivary TNF-α Sensing

In the fast-paced quest for early cancer detection, noninvasive screening techniques have emerged as game-changers, offering simple and accessible avenues for precession diagnostics. In line with this, our study highlights the potential of silver nanoparticle-decorated titanium carbide MXene nanosheets (Ti3C2_AgNPs) as an electroactive interface for the noninvasive diagnosis of oral carcinoma based on the prevalence of the salivary biomarker, tumor necrosis factor-α (TNF-α). An in situ reduction was utilized to synthesize the Ti3C2_AgNPs nanohybrid, wherein Ti3C2 acts as the reducing agent, and the resulting nanohybrid was subjected to various characterization techniques to examine the optical, structural, and morphological attributes. The results revealed that spherical AgNPs formed on the surface of Ti3C2 MXene nanosheets by virtue of the low-valent Ti species present in Ti3C2, which facilitated the reduction of AgNO3 to AgNPs. Furthermore, the electrochemical characterization of the nanohybrid-modified screen-printed electrode (Ti3C2_AgNPs/SPE) indicated enhanced heterogeneous electron transfer kinetics. With these encouraging results, the Ti3C2_AgNPs nanohybrid was employed as an immobilization matrix for TNF-α antibodies and applied for electrochemical sensing. Analytical studies of the fabricated immunosensor, conducted by differential pulse voltammetry (DPV), exhibited a broader linear range (1 to 180 pg mL-1), a low limit of detection (0.97 pg mL-1), and high sensitivity (1.214 μA mL pg-1 cm-2) and specificity, even in artificial saliva, indicating its reliability for oral carcinoma diagnosis. Therefore, the Ti3C2_AgNP nanohybrid seems a promising candidate for the effective sensing of TNF-α and could also be explored for other biomarkers.

Antibody numbering schemes: advances, comparisons and tools for antibody engineering

The evolution of antibody engineering has significantly enhanced the development of antibody-based therapeutics, enabling the creation of novel antibody formats tailored for specific applications. Since the introduction of the Kabat numbering scheme in 1977, various schemes have been developed and modified, forming the foundation for multiple antibody engineering projects. The tools associated with these schemes further facilitate the engineering process. However, discrepancies among current numbering schemes can lead to confusion. This study examines various numbering schemes and related tools, providing new insights into antibody variable domains. Improved understanding of antibody numbering and related tools holds significant potential for more precise and efficient antibody design, thereby advancing antibody-based therapeutics and diagnostics.

An allelic atlas of immunoglobulin heavy chain variable regions reveals antibody binding epitope preference resilient to SARS-CoV-2 mutation escape

Background

Although immunoglobulin (Ig) alleles play a pivotal role in the antibody response to pathogens, research to understand their role in the humoral immune response is still limited.

Methods

We retrieved the germline sequences for the IGHV from the IMGT database to illustrate the amino acid polymorphism present within germline sequences of IGHV genes. We aassembled the sequences of IgM and IgD repertoire from 130 people to investigate the genetic variations in the population. A dataset comprising 10,643 SARS-CoV-2 spike-specific antibodies, obtained from COV-AbDab, was compiled to assess the impact of SARS-CoV-2 infection on allelic gene utilization. Binding affinity and neutralizing activity were determined using bio-layer interferometry and pseudovirus neutralization assays. Primary docking was performed using ZDOCK (3.0.2) to generate the initial conformation of the antigen-antibody complex, followed by simulations of the complete conformations using Rosetta SnugDock software. The original and simulated structural conformations were visualized and presented using ChimeraX (v1.5).

Results

We present an allelic atlas of immunoglobulin heavy chain (IgH) variable regions, illustrating the diversity of allelic variants across 33 IGHV family germline sequences by sequencing the IgH repertoire of in the population. Our comprehensive analysis of SARS-CoV-2 spike-specific antibodies revealed the preferential use of specific Ig alleles among these antibodies. We observed an association between Ig alleles and antibody binding epitopes. Different allelic genotypes binding to the same RBD epitope on the spike show different neutralizing potency and breadth. We found that antibodies carrying the IGHV1-69*02 allele tended to bind to the RBD E2.2 epitope. The antibodies carrying G50 and L55 amino acid residues exhibit potential enhancements in binding affinity and neutralizing potency to SARS-CoV-2 variants containing the L452R mutation on RBD, whereas R50 and F55 amino acid residues tend to have reduced binding affinity and neutralizing potency. IGHV2-5*02 antibodies using the D56 allele bind to the RBD D2 epitope with greater binding and neutralizing potency due to the interaction between D56 on HCDR2 and K444 on RBD of most Omicron subvariants. In contrast, IGHV2-5*01 antibodies using the N56 allele show increased binding resistance to the K444T mutation on RBD.

