Antibody Structure and Function: The Basis for Engineering Therapeutics

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.

An important consideration when expressing mAbs in Escherichiacoli

Monoclonal antibodies (mAbs) are a driving force in the biopharmaceutical industry. Therapeutic mAbs are usually produced in mammalian cells, but there has been a push towards the use of alternative production hosts, such as Escherichia coli. When the genes encoding for a mAb heavy and light chains are codon-optimized for E. coli expression, a truncated form of the heavy chain can form along with the full-length product. In this work, the role of codon optimization in the formation of a truncated product was investigated. This study used the amino acid sequences of several therapeutic mAbs and multiple optimization algorithms. It was found that several algorithms incorporate sequences that lead to a truncated product. Approaches to avoid this truncated form are discussed.

Antibody-Antibiotic Conjugates: A Comprehensive Review on Their Therapeutic Potentials Against BacterialInfections

INTRODUCTION

Antibodies are significant agents in the immune system and have proven to be effective in treating bacterial infections. With the advancement of antibody engineering in recent decades, antibody therapy has evolved widely.

AIM

This review aimed to investigate a new method as a therapeutic platform for the treatment of bacterial infections and explore the novel features of this method in conferring pathogen specificity to broad-spectrum antibiotics.

MATERIAL AND METHODS

A literature review was conducted addressing the following topics about antibody-antibiotic conjugates (AACs): (1) structure and mechanism of action; (2) clinical effectiveness; (3) advantages and disadvantages.

RESULT

Antibody conjugates are designed to build upon the progress made in the development of monoclonal antibodies for the treatment of diseases. Despite the growing emergence of antibiotic resistance among pathogenic bacteria worldwide, novel antimicrobials have not been sufficiently expanded to combat the global crisis of antibiotic resistance. A recently developed strategy for the treatment of infectious diseases is the use of AACs, which are specifically activated only in host cells.

CONCLUSION

A novel therapeutic AAC employs an antibody to deliver the antibiotic to the bacteria. The AACs can release potent antibacterial components that unconjugated forms may not exhibit with an appropriate therapeutic index. This review highlights how this science has guided the design principles of an impressive AAC and discusses how the AAC model promises to enhance the antibiotic effect against bacterial infections.

VHH Nanobody Versatility against Pentameric Ligand-Gated Ion Channels

Pentameric ligand-gated ion channels provide rapid chemical-electrical signal transmission between cells in the central and peripheral nervous system. Their dysfunction is associated with many nervous system disorders. They are composed of five identical (homomeric receptors) or homologous (heteromeric receptors) subunits. VHH nanobodies, or single-chain antibodies, are the variable domain, VHH, of antibodies that are composed of the heavy chain only from camelids. Their unique structure results in many specific biochemical and biophysical properties that make them an excellent alternative to conventional antibodies. This Perspective explores the published VHH nanobodies which have been isolated against pentameric ligand-gated ion channel subfamilies. It outlines the genetic and chemical modifications available to alter nanobody function. An assessment of the available functional and structural data indicate that it is feasible to create therapeutic agents and impart, through their modification, a given desired modulatory effect of its target receptor for current stoichiometric-specific VHH nanobodies.

Understanding the Specific Implications of Amino Acids in the Antibody Development

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

Disposable electrochemical biosensors for the detection of bacteria in the light of antimicrobial resistance

Persistent and inappropriate use of antibiotics is causing rife antimicrobial resistance (AMR) worldwide. Common bacterial infections are thus becoming increasingly difficult to treat without the use of last resort antibiotics. This has necessitated a situation where it is imperative to confirm the infection to be bacterial, before treating it with antimicrobial speculatively. Conventional methods of bacteria detection are either culture based which take anywhere between 24 and 96 hor require sophisticated molecular analysis equipment with libraries and trained operators. These are difficult propositions for resource limited community healthcare setups of developing or less developed countries. Customized, inexpensive, point-of-care (PoC) biosensors are thus being researched and developed for rapid detection of bacterial pathogens. The development and optimization of disposable sensor substrates is the first and crucial step in development of such PoC systems. The substrates should facilitate easy charge transfer, a high surface to volume ratio, be tailorable by the various bio-conjugation chemistries, preserve the integrity of the biorecognition element, yet be inexpensive. Such sensor substrates thus need to be thoroughly investigated. Further, if such systems were made disposable, they would attain immunity to biofouling. This article discusses a few potential disposable electrochemical sensor substrates deployed for detection of bacteria for environmental and healthcare applications. The technologies have significant potential in helping reduce bacterial infections and checking AMR. This could help save lives of people succumbing to bacterial infections, as well as improve the overall quality of lives of people in low- and middle-income countries.

Heat-induced structural and chemical changes to a computationally designed miniprotein

The de novo design of miniprotein inhibitors has recently emerged as a new technology to create proteins that bind with high affinity to specific therapeutic targets. Their size, ease of expression, and apparent high stability makes them excellent candidates for a new class of protein drugs. However, beyond circular dichroism melts and hydrogen/deuterium exchange experiments, little is known about their dynamics, especially at the elevated temperatures they seemingly tolerate quite well. To address that and gain insight for future designs, we have focused on identifying unintended and previously overlooked heat-induced structural and chemical changes in a particularly stable model miniprotein, EHEE_rd2_0005. Nuclear magnetic resonance (NMR) studies suggest the presence of dynamics on multiple time and temperature scales. Transiently elevating the temperature results in spontaneous chemical deamidation visible in the NMR spectra, which we validate using both capillary electrophoresis and mass spectrometry (MS) experiments. High temperatures also result in greatly accelerated intrinsic rates of hydrogen exchange and signal loss in NMR heteronuclear single quantum coherence spectra from local unfolding. These losses are in excellent agreement with both room temperature hydrogen exchange experiments and hydrogen bond disruption in replica exchange molecular dynamics simulations. Our analysis reveals important principles for future miniprotein designs and the potential for high stability to result in long-lived alternate conformational states.

FcRn Inhibitor Therapies in Neurologic Diseases

In the last decade, the landscape of treating autoimmune diseases has evolved with the emergence and approval of novel targeted therapies. Several new biological agents offer selective and target-specific immunotherapy and therefore fewer side effects, such as neonatal Fc receptor (FcRn)-targeting therapy. Neonatal Fc receptor-targeted therapies are engineered to selectively target FcRn through various methods, such as Fc fragments or monoclonal anti-FcRn antibodies. These approaches enhance the breakdown of autoantibodies by blocking the immunoglobulin G recycling pathway. This mechanism reduces overall plasma immunoglobulin levels, including the levels of pathogenic autoantibodies, without affecting the other immunoglobulin class immunoglobulin A, immunoglobulin E, immunoglobulin M, and immunoglobulin D levels. Drugs that inhibit FcRn include efgartigimod, rozanolixizumab, batoclimab, and nipocalimab. These medications can be administered either intravenously or subcutaneously. Numerous clinical trials are currently underway to investigate their effectiveness, safety, and tolerability in various neurological conditions, including myasthenia gravis and other neurological disorders such as chronic inflammatory demyelinating polyneuropathy, myositis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. Positive results from clinical trials of efgartigimod and rozanolixizumab led to their approval for the treatment of generalized myasthenia gravis. Additional clinical trials are still ongoing. Neonatal Fc receptor inhibitor agents seem to be well tolerated. Reported adverse events include headache (most commonly observed with efgartigimod and rozanolixizumab), upper respiratory tract infection, urinary tract infection, diarrhea, pyrexia, and nausea. Additionally, some of these agents may cause transient hypoalbuminemia and hypercholesterolemia notably reported with batoclimab and nipocalimab. In this review, we discuss the available clinical data for FcRN inhibitor agents in treating different neurological autoimmune diseases.

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.

