Development Of Therapeutic Antibodies Research Articles

IgG1 Is the Optimal Subtype for Treating Atherosclerosis by Inducing M2 Macrophage Differentiation, and Is Independent of the FcγRIIA Gene Polymorphism

In recent years, it has been established that atherosclerosis is an autoimmune disease. However, little is currently known about the role of FcγRIIA in atherosclerosis. Herein, we sought to investigate the relationship between FcγRIIA genotypes and the effectiveness of different IgG subclasses in treating atherosclerosis. We constructed and produced different subtypes of IgG and Fc-engineered antibodies. In vitro, we observed the effect of different subtypes of IgG and Fc-engineered antibodies on the differentiation of CD14+ monocytes from patients or healthy individuals. In vivo, Apoe-/- mice were fed a high-fat diet (HFD) for 20 weeks and administered injections of different CVI-IgG subclasses or Fc-engineered antibodies. Flow cytometry was used to assess the polarization of monocytes and macrophages. Although CVI-IgG4 reduced the release of MCP-1 compared to the other subtypes, IgG4 did not yield an anti-inflammatory effect by induction of human monocyte and macrophage differentiation in vitro. Furthermore, genetic polymorphisms of FcγRIIA were not associated with different CVI-IgG subclasses during the treatment of atherosclerosis. In vivo, CVI-IgG1 decreased Ly6Chigh monocyte differentiation and promoted M2 macrophage polarization. We also found that the secretion of IL-10 was upregulated in the CVI-IgG1-treated group, whereas V11 and GAALIE exerted no significant effect. These findings highlight that IgG1 is the optimal subtype for treating atherosclerosis, and CVI-IgG1 can induce monocyte/macrophage polarization. Overall, these results have important implications for the development of therapeutic antibodies.

Process development of a SARS-CoV-2 nanoparticle vaccine

One of the outcomes from the global COVID-19 pandemic caused by SARS-CoV-2 has been an acceleration of development timelines to provide treatments in a timely manner. For example, it has recently been demonstrated that the development of monoclonal antibody therapeutics from vector construction to IND submission can be achieved in five to six months rather than the traditional ten-to-twelve-month timeline using CHO cells [1,2]. This timeline is predicated on leveraging existing, robust platforms for upstream and downstream processes, analytical methods, and formulation. These platforms also reduce; the requirement for ancillary studies such as cell line stability, or long-term product stability studies. Timeline duration was further reduced by employing a transient cell line for early material supply and using a stable cell pool to manufacture toxicology study materials. The development of non-antibody biologics utilizing traditional biomanufacturing processes in CHO cells within a similar timeline presents additional challenges, such as the lack of platform processes and additional analytical assay development. In this manuscript, we describe the rapid development of a robust and reproducible process for a two-component self-assembling protein nanoparticle vaccine for SARS-CoV-2. Our work has demonstrated a successful academia-industry partnership model that responded to the COVID-19 global pandemic quickly and efficiently and could improve our preparedness for future pandemic threats.

Harnessing Fc/FcRn Affinity Data from Patents with Different Machine Learning Methods.

Monoclonal antibodies are biopharmaceuticals with a very long half-life due to the binding of their Fc portion to the neonatal receptor (FcRn), a pharmacokinetic property that can be further improved through engineering of the Fc portion, as demonstrated by the approval of several new drugs. Many Fc variants with increased binding to FcRn have been found using different methods, such as structure-guided design, random mutagenesis, or a combination of both, and are described in the literature as well as in patents. Our hypothesis is that this material could be subjected to a machine learning approach in order to generate new variants with similar properties. We therefore compiled 1323 Fc variants affecting the affinity for FcRn, which were disclosed in twenty patents. These data were used to train several algorithms, with two different models, in order to predict the affinity for FcRn of new randomly generated Fc variants. To determine which algorithm was the most robust, we first assessed the correlation between measured and predicted affinity in a 10-fold cross-validation test. We then generated variants by in silico random mutagenesis and compared the prediction made by the different algorithms. As a final validation, we produced variants, not described in any patents, and compared the predicted affinity with the experimental binding affinities measured by surface plasmon resonance (SPR). The best mean absolute error (MAE) between predicted and experimental values was obtained with a support vector regressor (SVR) using six features and trained on 1251 examples. With this setting, the error on the log(KD) was less than 0.17. The obtained results show that such an approach could be used to find new variants with better half-life properties that are different from those already extensively used in therapeutic antibody development.