Discussion

This study provides valuable insights into humoral immune responses from the perspective of Ig alleles and population genetics. These findings underscore the importance of Ig alleles in vaccine design and therapeutic antibody development.

Radiolabeled HER2-targeted molecular probes in breast cancer imaging: current knowledge and future prospective

Breast cancer is the most frequent non-dermatologic malignancy in women. Breast cancer is characterized by the expression of the human epidermal growth factor receptor type 2 (HER2), and the presence or lack of estrogen receptor (ER) and progesterone receptor (PR) expression. HER2 overexpression is reported in about 20 to 25% of breast cancer patients, which is usually linked to cancer progression, metastases, and poor survival. Immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) are the gold standards for determining HER2 status, even though IHC has largely focused on quantifying HER2+ status versus "other" HER2 status (including variants with low or no expression). Recent findings regarding the beneficial therapeutic effects of anti-HER2 monoclonal antibodies (mAb) in HER2low metastatic patients lead to changes in the classic definition of advanced breast cancer, and methods for precise assessment of HER2 status are being developed. As a result, various radiolabeled HER-targeted mAbs and antibody fragments have been designed to avoid repeated biopsies with potential bias due to tumor heterogeneity, including single-chain variable fragment (scFv), F(ab')2, affibody, and nanobody. These small targeting radiotracers displayed favorable biodistributions, clearance, and stability, allowing for higher image quality, shorter circulation half-life, and lower immunogenicity. This study aimed to comprehensively review the application of radiolabeled anti-HER2 antibody fragments in breast cancer in vivo imaging and provide a better understanding of targeted HER2 quantification.

Acute adverse effects of F(ab')₂AV and FabAV use for rattlesnake Envenomations: A four-year poison center study

Rattlesnake envenomations account for many of the Crotalid envenomations in the United States annually. Two antivenoms are currently available to treat Crotalid envenomation in this country: Crotalidae-polyvalent ovine immune Fab antivenom (CroFab®; FabAV) and Crotalidae equine immune F(ab')₂ antivenom (ANAVIP®; F(ab')₂AV). Few studies have compared the adverse effect rates for each. We performed a retrospective chart review of rattlesnake envenomations called to the California Poison Control System from October 2018 to August 2022. Those treated at healthcare facilities with either antivenom were included. Those treated with both antivenoms were excluded. Records were obtained from the poison center electronic medical records system. Demographic and clinical data were abstracted. "Severe" adverse events were defined as multi-organ system involvement, swelling of the patient's airway, and/or hemodynamic instability. All others were categorized as "non-severe." A total of 481 cases were included with 360 treated with FabAV and 121 with F(ab')₂AV. The median age was 47 and 46 years, and 72 % and 73 % were male, respectively. Clinical signs and symptoms of envenomation were similar in each group. The FabAV group received a median of six vials. The F(ab')₂AV group received a median of 10 vials, based on the recommended loading doses of FabAV and F(ab')2AV. Following antivenom administration, 18 individual acute non-severe AEs were reported in 12 FabAV-treated patients. Two acute non-severe AEs were reported in two F(ab')₂AV-treated patients. Rash or urticaria was the most commonly reported adverse effect in both groups after antivenom administration. Five patients (1.5 %) had severe adverse events reported in the poison center records following FabAV administration, and none were reported following F(ab')₂AV administration (p = 0.025). Overall, our poison center data suggests the rate of adverse events is low following the use of either antivenom. Our findings are limited by the lack of consistent timing data, a smaller F(ab')₂AV cohort, retrospective format, and use of poison center data.

A Comprehensive Review of the Mechanisms and Clinical Development of Monoclonal Antibodies in Cancer Therapy

Cancer is still the disease that ranks first in human mortality in the twenty-first century. In the last 20 years, the concept of molecular targeted therapy has come to the fore with the use of small molecule agents or signal transduction inhibitors that show anticancer effects for certain types of cancer. Monoclonal antibodies, which have a therapeutic effect, especially by providing signal transduction inhibition, are used clinically as first-line treatment in various types of cancer. Molecular targeted therapies are critical for eliminating the adverse effects and drug resistance problems that occur in traditional cancer treatments. This review summarizes current information on various targeted therapeutic agents, including the structure and classification of monoclonal antibodies, their production methods and mechanisms of action, the monoclonal antibodies used in clinical trials, the complement system mechanism and cancer relationship, and the relationship between complement-dependent cytotoxicity and monoclonal antibodies.