Immunoglobulin constant regions provide stabilization to the paratope and enforce epitope specificity

Constant domains in antibody molecules at the level of the Fab (CH1 and CL) have long been considered to be simple scaffolding elements that physically separate the paratope-defining variable (V) region from the effector function-mediating constant (C) regions. However, due to recent findings that C domains of different isotypes can modulate the fine specificity encoded in the V region, elucidating the role of C domains in shaping the paratope and influencing specificity is a critical area of interest. To dissect the relative contributions of each C domain to this phenomenon, we generated antibody fragments with different C regions omitted, using a set of antibodies targeting capsular polysaccharides from the fungal pathogen, Cryptococcus neoformans. Antigen specificity mapping and functional activity measurements revealed that V region-only antibody fragments exhibited poly-specificity to antigenic variants and extended to recognition of self-antigens, while measurable hydrolytic activity of the capsule was greatly attenuated. To better understand the mechanistic origins of the remarkable loss of specificity that accompanies the removal of C domains from identical paratopes, we performed molecular dynamics simulations which revealed increased paratope plasticity in the scFv relative to the corresponding Fab. Together, our results provide insight into how the remarkable specificity of immunoglobulins is governed and maintained at the level of the Fab through the enforcement of structural restrictions on the paratope by CH1 domains.

Prediction of Paratope-Epitope Pairs Using Convolutional Neural Networks

Antibodies play a central role in the adaptive immune response of vertebrates through the specific recognition of exogenous or endogenous antigens. The rational design of antibodies has a wide range of biotechnological and medical applications, such as in disease diagnosis and treatment. However, there are currently no reliable methods for predicting the antibodies that recognize a specific antigen region (or epitope) and, conversely, epitopes that recognize the binding region of a given antibody (or paratope). To fill this gap, we developed ImaPEp, a machine learning-based tool for predicting the binding probability of paratope-epitope pairs, where the epitope and paratope patches were simplified into interacting two-dimensional patches, which were colored according to the values of selected features, and pixelated. The specific recognition of an epitope image by a paratope image was achieved by using a convolutional neural network-based model, which was trained on a set of two-dimensional paratope-epitope images derived from experimental structures of antibody-antigen complexes. Our method achieves good performances in terms of cross-validation with a balanced accuracy of 0.8. Finally, we showcase examples of application of ImaPep, including extensive screening of large libraries to identify paratope candidates that bind to a selected epitope, and rescoring and refining antibody-antigen docking poses.

Structural characterization of antibody-responses from Zolgensma treatment provides the blueprint for the engineering of an AAV capsid suitable for redosing

Monoclonal antibodies (mAbs) are useful tools to dissect the neutralizing antibody response against the adeno-associated virus (AAV) capsids used as gene therapy delivery vectors. This study structurally characterizes the interactions of 21 human-derived antibodies from patients treated with the AAV9 vector, Zolgensma ® , utilizing high-resolution cryo-electron microscopy. The majority of the bound antibodies 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 some antibodies inducing structural perturbations of the capsid upon binding. Key surface capsid amino acid residues were identified facilitating the design of capsid variants with an antibody escape phenotype, with the potential to expand the patient cohort treatable with AAV9 vectors to include those that were previously excluded due to their pre-existing neutralizing antibodies, and possibly also to those requiring redosing.

Cutting-edge approaches for targeted drug delivery in breast cancer: beyond conventional therapies

Breast cancer is a global health challenge with staggering statistics underscoring its pervasive impact. The burden of this disease is measured in terms of its prevalence and the challenges it poses to healthcare systems, necessitating a closer look at its epidemiology and impact. Current breast cancer treatments, including surgery, chemotherapy, radiation therapy, and targeted therapies, have made significant strides in improving patient outcomes. However, they are not without limitations, often leading to adverse effects and the development of drug resistance. This comprehensive review delves into the complex landscape of breast cancer, including its incidence, current treatment modalities, and the inherent limitations of existing therapeutic approaches. It also sheds light on the promising role of nanotechnology, encompassing both inorganic and organic nanoparticles equipped with the ability to selectively deliver therapeutic agents to tumor sites, in the battle against breast cancer. The review also addresses the emerging therapies, their associated challenges, and the future prospects of targeted drug delivery in breast cancer management.

LectoScape: A Highly Multiplexed Imaging Platform for Glycome Analysis and Biomedical Diagnosis

Glycosylation, a fundamental biological process, involves the attachment of glycans to proteins, lipids, and RNA, and it plays a crucial role in various biological pathways. It is of great significance to obtain the precise spatial distribution of glycosylation modifications at the cellular and tissue levels. Here, we introduce LectoScape, an innovative method enabling detailed imaging of tissue glycomes with up to 1 μm resolution through image mass cytometry (IMC). This method utilizes 12 distinct, nonoverlapping lectins selected via microarray technology, enabling the multiplexed detection of a wide array of glycans. Furthermore, we developed an efficient labeling strategy for these lectins. Crucially, our approach facilitates the concurrent imaging of diverse glycan motifs, including N-glycan and O-glycan, surpassing the capabilities of existing technologies. Using LectoScape, we have successfully delineated unique glycan structures in various cell types, enhancing our understanding of the glycan distribution across human tissues. Our method has identified specific glycan markers, such as α2,3-sialylated Galβ1, 3GalNAc in O-glycan, and terminal GalNAc, as diagnostic indicators for cervical intraepithelial neoplasia. This highlights the potential of LectoScape in cancer diagnostics through the detection of abnormal glycosylation patterns.

Structural Characterization of a Pathogenic Antibody Underlying Vaccine-Induced Immune Thrombotic Thrombocytopenia (VITT)

Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a rare but dangerous side effect of adenoviral-vectored COVID-19 vaccines. VITT had been linked to production of autoantibodies recognizing platelet factor 4 (PF4). Here, we characterize anti-PF4 antibodies obtained from a VITT patient's blood. Intact mass measurements indicate that a significant fraction of these antibodies represent a limited number of clones. MS analysis of large antibody fragments (the light chain and the Fc/2 and Fd fragments of the heavy chain) confirms the monoclonal nature of this component of the anti-PF4 antibodies repertoire and reveals the presence of a mature complex biantennary N-glycan within the Fd segment. Peptide mapping using two complementary proteases and LC-MS/MS was used to determine the amino acid sequence of the entire light chain and over 98% of the heavy chain (excluding a short N-terminal segment). The sequence analysis allows the monoclonal antibody to be assigned to the IgG2 subclass and verifies that the light chain belongs to the λ-type. Incorporation of enzymatic de-N-glycosylation into the peptide mapping routine allows the N-glycan in the Fab region of the antibody to be localized to the framework 3 region of the VH domain. This novel N-glycosylation site is the result of a single mutation within the germline sequence. Peptide mapping also provides information on lower-abundance (polyclonal) components of the anti-PF4 antibody ensemble, revealing the presence of all four subclasses (IgG1-IgG4) and both types of the light chain (λ and κ). This case study demonstrates the power of combining the intact, middle-down, and bottom-up MS approaches for meaningful characterization of ultralow quantities of pathogenic antibodies extracted directly from patients' blood.

A systemic approach to identifying sequence frameworks that decrease mAb production in a transient Chinese hamster ovary cell expression system

Monoclonal antibodies (mAbs) are often engineered at the sequence level for improved clinical performance yet are rarely evaluated prior to candidate selection for their "developability" characteristics, namely expression, which can necessitate additional resource investments to improve the manufacturing processes for problematic mAbs. A strong relationship between primary sequence and expression has emerged, with slight differences in amino acid sequence resulting in titers differing by up to an order of magnitude. Previous work on these "difficult-to-express" (DTE) mAbs has shown that these phenotypes are driven by post-translational bottlenecks in antibody folding, assembly, and secretion processes. However, it has been difficult to translate these findings across cell lines and products. This work presents a systematic approach to study the impact of sequence variation on mAb expression at a larger scale and under more industrially relevant conditions. The analysis found 91 mutations that decreased transient expression of an IgG1κ in Chinese hamster ovary (CHO) cells and revealed that mutations at inaccessible residues, especially those leading to decreases in residue hydrophobicity, are not favorable for high expression. This workflow can be used to better understand sequence determinants of mAb expression to improve candidate selection procedures and reduce process development timelines.