Comparative Thermodynamics of the Reversible Self-Association of Therapeutic mAbs Reveal Opposing Roles for Linked Proton- and Ion-Binding Events.

Reversible self-association (RSA) has long been a concern in therapeutic monoclonal antibody (mAb) development. Because RSA typically occurs at high mAb concentrations, accurate assessment of the underlying interaction parameters requires explicitly addressing hydrodynamic and thermodynamic nonideality. We previously examined the thermodynamics of RSA for two mAbs, C and E, in phosphate buffered saline (PBS). Here we continue to explore the mechanistic aspects of RSA by examining the thermodynamics of both mAbs under reduced pH and salt conditions. Dynamic light scattering and sedimentation velocity (SV) studies were conducted for both mAbs at multiple protein concentrations and temperatures, with the SV data analyzed via global fitting to determine best-fit models, interaction energetics, and nonideality contributions. We find that mAb C self-associates isodesmically irrespective of temperature, and that association is enthalpically driven but entropically penalized. Conversely, mAb E self-associates cooperatively and via a monomer-dimer-tetramer-hexamer reaction pathway. Moreover, all mAb E reactions are entropically driven and enthalpically modest or minimal. The thermodynamics for mAb C self-association are classically seen as originating from van der Waals interactions and hydrogen bonding. However, relative to the energetics we determined in PBS, self-association must also be linked to proton release and/or ion uptake events. For mAb E, the thermodynamics implicate electrostatic interactions. Furthermore, self-association is instead linked to proton uptake and/or ion release, and primarily by tetramers and hexamers. Finally, although the origins of mAb E cooperativity remain unclear, ring formation remains a possibility whereas linear polymerization reactions can be eliminated.

Polyspecificity - An emerging trend in the development of clinical antibodies.

The essence of the growth and development of therapeutic conventional monoclonal antibodies (MAbs) for the treatment of various disorders is the aptitude of MAbs to precisely bind a target antigen and neutralise or promote its activity. However, the conventional antibodies are monoclonal i.e., both paratopes bind to the same epitope. But most of the pathophysiological conditions are multifaceted, hence targeting/blocking/inhibition of more than one epitope/antigen is more promising than one epitope/antigen. Polyspecific antibodies (PsAbs) have the potential to concurrently bind to more than one target and are the next-generation antibodies that augment efficacy in both clinical and non-clinical contexts. Thus, the trend of engineering and developing various formats of PsAbs is emerging. In this review, we have briefly discussed the importance of antibody polyspecificity and PsAbs approved for clinical use. Subsequently, we have discussed the role of TNF-α and IL-23 in inflammatory diseases and stressed the need for developing anti-TNF-α and anti-IL-23 bispecific antibodies.

Fibroblast, Epithelial and Endothelial Cell-Derived Human Cytomegalovirus Strains Display Distinct Neutralizing Antibody Responses and Varying Levels of gH/gL Complexes.

In sequential sera from pregnant women with HCMV primary infection (PI), the serum neutralizing activity is higher against virions produced in epithelial and endothelial cells than in fibroblasts. Immunoblotting shows that the pentamer complex/trimer complex (PC/TC) ratio varies according to the producer cell culture type used for the virus preparation to be employed in the neutralizing antibody (NAb) assay, and is lower in fibroblasts and higher in epithelial, and especially endothelial cells. The blocking activity of TC- and PC-specific inhibitors varies according to the PC/TC ratio of virus preparations. The rapid reversion of the virus phenotype following its back passage to the original cell culture (fibroblasts) potentially argues in favor of a producer cell effect on virus phenotype. However, the role of genetic factors cannot be overlooked. In addition to the producer cell type, the PC/TC ratio may differ in single HCMV strains. In conclusion, the NAb activity not only varies with different HCMV strains, but is a dynamic parameter changing according to virus strain, type of target and producer cells, and number of cell culture passages. These findings may have some important implications for the development of both therapeutic antibodies and subunit vaccines.

Two-Dimensional Capillary Zone Electrophoresis-Mass Spectrometry: Intact mAb Charge Variant Separation Followed by Peptide Level Analysis Using In-Capillary Digestion.