CDR identification, epitope mapping and binding affinity determination of novel monoclonal antibodies generated against human apolipoprotein B-100

In-house generated mAbs to apolipoprotein B-100 (apoB-100) clones hLDL-E8, hLDL-2D8 and hLDL-F5 were extensively studied to determine their complementarity-determining regions (CDRs), binding epitopes and affinity. RT-PCR revealed that all mAbs consisted of kappa light chains and gamma heavy chains. DNA sequencing and bioinformatic analysis showed that the variable gene and protein sequences of their CDRs shared over 50 % identity with the existing databases. The 3D structures of the mAb variable fragments (Fv) with a QSQE score above 0.7 were constructed using the SWISS-MODEL platform. The structural accuracy was confirmed by Ramachandran plots, with 99 % of amino acid residues falling within acceptable regions. Thrombolytic cleavage of apoB-100 and Western blot analysis demonstrated that hLDL-E8 and hLDL-F5 specifically bind to the T3 fragment (aa 1297-3249), whereas hLDL-2D8 binds to the T4 fragment (aa 1-1297). These findings were supported with epitope-binding assays using inhibition ELISA, which indicated that hLDL-E8 binds at different epitopes from hLDL-2D8 and has some overlap with hLDL-F5. Lastly, the binding affinity of the mAbs was examined by indirect ELISA. The average affinity constants (Kaff) for mAbs hLDL-2D8, hLDL-E8 and hLDL-F5 are 1.51 ± 0.69 × 109 Mol-1, 7.25 ± 3.56 × 108 Mol-1 and 4.39 ± 2.63 × 106 Mol-1, respectively. Additionally, the behavior of the antibodies in the dose-response curve revealed that hLDL-F5 may recognize two epitopes of apoB-100 or have very low binding affinity. In contrast, hLDL-2D8 and hLDL-E8 each recognize a single epitope. These findings provide information that will be useful when selecting mAbs for both laboratory and clinical research purposes.

Therapeutic Potential of Neutralizing Monoclonal Antibodies (nMAbs) against SARS-CoV-2 Omicron Variant

BACKGROUND

The COVID-19 pandemic has spurred significant endeavors to devise treatments to combat SARS-CoV-2. A limited array of small-molecule antiviral drugs, specifically monoclonal antibodies and interferon therapy, have been sanctioned to treat COVID-19. These treatments typically necessitate administration within ten days of symptom onset. There have been reported reductions in the effectiveness of these medications due to mutations in non-structural protein genes, particularly against Omicron subvariants. This underscores the pressing requirement for healthcare systems to continually monitor pathogen variability and its impact on the efficacy of prevention and treatments.

AIM

This review aimed to comprehend the therapeutic benefits and recent progress of nMAbs for preventing and treating the Omicron variant of SARS-CoV-2.

RESULTS AND DISCUSSION

Neutralizing monoclonal antibodies (nMAbs) provide a treatment avenue for severely affected individuals, especially those at high risk for whom vaccination is not viable. With their specific epitope affinity, they pose no significant risk of severe adverse effects. The degree of reduction in neutralization varies significantly across different monoclonal antibodies and variant combinations. For instance, Sotrovimab maintained its neutralization effectiveness against Omicron BA.1, but exhibited diminished efficacy against BA.2, BA.4, BA.5, and BA.2.12.1.

CONCLUSION

Bebtelovimab has been observed to preserve its efficacy against all subtypes of the Omicron variant. Subsequently, WKS13, mAb-39, 19n01, F61-d2 cocktail, etc., have become effective. This review has highlighted the therapeutic implications of nMAbs in SARS-CoV-2 Omicron treatment and the progress of COVID-19 drug discovery.

A novel method for recombinant mammalian-expressed S-HBsAg virus-like particle production for assembly status analysis and improved anti-HBs serology

The Hepatitis B surface antigen (HBsAg) as the only lipid-associated envelope protein of the Hepatitis B virus (HBV) acts as cellular attachment and entry mediator of HBV making it the main target of neutralizing antibodies to provide HBV immunity after infection or vaccination. Despite its central role in inducing protective immunity, there is however a surprising lack of comparative studies examining different HBsAgs and their ability to detect anti-HBs antibodies. On the contrary, various time-consuming complex HBsAg production protocols have been established, which result in structurally and functionally insufficiently characterized HBsAg. Here, we present an easy-to-perform, streamlined and robust method for recombinant S-HBsAg virus-like particle (VLP) production by transient expression in mammalian cells and purification from the cell lysate with the aim of displaying uniform antigenic epitopes on the surface to improve serological detection of anti-HBs antibodies. We not only compare assembly status and particle composition by transmission electron microscopy and mass photometry of our S-HBsAg and of commonly used HBsAg reference samples, but also assess their antigenic quality and functional suitability for anti-HBs antibody detection to identify the best performing sample for serological screenings. While we found that serum-isolated and recombinant HBsAg VLPs are assembled differently, our S-HBsAg VLPs detected anti-HBs antibodies with the highest sensitivity and specificity in multiplex serology when compared to yeast or serum HBsAg making it the most suitable antigen for analysis of HBV immunity through anti-HBs serostatus.