Forskolin reverses the O-GlcNAcylation dependent decrease in GABAAR current amplitude at hippocampal synapses possibly at a neurosteroid site on GABAARs

GABAergic transmission is influenced by post-translational modifications, like phosphorylation, impacting channel conductance, allosteric modulator sensitivity, and membrane trafficking. O-GlcNAcylation is a post-translational modification involving the O-linked attachment of β-N-acetylglucosamine on serine/threonine residues. Previously we reported an acute increase in O-GlcNAcylation elicits a long-term depression of evoked GABAAR inhibitory post synaptic currents (eIPSCs) onto hippocampal principal cells. Importantly, O-GlcNAcylation and phosphorylation can co-occur or compete for the same residue; whether they interact in modulating GABAergic IPSCs is unknown. We tested this by recording IPSCs from hippocampal principal cells and pharmacologically increased O-GlcNAcylation, before or after increasing serine phosphorylation using the adenylate cyclase activator, forskolin. Although forskolin had no significant effect on baseline eIPSC amplitude, we found that a prior increase in O-GlcNAcylation unmasks a forskolin-dependent increase in eIPSC amplitude, reversing the O-GlcNAc-induced eIPSC depression. Inhibition of adenylate cyclase or protein kinase A did not prevent the potentiating effect of forskolin, indicating serine phosphorylation is not the mechanism. Surprisingly, increasing O-GlcNAcylation also unmasked a potentiating effect of the neurosteroids 5α-pregnane-3α,21-diol-20-one (THDOC) and progesterone on eIPSC amplitude, mimicking forskolin. Our findings show under conditions of heightened O-GlcNAcylation, the neurosteroid site on synaptic GABAARs is accessible to agonists, permitting strengthening of synaptic inhibition.

Enhanced therapeutic potential of antibody fragment via IEDDA-mediated site-specific albumin conjugation

BACKGROUND

The use of single-chain variable fragments (scFvs) for treating human diseases, such as cancer and immune system disorders, has attracted significant attention. However, a critical drawback of scFv is its extremely short serum half-life, which limits its therapeutic potential. Thus, there is a critical need to prolong the serum half-life of the scFv for clinical applications. One promising serum half-life extender for therapeutic proteins is human serum albumin (HSA), which is the most abundant protein in human serum, known to have an exceptionally long serum half-life. However, conjugating a macromolecular half-life extender to a small protein, such as scFv, often results in a significant loss of its critical properties.

RESULTS

In this study, we conjugated the HSA to a permissive site of scFv to improve pharmacokinetic profiles. To ensure minimal damage to the antigen-binding capacity of scFv upon HSA conjugation, we employed a site-specific conjugation approach using a heterobifunctional crosslinker that facilitates thiol-maleimide reaction and inverse electron-demand Diels-Alder reaction (IEDDA). As a model protein, we selected 4D5scFv, derived from trastuzumab, a therapeutic antibody used in human epithermal growth factor 2 (HER2)-positive breast cancer treatment. We introduced a phenylalanine analog containing a very reactive tetrazine group (frTet) at conjugation site candidates predicted by computational methods. Using the linker TCO-PEG4-MAL, a single HSA molecule was site-specifically conjugated to the 4D5scFv (4D5scFv-HSA). The 4D5scFv-HSA conjugate exhibited HER2 binding affinity comparable to that of unmodified 4D5scFv. Furthermore, in pharmacokinetic profile in mice, the serum half-life of 4D5scFv-HSA was approximately 12 h, which is 85 times longer than that of 4D5scFv.

CONCLUSIONS

The antigen binding results and pharmacokinetic profile of 4D5scFv-HSA demonstrate that the site-specifically albumin-conjugated scFv retained its binding affinity with a prolonged serum half-life. In conclusion, we developed an effective strategy to prepare site-specifically albumin-conjugated 4D5scFv, which can have versatile clinical applications with improved efficacy.

Δfur mutant as a potential live attenuated vaccine (LAV) candidate protects American eels (Anguilla rostrata) from Vibrio harveyi infection

The eel farming industry is highly susceptible to Vibriosis. Although various types of vaccines against Vibriosis have been investigated, there is limited research on decreasing the virulence of Vibrions through gene knockout and utilizing it as live attenuated vaccines (LAV). In this study, we aim to develop a LAV candidate against Vibrio harveyi infection in American eels (Anguilla rostrata) using a ferric uptake regulator (fur) gene mutant strain of V. harveyi (Δfur mutant). After the eels were administrated with the Δfur mutant at the dose of 4 × 102 cfu/g body weight, the phagocytic activity of the leucocytes, plasma IgM antibody titers, activity of lysozyme and Superoxide Dismutase (SOD) enzyme, and gene expression levels of 18 immune related proteins were detected to evaluate the protection effect of the LAV. Preliminary findings suggest that the LAV achieved over 60% relative percent survival (RPS) after the American eels were challenged by a wild-type strain of V. harveyi infection on 28 and 42 days post the immunization (dpi). The protection was mainly attributed to increased plasma IgM antibody titers, higher levels of lysozyme, enhanced activity of SOD and some regulated genes encoded immune related proteins. Together, the Δfur mutant strain of V. harveyi, as a novel LAV vaccine, demonstrates promising protective effects against V. harveyi infection in American eels, thus presenting a potential candidate vaccine for fish farming.

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

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

Computational Mutagenesis of Antibody Fragments: Disentangling Side Chains from ΔΔG Predictions

The development of highly potent antibodies and antibody fragments as binding agents holds significant implications in fields such as biosensing and biotherapeutics. Their binding strength is intricately linked to the arrangement and composition of residues at the binding interface. Computational techniques offer a robust means to predict the three-dimensional structure of these complexes and to assess the affinity changes resulting from mutations. Given the interdependence of structure and affinity prediction, our objective here is to disentangle their roles. We aim to evaluate independently six side-chain reconstruction methods and ten binding affinity estimation techniques. This evaluation was pivotal in predicting affinity alterations due to single mutations, a key step in computational affinity maturation protocols. Our analysis focuses on a data set comprising 27 distinct antibody/hen egg white lysozyme complexes, each with crystal structures and experimentally determined binding affinities. Using six different side-chain reconstruction methods, we transformed each structure into its corresponding mutant via in silico single-point mutations. Subsequently, these structures undergo minimization and molecular dynamics simulation. We therefore estimate ΔΔG values based on the original crystal structure, its energy-minimized form, and the ensuing molecular dynamics trajectories. Our research underscores the critical importance of selecting reliable side-chain reconstruction methods and conducting thorough molecular dynamics simulations to accurately predict the impact of mutations. In summary, our study demonstrates that the integration of conformational sampling and scoring is a potent approach to precisely characterizing mutation processes in single-point mutagenesis protocols and crucial for computational antibody design.

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

BACKGROUND

Nanobodies, also known as VHH or single-domain antibodies, are unique antibody fragments derived solely from heavy chains. They offer advantages of small molecules and conventional antibodies, making them promising therapeutics. The paratope is the specific region on an antibody that binds to an antigen. Paratope prediction involves the identification and characterization of the antigen-binding site on an antibody. This process is crucial for understanding the specificity and affinity of antibody-antigen interactions. Various computational methods and experimental approaches have been developed to predict and analyze paratopes, contributing to advancements in antibody engineering, drug development, and immunotherapy. However, existing predictive models trained on traditional antibodies may not be suitable for nanobodies. Additionally, the limited availability of nanobody datasets poses challenges in constructing accurate models.