Lowering the affinity of single-chain monovalent BBB shuttle scFc-scFv8D3 prolongs its half-life and increases brain concentration

Monoclonal antibody therapeutics is a massively growing field. Progress in providing monoclonal antibody therapeutics to treat brain disorders is complicated, due to the impermeability of the blood-brain barrier (BBB) to large macromolecular structures. To date, the most successful approach for delivering antibody therapeutics to the brain is by targeting the transferrin receptor (TfR) using anti-TfR BBB shuttles, with the 8D3 antibody being one of the most extensively studied in the field. The strategy of fine-tuning TfR binding affinity has shown promise, with previous results showing an improved brain delivery of bivalent 8D3-BBB constructs. In the current study, a fine-tuning TfR affinity strategy has been employed to improve single-chain variable fragment (scFv) 8D3 (scFv8D3) affinity mutants. Initially, in silico protein-protein docking analysis was performed to identify amino acids (AAs) likely to contribute to 8D3s TfR binding affinity. Mutating the identified AAs resulted in decreased TfR binding affinity, increased blood half-life and increased brain concentration. As monovalent BBB shuttles are seemingly superior for delivering antibodies at therapeutically relevant doses, our findings and approach may be relevant for optimizing brain delivery.

Influence of previous COVID-19 exposure and vaccine type (CoronaVac, ChAdOx1 nCov-19 or BNT162b2) on antibody and cytokine (Th1 or Th2) responses

To achieve global herd immunity, widespread vaccination is the most effective strategy. Vaccines stimulate the immune system, generating cytokines and chemokines, isotype antibodies, and neutralizing antibodies; all these molecules collectively provide a more comprehensive characterization of the immune response post-vaccination. We conducted a longitudinal study in northwestern Mexico, involving 120 individuals before vaccination and after the first dose of the SARS-CoV-2 vaccine, and 46 individuals after their second dose. Our findings reveal that antibody levels stabilize over time; cytokine levels generally increase following the first dose but decrease after the second dose and higher than normal levels in IgG1 and IgG3 concentrations are present. Most of the innate cytokines determined in this study were higher after the first dose of the vaccine. Regardless of previous infection history, this finding suggests that the first dose of the vaccine is crucial and may stimulate immunity by enhancing the innate immune response. Conversely, increased levels of IL-4, indicative of a Th2 response, were found in individuals without prior exposure to the virus and in those vaccinated with CoronaVac. These results suggest that the immune response to COVID-19 vaccines is multi-faceted, with preexisting immunity potentiating a more robust innate response. Vaccine type plays a critical role, with genetic vaccines favoring a Th1 response and inactivated vaccines like CoronaVac skewing toward a Th2 profile.

Nanoparticle targeting strategies for traumatic brain injury

Nanoparticle (NP)-based drug delivery systems hold immense potential for targeted therapy and diagnosis of neurological disorders, overcoming the limitations of conventional treatment modalities. This review explores the design considerations and functionalization strategies of NPs for precise targeting of the brain and central nervous system. This review discusses the challenges associated with drug delivery to the brain, including the blood-brain barrier and the complex heterogeneity of traumatic brain injury. We also examine the physicochemical properties of NPs, emphasizing the role of size, shape, and surface characteristics in their interactions with biological barriers and cellular uptake mechanisms. The review concludes by exploring the options of targeting ligands designed to augment NP affinity and retention to specific brain regions or cell types. Various targeting ligands are discussed for their ability to mimic receptor-ligand interaction, and brain-specific extracellular matrix components. Strategies to mimic viral mechanisms to increase uptake are discussed. Finally, the emergence of antibody, antibody fragments, and antibody mimicking peptides are discussed as promising targeting strategies. By integrating insights from these scientific fields, this review provides an understanding of NP-based targeting strategies for personalized medicine approaches to neurological disorders. The design considerations discussed here pave the way for the development of NP platforms with enhanced therapeutic efficacy and minimized off-target effects, ultimately advancing the field of neural engineering.

Integrating In Silico and In Vitro Tools for Optimized Antibody Development-Design of Therapeutic Anti-oxMIF Antibodies

BACKGROUND

Rigorous assessment of antibody developability is crucial for optimizing lead candidates before progressing to clinical studies. Recent advances in predictive tools for protein structures, surface properties, stability, and immunogenicity have streamlined the development of new biologics. However, accurate prediction of the impact of single amino acid substitutions on antibody structures remains challenging, due to the diversity of complementarity-determining regions (CDRs), particularly CDR3s.

METHODS

In this study, we combined in silico tools with in vitro assessments to engineer improved antibodies against the oxidized isoform of the macrophage migration inhibitory factor (oxMIF), building on the first generation anti-oxMIF antibody imalumab.

RESULTS

We identified hydrophobic hotspots conferring increased self-interaction and aggregation propensity on imalumab, which unravels its unusually short half-life in humans. By introducing mutations into the variable regions, we addressed these liabilities. Structural prediction tools and molecular dynamics simulations guided the selection of mutations, which were then experimentally validated. The lead candidate antibody, C0083, demonstrated reduced hydrophobicity and self-interaction due to the restructuring of its heavy chain CDR3 loop. Despite these structural changes, C0083 retained target specificity and binding affinity to oxMIF.

CONCLUSIONS

Altogether, this study shows that a small number of well-selected mutations was sufficient to substantially improve the biophysicochemical properties of imalumab.

Antibody-Based Immunotherapies for the Treatment of Hematologic Malignancies

Despite the great advancements in treatment strategies for hematological malignancies (HMs) over the years, their effective treatment remains challenging. Conventional treatment strategies are burdened with several serious drawbacks limiting their effectiveness and safety. Improved understanding of tumor immunobiology has provided novel anti-cancer strategies targeting selected immune response components. Currently, immunotherapy is counted as the fourth pillar of oncological treatment (together with surgery, chemo- and radiotherapy) and is becoming standard in the treatment regimen, alone or in combination therapy. Several categories of immunotherapies have been developed and are currently being assessed in clinical trials for the treatment of blood cancers, including immune checkpoint inhibitors, antigen-targeted antibodies, antibody-drug conjugates, tumor vaccines, and adoptive cell therapies. However, monoclonal antibodies (mAbs) and their derivatives have achieved the most notable clinical outcome so far. Since the approval of rituximab for treating B-cell malignancies, the availability of mAbs against tumor-specific surface molecules for clinical use has flourished. Antibody-based therapy has become one of the most successful strategies for immunotherapeutic cancer treatment in the last few decades, and many mAbs have already been introduced into standard treatment protocols for some hematologic malignancies. To further increase the efficacy of mAbs, they can be conjugated to radioisotopes or cytostatic drugs, so-called antibody-drug conjugates. Moreover, with the growing recognition of T-cell immunity's role in cancer development, strategies aimed at enhancing T cell activation and inhibiting mechanisms that suppress T cell function are actively being developed. This review provides a comprehensive overview of the current status of immunotherapeutic strategies based on monoclonal antibodies and their derivatives, including antibody-drug conjugates, bispecific T-cell engagers, and checkpoint inhibitors, approved for the treatment of various HMs.

ANTIPASTI: Interpretable prediction of antibody binding affinity exploiting normal modes and deep learning

The high binding affinity of antibodies toward their cognate targets is key to eliciting effective immune responses, as well as to the use of antibodies as research and therapeutic tools. Here, we propose ANTIPASTI, a convolutional neural network model that achieves state-of-the-art performance in the prediction of antibody binding affinity using as input a representation of antibody-antigen structures in terms of normal mode correlation maps derived from elastic network models. This representation captures not only structural features but energetic patterns of local and global residue fluctuations. The learnt representations are interpretable: they reveal similarities of binding patterns among antibodies targeting the same antigen type, and can be used to quantify the importance of antibody regions contributing to binding affinity. Our results show the importance of the antigen imprint in the normal mode landscape, and the dominance of cooperative effects and long-range correlations between antibody regions to determine binding affinity.

Polybodies: Next-generation clinical antibodies

Conventional antibodies [full-length and fragments: F(ab')2, fragment antigen-binding (Fab), single-chain variable fragment (scFv), variable heavy domain of heavy chain antibody (VHH)] are monospecific, first-generation antibodies, that have dominated the biopharmaceuticals field. However, protein engineering approaches has led to the advent of the next-generation antibodies (polybodies), which are significant improvement over the conventional antibodies. Polybodies comprise polyspecific and/or polyvalent antibodies that enable a single antibody to target multiple specific antigens simultaneously. Polybodies are superior to first-generation antibodies (more efficacious, broad-spectrum, resistance resilient, customizable, etc.) and provide a cost-effective healthcare solution. This review addresses recent developments in polybodies, highlighting their superiority over conventional antibodies and offering future perspectives to encourage the generation of innovative immunotherapies.