METHODS

To address these challenges, we have developed a novel nanobody prediction model, named NanoBERTa-ASP (Antibody Specificity Prediction), which is specifically designed for predicting nanobody-antigen binding sites. The model adopts a training strategy more suitable for nanobodies, based on an advanced natural language processing (NLP) model called BERT (Bidirectional Encoder Representations from Transformers). To be more specific, the model utilizes a masked language modeling approach named RoBERTa (Robustly Optimized BERT Pretraining Approach) to learn the contextual information of the nanobody sequence and predict its binding site.

RESULTS

NanoBERTa-ASP achieved exceptional performance in predicting nanobody binding sites, outperforming existing methods, indicating its proficiency in capturing sequence information specific to nanobodies and accurately identifying their binding sites. Furthermore, NanoBERTa-ASP provides insights into the interaction mechanisms between nanobodies and antigens, contributing to a better understanding of nanobodies and facilitating the design and development of nanobodies with therapeutic potential.

CONCLUSION

NanoBERTa-ASP represents a significant advancement in nanobody paratope prediction. Its superior performance highlights the potential of deep learning approaches in nanobody research. By leveraging the increasing volume of nanobody data, NanoBERTa-ASP can further refine its predictions, enhance its performance, and contribute to the development of novel nanobody-based therapeutics. Github repository: https://github.com/WangLabforComputationalBiology/NanoBERTa-ASP.

A Kinetically Controlled Bioconjugation Method for the Synthesis of Radioimmunoconjugates and the Development of a Domain Mapping MS-Workflow for Its Characterization

Immunoconjugates exploit the high affinity of monoclonal antibodies for a recognized antigen to selectively deliver a cytotoxic payload, such as drugs or radioactive nuclides, at the site of disease. Despite numerous techniques have been recently developed for site-selective bioconjugations of protein structures, reaction of ε-amine group of lysine residues with electrophilic reactants, such as activated esters (NHS), is the main method reported in the literature as it maintains proteins in their native conformation. Since antibodies hold a high number of lysine residues, a heterogeneous mixture of conjugates will be generated, which can result in decreased target affinity. Here, we report an intradomain regioselective bioconjugation between the monoclonal antibody Trastuzumab and the N-hydroxysuccinimide ester of the chelator 2,2',2″,2‴-(1,4,7,10-tetraazacyclododecane-1,4,7,10-tetrayl)tetraacetic acid (DOTA) by a kinetically controlled reaction adding substoichiometric quantities of the activated ester to the mAb working at slightly basic pH. Liquid chromatography-mass spectrometry (LC-MS) analyses were carried out to assess the chelator-antibody ratio (CAR) and the number of chelating moieties linked to the mAb chains. Proteolysis experiments showed four lysine residues mainly involved in bioconjugation (K188 for the light chain and K30, K293, and K417 for the heavy chain), each of which was located in a different domain. Since the displayed intradomain regioselectivity, a domain mapping MS-workflow, based on a selective domain denaturation, was developed to quantify the percentage of chelator linked to each mAb domain. The resulting immunoconjugate mixture showed an average CAR of 0.9. About a third of the heavy chains were found as monoconjugated, whereas conjugation of the chelator in the light chain was negligible. Domain mapping showed the CH3 domain bearing 13% of conjugated DOTA, followed by CH2 and VH respectively bearing 12.5 and 11% of bonded chelator. Bioconjugation was not found in the CH1 domain, whereas for the light chain, only the CL domain was conjugated (6%). Data analysis based on LC-MS quantification of different analytical levels (intact, reduced chains, and domains) provided the immunoconjugate formulation. A mixture of immunoconjugates restricted to 15 species was obtained, and the percentage of each one within the mixture was calculated. In particular, species bearing 1 DOTA with a relative abundance ranging from 4 to 20-fold, in comparison to species bearing 2DOTA, were observed. Pairing of bioconjugation under kinetic control with the developed domain mapping MS-workflow could raise the standard of chemical quality for immunoconjugates obtained with commercially available reactants.

The Role of Force Fields and Water Models in Protein Folding and Unfolding Dynamics

Protein folding is a fascinating, not fully understood phenomenon in biology. Molecular dynamics (MD) simulations are an invaluable tool to study conformational changes in atomistic detail, including folding and unfolding processes of proteins. However, the accuracy of the conformational ensembles derived from MD simulations inevitably relies on the quality of the underlying force field in combination with the respective water model. Here, we investigate protein folding, unfolding, and misfolding of fast-folding proteins by examining different force fields with their recommended water models, i.e., ff14SB with the TIP3P model and ff19SB with the OPC model. To this end, we generated long conventional MD simulations highlighting the perks and pitfalls of these setups. Using Markov state models, we defined kinetically independent conformational substates and emphasized their distinct characteristics, as well as their corresponding state probabilities. Surprisingly, we found substantial differences in thermodynamics and kinetics of protein folding, depending on the combination of the protein force field and water model, originating primarily from the different water models. These results emphasize the importance of carefully choosing the force field and the respective water model as they determine the accuracy of the observed dynamics of folding events. Thus, the findings support the hypothesis that the water model is at least equally important as the force field and hence needs to be considered in future studies investigating protein dynamics and folding in all areas of biophysics.

Engineering high affinity antigen-binders: Beyond conventional antibodies

For decades, antibodies have remained the archetypal binding proteins that can be rapidly produced with high affinity and specificity against virtually any target. A conventional antibody is still considered the prototype of a binding molecule. It is therefore not surprising that antibodies are routinely used in basic scientific and biomedical research, analytical workflows, molecular diagnostics etc. and represent the fastest growing sector in the field of biotechnology. However, several limitations associated with conventional antibodies, including stringent requirement of animal immunizations, mammalian cells for expression, issues on stability and aggregation, bulkier size and the overall time and cost of production has propelled evolution of concepts along alternative antigen binders. Rapidly evolving protein engineering approaches and high throughput screening platforms have further complemented the development of myriads of classes of non-conventional protein binders including antibody derived as well as non-antibody based molecular scaffolds. These non-canonical binders are finding use across disciplines of which diagnostics and therapeutics are the most noteworthy.

Leveraging bioanalytical characterization of fractionated monoclonal antibody pools to identify aggregation-prone and less filterable proteoforms during virus filtration

Monoclonal antibodies (mAbs) are an essential class of biotherapeutics. A platform process is used for mAb development to ensure clinically safe and stable molecules. Regulatory authorities ensure that mAb production processes include sufficient viral clearance steps to achieve less than one virus particle per million doses of product. Virus filtration is used for size-based removal of enveloped and nonenveloped viruses during downstream processing of mAbs. Process development in mAb purification relies on empirical approaches and often includes adsorptive prefiltration to mitigate virus filter fouling. Opportunities for molecular-level prediction of mAb filterability are needed to plug the existing knowledge gap in downstream processing. A molecular-level approach to understanding the factors influencing mAb filterability may reduce process development time, material loss, and processing costs due to oversized virus filters. In this work, pH step gradient fractionation was applied on polished bulk mAb feed to obtain concentrated pools of fractionated mAb variants. Biophysical properties and quality attributes of fractionated pools, including oligomeric state (size), isoelectric point profile, diffusion interaction parameters, and glycoform profile, were determined using bioanalytical methods. Filterability (loading and throughput) of fractionated pools were evaluated. Statistical methods were used to obtain correlations between quality attributes of mAb fractions and filterability on the Viresolve Pro virus filter.