Structural trends in antibody-antigen binding interfaces: a computational analysis of 1833 experimentally determined 3D structures

Antibodies are attractive therapeutic candidates due to their ability to bind cognate antigens with high affinity and specificity. Still, the underlying molecular rules governing the antibody-antigen interface remain poorly understood, making in silico antibody design inherently difficult and keeping the discovery and design of novel antibodies a costly and laborious process. This study investigates the characteristics of antibody-antigen binding interfaces through a computational analysis of more than 850,000 atom-atom contacts from the largest reported set of antibody-antigen complexes with 1833 nonredundant, experimentally determined structures. The analysis compares binding characteristics of conventional antibodies and single-domain antibodies (sdAbs) targeting both protein- and peptide antigens. We find clear patterns in the number antibody-antigen contacts and amino acid frequencies in the paratope. The direct comparison of sdAbs and conventional antibodies helps elucidate the mechanisms employed by sdAbs to compensate for their smaller size and the fact that they harbor only half the number of complementarity-determining regions compared to conventional antibodies. Furthermore, we pinpoint antibody interface hotspot residues that are often found at the binding interface and the amino acid frequencies at these positions. These findings have direct potential applications in antibody engineering and the design of improved antibody libraries.

Strategies to boost antibody selectivity in oncology

Antibodies in oncology are being equipped with toxic cargoes and effector functions that can kill cells at very low concentrations. A key challenge is that most targets on cancer cells are also present on at least some healthy cells. Shared targets can result in off-tumor binding and compromise the safety and potential of therapeutic candidates. In this review, we survey strategies that can help direct biologics to cancer sites more selectively. These strategies are becoming increasingly feasible thanks to advances in molecular design and engineering. The objective is to create therapeutics that exploit changes in cancer and leverage the human body infrastructure, enabling therapeutics that discriminate not just self from non-self but diseased from healthy tissue.

A comprehensive overview of recent advances in generative models for antibodies

Therapeutic antibodies are an important class of biopharmaceuticals. With the rapid development of deep learning methods and the increasing amount of antibody data, antibody generative models have made great progress recently. They aim to solve the antibody space searching problems and are widely incorporated into the antibody development process. Therefore, a comprehensive introduction to the development methods in this field is imperative. Here, we collected 34 representative antibody generative models published recently and all generative models can be divided into three categories: sequence-generating models, structure-generating models, and hybrid models, based on their principles and algorithms. We further studied their performance and contributions to antibody sequence prediction, structure optimization, and affinity enhancement. Our manuscript will provide a comprehensive overview of the status of antibody generative models and also offer guidance for selecting different approaches.

Dynamics of antibody engagement of red blood cells in vivo and in vitro

Exposure to allogenic red blood cells (RBCs), either through pregnancy or transfusion, can result in alloimmunization, which can lead to severe hemolytic transfusion reactions and pregnancy complications. Passively administered antibodies can be used to prevent alloimmunization, where steric hindrance of allogeneic epitopes has been postulated as one mechanism whereby antibody engagement may prevent RBC alloimmunization. However, the dynamics of antibody engagement on the RBC surface has remained difficult to study. To examine this, we leveraged the HOD (HEL, OVA and Duffy) model system and Fcγ receptor knockout recipients to define the dynamics of antibody engagement of the Duffy antigen in the absence of RBC clearance or antigen modulation. Using this approach, the on-rate of antibody engagement of HOD RBCs was very similar in vivo and in vitro, with high levels of antibody binding observed within minutes of HOD RBC exposure. In contrast, the off-rate of HOD RBC bound antibody was relatively slow, with appreciable dissociation not being observed for an hour. However, the dynamics of antibody interactions with HOD changed significantly when antibody decorated HOD RBCs were exposed to free antibody. Despite the presence of prebound antibody, free antibody rapidly associated with HOD RBCs, with the rate of free antibody association observed being faster in vivo than in vitro. Importantly, antibody association and dissociation occurred in the absence of any appreciable changes in RBC clearance, antigen modulation or complement deposition, suggesting that differences in antibody levels observed reflected actual differences in the dynamics of antibody binding. These results suggest that while antibodies appear to be relatively static on the cell surface once bound, antibody engagement can be quite dynamic, especially in the face of free antibody in solution. These results not only have implications in the mechanisms of antibody-mediated immunosuppression, but also the potential use of other antibody-based approaches designed to prevent hemolytic transfusion reactions or target antigens in vivo in general.

Predicting Structural Consequences of Antibody Light Chain N-Glycosylation in AL Amyloidosis

Background/Objectives: Antibody light chains form amyloid fibrils that lead to progressive tissue damage in amyloid light chain (AL) amyloidosis. The properties of each patient's unique light chain appear to determine its propensity to form amyloid. One factor is N-glycosylation, which is more frequent in amyloid-associated light chains than in light chains from the normal immune repertoire. However, the mechanisms underlying this association are unknown. Here, we investigate the frequency and position within the light chain sequence of the N-glycosylation sequence motif, or sequon. Methods: Monoclonal light chains from AL amyloidosis and multiple myeloma were identified from the AL-Base repository. Polyclonal light chains were obtained from the Observed Antibody Space resource. We compared the fraction of light chains from each group harboring an N-glycosylation sequon, and the positions of these sequons within the sequences. Results: Sequons are enriched among AL-associated light chains derived from a subset of precursor germline genes. Sequons are observed at multiple positions, which differ between the two types of light chains, κ and λ, but are similar between light chains from AL amyloidosis and multiple myeloma. Positions of sequons map to residues with surface-exposed sidechains that are compatible with the folded structures of light chains. Within the known structures of λ AL amyloid fibrils, many residues where sequons are observed are buried, inconsistent with N-glycosylation. Conclusions: There is no clear structural rationale for why N-glycosylation of κ light chains is associated with AL amyloidosis. A better understanding of the roles of N-glycosylation in AL amyloidosis is required before it can be used as a marker for disease risk.

2D-CEX-FcRn-MS to Study Structure/Function Relation of mAb Charge Variants

The automated elucidation of the interplay between monoclonal antibody (mAb) structure and function using two-dimensional liquid chromatography-mass spectrometry (2D-LC-MS) is reported. Charge variants, induced through forced degradation, are resolved by first-dimension (1D) cation-exchange chromatography (CEX) and subsequently collected in loops installed on a multiple heart-cutting valve prior to transfer to second-dimension (2D) neonatal crystallizable fragment receptor (FcRn) affinity chromatography coupled with MS. As such, binding affinity of the latter mAb variants can elegantly be assessed and a first glimpse of identity provided. To maximize MS sensitivity, charge variants are unfolded upon eluting from the 2D affinity column by postcolumn addition of a denaturing solution. Further structural details, i.e., modification sites and chain distribution, are unraveled by a multidimensional LC-MS (mD-LC-MS) setup incorporating 1D CEX and parallel online middle-up and bottom-up LC-MS analysis in the subsequent dimensions. Identified charge variants could be ranked according to their affinity for FcRn. Binding is predominantly impacted by heavy chain (HC) M253 oxidation and to a lesser extend, M429 oxidation. Oxidation of both HCs more drastically affects FcRn interaction compared to single-chain oxidation, and the more oxidation, the less binding. Other modifications, such as HC glycosylation, HC N385/390, and N326 deamidation or HC C-terminal processing, are not shown to affect binding. The streamlined platform is challenged against the established workflow involving offline collection of charge variants and structural and functional assessment by, respectively, LC-MS and enzyme-linked immunosorbent assay (ELISA). A decent correlation is demonstrated between the binding affinity measured with ELISA and 2D FcRn affinity chromatography. In addition, throughput is improved (7-fold), material requirements are substantially reduced (2 orders of magnitude), and sample preparation artifacts and loss are minimized. With the simultaneous determination of mAb structure and function, the current study takes the concept of multiattribute analysis to the next level, thereby contributing to the future development of safer and more effective antibody therapeutics.

A Brief Chronicle of Antibody Research and Technological Advances

This review briefly traces the historical development of antibody research and related technologies. The path from early perceptions of immunity to the emergence of modern immunotherapy has been marked by pivotal discoveries and technological advances. Early insights into immunity led to the development of vaccination and serotherapy. The elucidation of antibody structure and function paved the way for monoclonal antibody technology and its application in diagnosis and therapy. Breakthroughs in genetic engineering have enabled the production of humanized antibodies and the advances in Fc engineering, thereby increasing therapeutic efficacy. The discovery of immune checkpoints and cytokines revolutionized the treatment of cancer and autoimmune diseases. The field continues to evolve rapidly with the advent of antibody-drug conjugates, bispecific antibodies, and CAR T-cell therapies. As we face global health challenges, antibody research remains at the forefront of medical innovation and offers promising solutions for the future.

Unlocking the Gates: Therapeutic Agents for Noninvasive Drug Delivery Across the Blood-Brain Barrier

The blood-brain barrier (BBB) is a highly selective network of various cell types that acts as a filter between the blood and the brain parenchyma. Because of this, the BBB remains a major obstacle for drug delivery to the central nervous system (CNS). In recent years, there has been a focus on developing various modifiable platforms, such as monoclonal antibodies (mAbs), nanobodies (Nbs), peptides, and nanoparticles, as both therapeutic agents and carriers for targeted drug delivery to treat brain cancers and diseases. Methods for bypassing the BBB can be invasive or noninvasive. Invasive techniques, such as transient disruption of the BBB using low pulse electrical fields and intracerebroventricular infusion, lack specificity and have numerous safety concerns. In this review, we will focus on noninvasive transport mechanisms that offer high levels of biocompatibility, personalization, specificity and are regarded as generally safer than their invasive counterparts. Modifiable platforms can be designed to noninvasively traverse the BBB through one or more of the following pathways: passive diffusion through a physio-pathologically disrupted BBB, adsorptive-mediated transcytosis, receptor-mediated transcytosis, shuttle-mediated transcytosis, and somatic gene transfer. Through understanding the noninvasive pathways, new applications, including Chimeric Antigen Receptors T-cell (CAR-T) therapy, and approaches for drug delivery across the BBB are emerging.