Biosensing Platforms for Cardiac Biomarker Detection

Myocardial infarction (MI) is a cardiovascular disease that occurs when there is an elevated demand for myocardial oxygen as a result of the rupture or erosion of atherosclerotic plaques. Globally, the mortality rates associated with MI are steadily on the rise. Traditional diagnostic biomarkers employed in clinical settings for MI diagnosis have various drawbacks, prompting researchers to investigate fast, precise, and highly sensitive biosensor platforms and technologies. Biosensors are analytical devices that combine biological elements with physicochemical transducers to detect and quantify specific compounds or analytes. These devices play a crucial role in various fields including healthcare, environmental monitoring, food safety, and biotechnology. Biosensors developed for the detection of cardiac biomarkers are typically electrochemical, mass, and optical biosensors. Nanomaterials have emerged as revolutionary components in the field of biosensing, offering unique properties that significantly enhance the sensitivity and specificity of the detection systems. This review provides a comprehensive overview of the advancements and applications of nanomaterial-based biosensing systems. Beginning with an exploration of the fundamental principles governing nanomaterials, we delve into their diverse properties, including but not limited to electrical, optical, magnetic, and thermal characteristics. The integration of these nanomaterials as transducers in biosensors has paved the way for unprecedented developments in analytical techniques. Moreover, the principles and types of biosensors and their applications in cardiovascular disease diagnosis are explained in detail. The current biosensors for cardiac biomarker detection are also discussed, with an elaboration of the pros and cons of existing platforms and concluding with future perspectives.

Leveraging Cross-Linking Mass Spectrometry for Modeling Antibody-Antigen Complexes

Elucidating antibody-antigen complexes at the atomic level is of utmost interest for understanding immune responses and designing better therapies. Cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for mapping protein-protein interactions, suggesting valuable structural insights. However, the use of XL-MS studies to enable epitope/paratope mapping of antibody-antigen complexes is still limited up to now. XL-MS data can be used to drive integrative modeling of antibody-antigen complexes, where cross-links information serves as distance restraints for the precise determination of binding interfaces. In this approach, XL-MS data are employed to identify connections between binding interfaces of the antibody and the antigen, thus informing molecular modeling. Current literature provides minimal input about the impact of XL-MS data on the integrative modeling of antibody-antigen complexes. Here, we applied XL-MS to retrieve information about binding interfaces of three antibody-antigen complexes. We leveraged XL-MS data to perform integrative modeling using HADDOCK (active-passive residues and distance restraints strategies) and AlphaLink2. We then compared these three approaches with initial predictions of investigated antibody-antigen complexes by AlphaFold Multimer. This work emphasizes the importance of cross-linking data in resolving conformational dynamics of antibody-antigen complexes, ultimately enhancing the design of better protein therapeutics and vaccines.

Streamlined Multi-Attribute Assessment of an Array of Clinical-Stage Antibodies: Relationship Between Degradation and Stability

Clinical antibodies are an important class of drugs for the treatment of both chronic and acute diseases. Their manufacturability is subject to evaluation to ensure product quality and efficacy. One critical quality attribute is deamidation, a non-enzymatic process that is observed to occur during thermal stress, at low or high pH, or a combination thereof. Deamidation may induce antibody instability and lead to aggregation, which may pose immunogenicity concerns. The introduction of a negative charge via deamidation may impact the desired therapeutic function (i) within the complementarity-determining region, potentially causing loss of efficacy; or (ii) within the fragment crystallizable region, limiting the effector function involving antibody-dependent cellular cytotoxicity. Here we describe a transformative solution that allows for a comparative assessment of deamidation and its impact on stability and aggregation. The innovative streamlined method evaluates the intact protein in its formulation conditions. This breakthrough platform technology is comprised of a quantum cascade laser microscope, a slide cell array that allows for flexibility in the design of experiments, and dedicated software. The enhanced spectral resolution is achieved using two-dimensional correlation, co-distribution, and two-trace two-dimensional correlation spectroscopies that reveal the molecular impact of deamidation. Eight re-engineered immunoglobulin G4 scaffold clinical antibodies under control and forced degradation conditions were evaluated for deamidation and aggregation. We determined the site of deamidation, the overall extent of deamidation, and where applicable, whether the deamidation event led to self-association or aggregation of the clinical antibody and the molecular events that led to the instability. The results were confirmed using orthogonal techniques for four of the samples.

Effect of nanoporous membranes thickness in electrochemical biosensing performance: application for the detection of a wound infection biomarker

Introduction: Nanoporous alumina membranes present a honeycomb-like structure characterized by two main parameters involved in their performance in electrochemical immunosening: pore diameter and pore thickness. Although this first one has been deeply studied, the effect of pore thickness in electrochemical-based nanopore immunosensors has been less taken into consideration. Methods: In this work, the influence of the thickness of nanoporous membranes in the steric blockage is studied for the first time, through the formation of an immunocomplex in their inner walls. Finally, the optimal nanoporous membranes were applied to the detection of catalase, an enzyme related with chronic wound infection and healing. Results: Nanoporous alumina membranes with a fixed pore diameter (60 nm) and variable pore thicknesses (40, 60, 100 μm) have been constructed and evaluated as immunosensing platform for protein detection. Our results show that membranes with a thickness of 40 μm provide a higher sensitivity and lower limit-of-detection (LOD) compared to thicker membranes. This performance is even improved when compared to commercial membranes (with 20 nm pore diameter and 60 μm pore thickness), when applied for human IgG as model analyte. A label-free immunosensor using a monoclonal antibody against anti-catalase was also constructed, allowing the detection of catalase in the range of 50-500 ng/mL and with a LOD of 1.5 ng/mL. The viability of the constructed sensor in real samples was also tested by spiking artificial wound infection solutions, providing recovery values of 110% and 118%. Discussion: The results obtained in this work evidence the key relevance of the nanochannel thickness in the biosensing performance. Such findings will illuminate nanoporous membrane biosensing research, considering thickness as a relevant parameter in electrochemical-based nanoporous membrane sensors.

Degron-based bioPROTACs for controlling signaling in CAR T cells

Chimeric antigen receptor (CAR) T cells have made a tremendous impact in the clinic, but potent signaling through the CAR can be detrimental to treatment safety and efficacy. The use of protein degradation to control CAR signaling can address these issues in pre-clinical models. Existing strategies for regulating CAR stability rely on small molecules to induce systemic degradation. In contrast to small molecule regulation, genetic circuits offer a more precise method to control CAR signaling in an autonomous, cell-by-cell fashion. Here, we describe a programmable protein degradation tool that adopts the framework of bioPROTACs, heterobifunctional proteins that are composed of a target recognition domain fused to a domain that recruits the endogenous ubiquitin proteasome system. We develop novel bioPROTACs that utilize a compact four residue degron and demonstrate degradation of cytosolic and membrane protein targets using either a nanobody or synthetic leucine zipper as a protein binder. Our bioPROTACs exhibit potent degradation of CARs and can inhibit CAR signaling in primary human T cells. We demonstrate the utility of our bioPROTACs by constructing a genetic circuit to degrade the tyrosine kinase ZAP70 in response to recognition of a specific membrane-bound antigen. This circuit is able to disrupt CAR T cell signaling only in the presence of a specific cell population. These results suggest that bioPROTACs are a powerful tool for expanding the cell engineering toolbox for CAR T cells.

Tyrosine Sulfation at Antibody Light Chain CDR-1 Increases Binding Affinity and Neutralization Potency to Interleukine-4

Structure and function of therapeutic antibodies can be modulated by a variety of post-translational modifications (PTM). Tyrosine (Tyr) sulfation is a type of negatively charged PTM that occurs during protein trafficking through the Golgi. In this study, we discovered that an anti-interleukin (IL)-4 human IgG1, produced by transiently transfected HEK293 cells, contained a fraction of unusual negatively charged species. Interestingly, the isolated acidic species exhibited a two-fold higher affinity to IL-4 and a nearly four-fold higher potency compared to the main species. Mass spectrometry (MS) showed the isolated acidic species possessed an +80-Dalton from the expected mass, suggesting an occurrence of Tyr sulfation. Consistent with this hypothesis, we show the ability to control the acidic species during transient expression with the addition of Tyr sulfation inhibitor sodium chlorate or, conversely, enriched the acidic species from 30% to 92% of the total antibody protein when the IL-4 IgG was co-transfected with tyrosylprotein sulfotransferase genes. Further MS and mutagenesis analysis identified a Tyr residue at the light chain complementarity-determining region-1 (CDRL-1), which was sulfated specifically. These results together have demonstrated for the first time that Tyr sulfation at CDRL-1 could modulate antibody binding affinity and potency to a human immune cytokine.

Quantitative Analysis of Therapeutic Antibody Interactions with Fcγ Receptors Using High-Speed Atomic Force Microscopy

This study employed high-speed atomic force microscopy to quantitatively analyze the interactions between therapeutic antibodies and Fcγ receptors (FcγRs). Antibodies are essential components of the immune system and are integral to biopharmaceuticals. The focus of this study was on immunoglobulin G molecules, which are crucial for antigen binding via the Fab segments and cytotoxic functions through their Fc portions. We conducted real-time, label-free observations of the interactions of rituximab and mogamulizumab with the recombinant FcγRIIIa and FcγRIIa. The dwell times of FcγR binding were measured at the single-molecule level, which revealed an extended interaction duration of mogamulizumab with FcγRIIIa compared with that of rituximab. This is linked to enhanced antibody-dependent cellular cytotoxicity that is attributed to the absence of the core fucosylation of Fc-linked N-glycan. This study also emphasizes the crucial role of the Fab segments in the interaction with FcγRIIa as well as that with FcγRIIIa. This approach provided quantitative insight into therapeutic antibody interactions and exemplified kinetic proofreading, where cellular discrimination relies on ligand residence times. Observing the dwell times of antibodies on the effector molecules has emerged as a robust indicator of therapeutic antibody efficacy. Ultimately, these findings pave the way for the development of refined therapeutic antibodies with tailored interactions with specific FcγRs. This research contributes to the advancement of biopharmaceutical antibody design and optimizing antibody-based treatments for enhanced efficacy and precision.

Serum immunoglobulin or albumin binding single-domain antibodies that enable tailored half-life extension of biologics in multiple animal species

Single-domain antibody fragments (sdAbs) can be isolated from heavy-chain-only antibodies that occur in camelids or the heavy chain of conventional antibodies, that also occur in camelids. Therapeutic application of sdAbs is often complicated by their low serum half-life. Fusion to sdAb that bind to long-lived serum proteins albumin or IgG can prolong serum half-life of fusion partners. Such studies mostly focused on human application. For half-life prolongation in multiple animal species novel species cross-reacting sdAb are needed. We here describe the isolation from immunized llamas of sdAbs G6 and G13 that bound IgG of 9-10 species analysed, including horse, dog, cat, and swine, as well as sdAb A12 that bound horse, dog, swine and cat albumin. A12 bound albumin with 13 to 271 nM affinity dependent on the species. G13 affinity was difficult to determine by biolayer interferometry due to low and heterogeneous signals. G13 and G6 compete for the same binding domain on Fab fragments. Furthermore, they both lack the hallmark residues typical of camelid sdAbs derived from heavy-chain antibodies and had sequence characteristics typical of human sdAbs with high solubility and stability. This suggests they are derived from conventional llama antibodies. They most likely bind IgG through pairing with VL domains at the VH-VL interface rather than a paratope involving complementarity determining regions. None of the isolated sdAb interfered with FcRn binding to albumin or IgG, and thus do not prevent endosomal albumin/IgG-sdAb complex recycling. Fusions of albumin-binding sdAb A12 to several tetanus neurotoxin (TeNT) binding sdAbs prolonged the terminal serum half-life in piglets to about 4 days, comparable to authentic swine albumin. However, G13 conferred a much lower half-life of 0.84 days. Similarly, in horse, G13 prolonged half-life to only 1.2 days whereas A12 fused to two TeNT binding domains (T6T16A12) had a half-life of 21 days. The high half-life of T6T16A12, which earlier proved to be a highly potent TeNT antitoxin, further supports its therapeutic value. Furthermore, we have identified several additional sdAbs that enable tailored half-life extension of biologicals in multiple animal species.

Trends on Aerogel-Based Biosensors for Medical Applications: An Overview

Aerogels are unique solid-state materials composed of interconnected 3D solid networks and a large number of air-filled pores. This structure leads to extended structural characteristics as well as physicochemical properties of the nanoscale building blocks to macroscale, and integrated typical features of aerogels, such as high porosity, large surface area, and low density, with specific properties of the various constituents. Due to their combination of excellent properties, aerogels attract much interest in various applications, ranging from medicine to construction. In recent decades, their potential was exploited in many aerogels' materials, either organic, inorganic or hybrid. Considerable research efforts in recent years have been devoted to the development of aerogel-based biosensors and encouraging accomplishments have been achieved. In this work, recent (2018-2023) and ground-breaking advances in the preparation, classification, and physicochemical properties of aerogels and their sensing applications are presented. Different types of biosensors in which aerogels play a fundamental role are being explored and are collected in this manuscript. Moreover, the current challenges and some perspectives for the development of high-performance aerogel-based biosensors are summarized.

Understanding Fc function for rational vaccine design against pathogens

Antibodies represent the primary correlate of immunity following most clinically approved vaccines. However, their mechanisms of action vary from pathogen to pathogen, ranging from neutralization, to opsonophagocytosis, to cytotoxicity. Antibody functions are regulated both by antigen specificity (Fab domain) and by the interaction of their Fc domain with distinct types of Fc receptors (FcRs) present in immune cells. Increasing evidence highlights the critical nature of Fc:FcR interactions in controlling pathogen spread and limiting the disease state. Moreover, variation in Fc-receptor engagement during the course of infection has been demonstrated across a range of pathogens, and this can be further influenced by prior exposure(s)/immunizations, age, pregnancy, and underlying health conditions. Fc:FcR functional variation occurs at the level of antibody isotype and subclass selection as well as post-translational modification of antibodies that shape Fc:FcR-interactions. These factors collectively support a model whereby the immune system actively harnesses and directs Fc:FcR interactions to fight disease. By defining the precise humoral mechanisms that control infections, as well as understanding how these functions can be actively tuned, it may be possible to open new paths for improving existing or novel vaccines.

Antibody-drug conjugates in cancer therapy: innovations, challenges, and future directions

The emergence of antibody-drug conjugates (ADCs) as a potential therapeutic avenue in cancer treatment has garnered significant attention. By combining the selective specificity of monoclonal antibodies with the cytotoxicity of drug molecules, ADCs aim to increase the therapeutic index, selectively targeting cancer cells while minimizing systemic toxicity. Various ADCs have been licensed for clinical usage, with ongoing research paving the way for additional options. However, the manufacture of ADCs faces several challenges. These include identifying suitable target antigens, enhancing antibodies, linkers, and payloads, and managing resistance mechanisms and side effects. This review focuses on the strategies to overcome these hurdles, such as site-specific conjugation techniques, novel antibody formats, and combination therapy. Our focus lies on current advancements in antibody engineering, linker technology, and cytotoxic payloads while addressing the challenges associated with ADC development. Furthermore, we explore the future potential of personalized medicine, leveraging individual patients' molecular profiles, to propel ADC treatments forward. As our understanding of the molecular mechanisms driving cancer progression continues to expand, we anticipate the development of new ADCs that offer more effective and personalized therapeutic options for cancer patients.

LC-MS Approach to Decipher a Light Chain Chromatographic Peak Splitting of a Monoclonal Antibody

PURPOSE

Monoclonal antibodies (mAbs), like other protein therapeutics, are prone to various forms of degradation, some of which are difficult to distinguish from the native form yet may alter potency. A generalizable LC-MS approach was developed to enable quantitative analysis of isoAsp. In-depth understanding of product quality attributes (PQAs) enables optimization of the manufacturing process, better formulation selection, and decreases risk associated with product handling in the clinic or during shipment.

METHODS

Reversed-phase chromatographic peak splitting was observed when a mAb was exposed to elevated temperatures. Multiple LC-MS based methods were applied to identify the reason for peak splitting. The approach involved the use of complementary HPLC columns, multiple enzymatic digestions and different MS/MS ion dissociation methods. In addition, mAb potency was measured by enzyme-linked immunosorbent assay (ELISA).