Enhancing Fc-mediated effector functions of monoclonal antibodies: The example of HexaBodies

Since the approval of the CD20-targeting monoclonal antibody (mAb) rituximab for the treatment of lymphoma in 1997, mAb therapy has significantly transformed cancer treatment. With over 90 FDA-approved mAbs for the treatment of various hematological and solid cancers, modern cancer treatment relies heavily on these therapies. The overwhelming success of mAbs as cancer therapeutics is attributed to their broad applicability, high safety profile, and precise targeting of cancer-associated surface antigens. Furthermore, mAbs can induce various anti-tumor cytotoxic effector mechanisms including antibody-dependent cellular cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP), and complement-dependent cytotoxicity (CDC), all of which are mediated via their fragment crystallizable (Fc) domain. Over the past decades, these effector mechanisms have been substantially improved through Fc domain engineering. In this review, we will outline the different approaches to enhance Fc effector functions via Fc engineering of mAbs, with a specific emphasis on the so-called "HexaBody" technology, which is designed to enhance the hexamerization of mAbs on the target cell surface, thereby inducing greater complement activation, CDC, and receptor clustering. The review will summarize the development, preclinical, and clinical testing of several HexaBodies designed for the treatment of B-cell malignancies, as well as the potential use of the HexaBody technology beyond Fc-mediated effector functions.

Antibody-mediated control mechanisms of viral infections

Antibodies generated after vaccination or natural pathogen exposure are essential mediators of protection against many infections. Most studies with viruses have focused on antibody neutralization, in which protection is conferred by the fragment antigen binding region (Fab) through targeting of different steps in the viral lifecycle including attachment, internalization, fusion, and egress. Beyond neutralization, the fragment crystallizable (Fc) region of antibodies can integrate innate and adaptive immune responses by engaging complement components and distinct Fc gamma receptors (FcγR) on different host immune cells. In this review, we discuss recent advances in our understanding of antibody neutralization and Fc effector functions, and the assays used to measure them. Additionally, we describe the contexts in which these mechanisms are associated with protection against viruses and highlight how Fc-FcγR interactions can improve the potency of antibody-based therapies.

p-IgGen: a paired antibody generative language model

SUMMARY

A key challenge in antibody drug discovery is designing novel sequences that are free from developability issues-such as aggregation, polyspecificity, poor expression, or low solubility. Here, we present p-IgGen, a protein language model for paired heavy-light chain antibody generation. The model generates diverse, antibody-like sequences with pairing properties found in natural antibodies. We also create a finetuned version of p-IgGen that biases the model to generate antibodies with 3D biophysical properties that fall within distributions seen in clinical-stage therapeutic antibodies.

AVAILABILITY AND IMPLEMENTATION

The model and inference code are freely available at www.github.com/oxpig/p-IgGen. Cleaned training data are deposited at doi.org/10.5281/zenodo.13880874.

Immunotherapies in breast cancer: harnessing the cancer immunity cycle

INTRODUCTION

Immunotherapies have found limited success in breast cancerdue to significant challenges within the tumor that block T-cell activity and function.

AREAS COVERED

The current review discusses clinically relevant immunotherapeutics and trials within the framework of the cancer-immunity cycle.

EXPERT OPINION

Current therapies such as antibody-drug conjugates and immune checkpoint blockade require proper biomarker selection, such as PD1 expression and the degree of tumor-infiltrating lymphocyte (TIL) infiltration to subset potential responders. HER2 and other tumor-associated antigens have served as valuable benchmarks for developing novel therapies, such as antibody engagers and CAR T-cells. However, further research is essential to identify and validate new target antigens that can enhance therapeutic efficacy and broaden the clinical applicability of these approaches.

Discovery of Therapeutic Antibodies Targeting Complex Multi-Spanning Membrane Proteins

Complex integral membrane proteins, which are embedded in the cell surface lipid bilayer by multiple transmembrane spanning polypeptides, encompass families of proteins that are important target classes for drug discovery. These protein families include G protein-coupled receptors, ion channels, transporters, enzymes, and adhesion molecules. The high specificity of monoclonal antibodies and the ability to engineer their properties offers a significant opportunity to selectively bind these target proteins, allowing direct modulation of pharmacology or enabling other mechanisms of action such as cell killing. Isolation of antibodies that bind these types of membrane proteins and exhibit the desired pharmacological function has, however, remained challenging due to technical issues in preparing membrane protein antigens suitable for enabling and driving antibody drug discovery strategies. In this article, we review progress and emerging themes in defining discovery strategies for a generation of antibodies that target these complex membrane protein antigens. We also comment on how this field may develop with the emerging implementation of computational techniques, artificial intelligence, and machine learning.