RESULTS

The split peaks had identical masses, and the root cause of the peak splitting was identified as isomerization of an aspartic acid located in the complementarity-determining region (CDR) of the light chain. And the early eluting and late eluting peaks were collected and performed enzymatic digestion to confirm the isoAsp enrichment in the early eluting peak. In addition, decreased potency was observed in the same heat-stressed sample, and the increased isoAsp levels in the CDR correlate well with a decrease of potency.

CONCLUSION

Liquid chromatography-mass spectrometry (LC-MS) has been utilized extensively to assess PQAs of biological therapeutics. In this study, a generalizable LC-MS-based approach was developed to enable identification and quantitation of the isoAsp-containing peptides.

Minerals and essential amino acids of bovine colostrum: Phenotypic variability and predictive ability of mid- and near-infrared spectroscopy

Colostrum quality and volume are fundamental for calves because it is the primary supplier of antibodies and the first source of energy, carbohydrates, lipids, proteins, minerals, and vitamins for the newborn. Assessing the detailed composition (i.e., AA and mineral content) of bovine colostrum (BC) on-line and at a reasonable cost would help dairy stakeholders such as farmers or veterinarians for precision feeding purposes and industries producing preparations containing BC such as foodstuff, supplements, and medicaments. In the present study we evaluated mid- (MIRS) and near-infrared spectroscopy (NIRS) prediction ability for AA and mineral composition of individual BC. Second, we the investigated the major factors affecting the phenotypic variability of such traits also evaluating the correlations with the Ig concentration. Results demonstrated that MIRS and NIRS were able to provide sufficiently accurate predictions for all the AA. The coefficient of determination in external validation (R2V) fell, in fact, within the range of 0.70 to 0.86, with the exception of Ile, His, and Met. Only some minerals reached a sufficient accuracy (i.e., Ca, P, S, and Mg; R2V ≥ 0.66) using MIRS, and also S (R2V = 0.87) using NIRS. Phenotypically, both parity and calving season affected the variability of these BC composition traits. Heifers' colostrum was the one with the greatest concentration of Ca and P, the 2 most abundant minerals. These minerals were however very low in cows calving in summer compared with the rest of the year. The pattern of AA across parities and calving season was not linear, likely because their variability was scarcely (or not) affected by these effects. Finally, samples characterized by high IgG concentration were those presenting on average greater concentration of AA. Findings suggest that infrared spectroscopy has the potential to be used to predict certain AA and minerals, outlining the possibility of implementing on-site analyses for the evaluation of the broad-sense BC quality.

Recent Advances in the Development of Monoclonal Antibodies and Next-Generation Antibodies

mAbs are highly indispensable tools for diagnostic, prophylactic, and therapeutic applications. The first technique, hybridoma technology, was based on fusion of B lymphocytes with myeloma cells, which resulted in generation of single mAbs against a specific Ag. Along with hybridoma technology, several novel and alternative methods have been developed to improve mAb generation, ranging from electrofusion to the discovery of completely novel technologies such as B cell immortalization; phage, yeast, bacterial, ribosome, and mammalian display systems; DNA/RNA encoded Abs; single B cell technology; transgenic animals; and artificial intelligence/machine learning. This commentary outlines the evolution, methodology, advantages, and limitations of various mAb production techniques. Furthermore, with the advent of next-generation Ab technologies such as single-chain variable fragments, nanobodies, bispecific Abs, Fc-engineered Abs, Ab biosimilars, Ab mimetics, and Ab-drug conjugates, the healthcare and pharmaceutical sectors have become resourceful to develop highly specific mAb treatments against various diseases such as cancer and autoimmune and infectious diseases.

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity, and Antibody Developability

The electrostatic properties of proteins arise from the number and distribution of polar and charged residues. Electrostatic interactions in proteins play a critical role in numerous processes such as molecular recognition, protein solubility, viscosity, and antibody developability. Thus, characterizing and quantifying electrostatic properties of a protein are prerequisites for understanding these processes. Here, we present PEP-Patch, a tool to visualize and quantify the electrostatic potential on the protein surface in terms of surface patches, denoting separated areas of the surface with a common physical property. We highlight its applicability to elucidate protease substrate specificity and antibody-antigen recognition and predict heparin column retention times of antibodies as an indicator of pharmacokinetics.

Evaluation of the Ability of AlphaFold to Predict the Three-Dimensional Structures of Antibodies and Epitopes

Being able to accurately predict the three-dimensional structure of an Ab can facilitate Ab characterization and epitope prediction, with important diagnostic and clinical implications. In this study, we evaluated the ability of AlphaFold to predict the structures of 222 recently published, high-resolution Fab H and L chain structures of Abs from different species directed against different Ags. We show that although the overall Ab prediction quality is in line with the results of CASP14, regions such as the complementarity-determining regions (CDRs) of the H chain, which are prone to higher variation, are predicted less accurately. Moreover, we discovered that AlphaFold mispredicts the bending angles between the variable and constant domains. To evaluate the ability of AlphaFold to model Ab-Ag interactions based only on sequence, we used AlphaFold-Multimer in combination with ZDOCK to predict the structures of 26 known Ab-Ag complexes. ZDOCK, which was applied on bound components of both the Ab and the Ag, succeeded in assembling 11 complexes, whereas AlphaFold succeeded in predicting only 2 of 26 models, with significant deviations in the docking contacts predicted in the rest of the molecules. Within the 11 complexes that were successfully predicted by ZDOCK, 9 involved short-peptide Ags (18-mer or less), whereas only 2 were complexes of Ab with a full-length protein. Docking of modeled unbound Ab and Ag was unsuccessful. In summary, our study provides important information about the abilities and limitations of using AlphaFold to predict Ab-Ag interactions and suggests areas for possible improvement.

Long-term Prophylaxis Against Aerosolized Marburg Virus in Nonhuman Primates With an Afucosylated Monoclonal Antibody

Marburg virus (MARV) causes a hemorrhagic fever disease in human and nonhuman primates with high levels of morbidity and mortality. Concerns about weaponization of aerosolized MARV have spurred the development of nonhuman primate (NHP) models of aerosol exposure. To address the potential threat of aerosol exposure, a monoclonal antibody that binds MARV glycoprotein was tested, MR186YTE, for its efficacy as a prophylactic. MR186YTE was administered intramuscularly to NHPs at 15 or 5 mg/kg 1 month prior to MARV aerosol challenge. Seventy-five percent (3/4) of the 15 mg/kg dose group and 50% (2/4) of the 5 mg/kg dose group survived. Serum analyses showed that the NHP dosed with 15 mg/kg that succumbed to infection developed an antidrug antibody response and therefore had no detectable MR186YTE at the time of challenge. These results suggest that intramuscular dosing of mAbs may be a clinically useful prophylaxis for MARV aerosol exposure.

Identifying promising sequences for protein engineering using a deep transformer protein language model

Protein engineers aim to discover and design novel sequences with targeted, desirable properties. Given the near limitless size of the protein sequence landscape, it is no surprise that these desirable sequences are often a relative rarity. This makes identifying such sequences a costly and time-consuming endeavor. In this work, we show how to use a deep transformer protein language model to identify sequences that have the most promise. Specifically, we use the model's self-attention map to calculate a Promise Score that weights the relative importance of a given sequence according to predicted interactions with a specified binding partner. This Promise Score can then be used to identify strong binders worthy of further study and experimentation. We use the Promise Score within two protein engineering contexts-Nanobody (Nb) discovery and protein optimization. With Nb discovery, we show how the Promise Score provides an effective way to select lead sequences from Nb repertoires. With protein optimization, we show how to use the Promise Score to select site-specific mutagenesis experiments that identify a high percentage of improved sequences. In both cases, we also show how the self-attention map used to calculate the Promise Score can indicate which regions of a protein are involved in intermolecular interactions that drive the targeted property. Finally, we describe how to fine-tune the transformer protein language model to learn a predictive model for the targeted property, and discuss the capabilities and limitations of fine-tuning with and without knowledge transfer within the context of protein engineering.

Quenchbodies That Enable One-Pot Detection of Antigens: A Structural Perspective

Quenchbody (Q-body) is a unique, reagentless, fluorescent antibody whose fluorescent intensity increases in an antigen-concentration-dependent manner. Q-body-based homogeneous immunoassay is superior to conventional immunoassays as it does not require multiple immobilization, reaction, and washing steps. In fact, simply mixing the Q-body and the sample containing the antigen enables the detection of the target antigen. To date, various Q-bodies have been developed to detect biomarkers of interest, including haptens, peptides, proteins, and cells. This review sought to describe the principle of Q-body-based immunoassay and the use of Q-body for various immunoassays. In particular, the Q-bodies were classified from a structural perspective to provide useful information for designing Q-bodies with an appropriate objective.

A photoaffinity glycan-labeling approach to investigate immunoglobulin glycan-binding partners

Glycans play a pivotal role in biology. However, because of the low-affinity of glycan-protein interactions, many interaction pairs remain unknown. Two important glycoproteins involved in B-cell biology are the B-cell receptor and its secreted counterpart, antibodies. It has been indicated that glycans expressed by these B-cell-specific molecules can modulate immune activation via glycan-binding proteins. In several autoimmune diseases, an increased prevalence of variable domain glycosylation of IgG autoantibodies has been observed. Especially, the hallmarking autoantibodies in rheumatoid arthritis, anti-citrullinated protein antibodies, carry a substantial amount of variable domain glycans. The variable domain glycans expressed by these autoantibodies are N-linked, complex-type, and α2-6 sialylated, and B-cell receptors carrying variable domain glycans have been hypothesized to promote selection of autoreactive B cells via interactions with glycan-binding proteins. Here, we use the anti-citrullinated protein antibody response as a prototype to study potential in solution and in situ B-cell receptor-variable domain glycan interactors. We employed SiaDAz, a UV-activatable sialic acid analog carrying a diazirine moiety that can form covalent bonds with proximal glycan-binding proteins. We show, using oligosaccharide engineering, that SiaDAz can be readily incorporated into variable domain glycans of both antibodies and B-cell receptors. Our data show that antibody variable domain glycans are able to interact with inhibitory receptor, CD22. Interestingly, although we did not detect this interaction on the cell surface, we captured CD79 β glycan-B-cell receptor interactions. These results show the utility of combining photoaffinity labeling and oligosaccharide engineering for identifying antibody and B-cell receptor interactions and indicate that variable domain glycans appear not to be lectin cis ligands in our tested conditions.

Effects of glycans and hinge on dynamics in the IgG1 Fc

The crystallizable fragment (Fc) domain of immunoglobulin subclass IgG1 antibodies is engineered for a wide variety of pharmaceutical applications. Two important structural variables in Fc constructs are the hinge region connecting the Fc to the antigen binding fragments (Fab) and the glycans present in various glycoforms. These components affect receptor binding interactions that mediate immune activation. To design new antibody drugs, a robust in silico method for linking stability to structural changes is necessary. In this work, all-atom simulations were used to compare the dynamic behavior of the four structural variants arising from presence or absence of the hinge and glycans. We expressed the simplest of these constructs, the 'minimal Fc' with no hinge and no glycans, in Escherichia coli and report its crystal structure. The 'maximal Fc' that includes full hinge and G0F/G1F glycans is based on a previously reported structure, Protein Data Bank (PDB) ID: 5VGP. These, along with two intermediate structures (with only the glycans or with only the hinge) were used to independently measure the stability effects of the two structural variables using umbrella sampling simulations. Principal component analysis (PCA) was used to determine free energy effects along the Fc's dominant mode of motion. This work provides a comprehensive picture of the effects of hinge and glycans on Fc dynamics and stability.Communicated by Ramaswamy H. Sarma.

Structure and Dynamics Guiding Design of Antibody Therapeutics and Vaccines

Antibodies and other new antibody-like formats have emerged as one of the most rapidly growing classes of biotherapeutic proteins. Understanding the structural features that drive antibody function and, consequently, their molecular recognition is critical for engineering antibodies. Here, we present the structural architecture of conventional IgG antibodies alongside other formats. We emphasize the importance of considering antibodies as conformational ensembles in solution instead of focusing on single-static structures because their functions and properties are strongly governed by their dynamic nature. Thus, in this review, we provide an overview of the unique structural and dynamic characteristics of antibodies with respect to their antigen recognition, biophysical properties, and effector functions. We highlight the numerous technical advances in antibody structure prediction and design, enabled by the vast number of experimentally determined high-quality structures recorded with cryo-EM, NMR, and X-ray crystallography. Lastly, we assess antibody and vaccine design strategies in the context of structure and dynamics.

Emerging Applications of Nanobiosensors in Pathogen Detection in Water and Food

Food and waterborne illnesses are still a major concern in health and food safety areas. Every year, almost 0.42 million and 2.2 million deaths related to food and waterborne illness are reported worldwide, respectively. In foodborne pathogens, bacteria such as Salmonella, Shiga-toxin producer Escherichia coli, Campylobacter, and Listeria monocytogenes are considered to be high-concern pathogens. High-concern waterborne pathogens are Vibrio cholerae, leptospirosis, Schistosoma mansoni, and Schistosima japonicum, among others. Despite the major efforts of food and water quality control to monitor the presence of these pathogens of concern in these kinds of sources, foodborne and waterborne illness occurrence is still high globally. For these reasons, the development of novel and faster pathogen-detection methods applicable to real-time surveillance strategies are required. Methods based on biosensor devices have emerged as novel tools for faster detection of food and water pathogens, in contrast to traditional methods that are usually time-consuming and are unsuitable for large-scale monitoring. Biosensor devices can be summarized as devices that use biochemical reactions with a biorecognition section (isolated enzymes, antibodies, tissues, genetic materials, or aptamers) to detect pathogens. In most cases, biosensors are based on the correlation of electrical, thermal, or optical signals in the presence of pathogen biomarkers. The application of nano and molecular technologies allows the identification of pathogens in a faster and high-sensibility manner, at extremely low-pathogen concentrations. In fact, the integration of gold, silver, iron, and magnetic nanoparticles (NP) in biosensors has demonstrated an improvement in their detection functionality. The present review summarizes the principal application of nanomaterials and biosensor-based devices for the detection of pathogens in food and water samples. Additionally, it highlights the improvement of biosensor devices through nanomaterials. Nanomaterials offer unique advantages for pathogen detection. The nanoscale and high specific surface area allows for more effective interaction with pathogenic agents, enhancing the sensitivity and selectivity of the biosensors. Finally, biosensors' capability to functionalize with specific molecules such as antibodies or nucleic acids facilitates the specific detection of the target pathogens.

Studying Intermolecular Interactions in an Antibody-Drug Conjugate Through Chemical Screening and Computational Modeling

Antibody-drug conjugates (ADCs) combine the selectivity of antibodies with the cytotoxicity of drug payloads to yield highly targeted and potent therapeutics. Owing to the need to chemically modify residues for attachment of the payload and their more complex structure compared to either component alone, ADCs can present additional challenges related to stability of the final drug product. Here, we report for the first time the use of high-throughput experimental screens and computational techniques to tune the conformational and colloidal behavior of a monomethyl auristatin F-based ADC. The ADC, which exhibits high opalescence with strongly attractive protein-protein interactions, is transformed into a more stable structure by experimentally traversing a library of more than ∼100 formulations. A significant reduction in turbidity and increase in diffusion interaction parameter is observed by varying properties such as pH and ionic strength. Computational modeling rationalized these changes and pointed to the presence of attractive electrostatic interactions between ADC molecules facilitated by the drug payload and histidine residues. Taken together, the experimental and computational work presented provides a general roadmap of studies to perform during ADC development to find stable formulations, while the mechanistic learnings can be applied towards the design and stabilization of other IgG1-based ADCs.