Characterization of charge heterogeneity is an essential pillar for pharmaceutical development and quality control of therapeutic monoclonal antibodies (mAbs). The highly selective and commonly applied capillary zone electrophoresis (CZE) method containing high amounts of ε-aminocaproic acid (EACA) provides a detailed and robust charge heterogeneity profile of intact mAb variants. Nevertheless, the exact location of protein modifications within these charge profiles remains ambiguous. Electrospray ionization mass spectrometry (ESI-MS) is a promising tool for this purpose; however, EACA is incompatible with electrospray. In this context, we present a two-dimensional CZE-CZE-MS system to combine efficient charge variant separation of intact mAbs with subsequent peptide analysis after in-capillary digestion of selected charge variants. The first dimension is based on a generic CZE(EACA) method in a fused silica capillary. In the second dimension, a neutral-coated capillary is used for in-capillary reduction and digestion with Tris(2-carboxyethyl)phosphine (TCEP) and pepsin, followed by CZE separation and MS/MS-characterization of the resulting peptides. The setup is demonstrated using stressed and nonstressed mAbs where peaks of basic, main, and acidic variants were transferred in a heart-cut fashion, digested, and characterized on the peptide level. Sequence coverages of more than 90% were obtained for heavy chain (HC) and light chain (LC) for four different mAbs, including low-abundance variants (<2% of the main peak). Frequently observed modifications (deamidation, oxidation, etc.) could be detected and localized. This study demonstrates a proof-of-concept for identification and localization of protein modifications from CZE charge heterogeneity profiles and, in this way, is expected to support the development and quality control testing of protein pharmaceuticals.

Antibody Fc-chimerism and effector functions: When IgG takes advantage of IgA.

Recent advances in the development of therapeutic antibodies (Abs) have greatly improved the treatment of otherwise drug-resistant cancers and autoimmune diseases. Antibody activities are mediated by both their Fab and the Fc. However, therapeutic Abs base their protective mechanisms on Fc-mediated effector functions resulting in the activation of innate immune cells by FcRs. Therefore, Fc-bioengineering has been widely used to maximise the efficacy and convenience of therapeutic antibodies. Today, IgG remains the only commercially available therapeutic Abs, at the expense of other isotypes. Indeed, production, sampling, analysis and related in vivo studies are easier to perform with IgG than with IgA due to well-developed tools. However, interest in IgA is growing, despite a shorter serum half-life and a more difficult sampling and purification methods than IgG. Indeed, the paradigm that the effector functions of IgG surpass those of IgA has been experimentally challenged. Firstly, IgA has been shown to bind to its Fc receptor (FcR) on effector cells of innate immunity with greater efficiency than IgG, resulting in more robust IgA-mediated effector functions in vitro and better survival of treated animals. In addition, the two isotypes have been shown to act synergistically. From these results, new therapeutic formats of Abs are currently emerging, in particular chimeric Abs containing two tandemly expressed Fc, one from IgG (Fcγ) and one from IgA (Fcα). By binding both FcγR and FcαR on effector cells, these new chimeras showed improved effector functions in vitro that were translated in vivo. Furthermore, these chimeras retain an IgG-like half-life in the blood, which could improve Ab-based therapies, including in AIDS. This review provides the rationale, based on the biology of IgA and IgG, for the development of Fcγ and Fcα chimeras as therapeutic Abs, offering promising opportunities for HIV-1 infected patients. We will first describe the main features of the IgA- and IgG-specific Fc-mediated signalling pathways and their respective functional differences. We will then summarise the very promising results on Fcγ and Fcα containing chimeras in cancer treatment. Finally, we will discuss the impact of Fcα-Fcγ chimerism in prevention/treatment strategies against infectious diseases such as HIV-1.

Structures of Cancer Antigen Mesothelin and Its Complexes with Therapeutic Antibodies.

The structures of full-length mesothelin and its complexes with antibodies reported here are the first to be determined experimentally, providing atomic models for structural organization of this protein and its interactions with antibodies. It offers insights into the function of mesothelin and guidance for further development of therapeutic antibodies.

Membrane binding is involved in the action of broadly neutralizing influenza antibodies.

Influenza poses a major health issue globally. Characterized by annual epidemics with mild to severe symptoms and even a significant number of deaths, the virus has historically resulted in substantial economic and societal problems in the world. Neutralizing antibodies that bind to the membrane-proximal region of hemagglutinin (HA) provide considerable protection against the infection by blocking the fusion of virus to the host cell. Here, using an array of advanced modeling and simulation techniques employed to a very large molecular assembly, for the first time, we develop a high-resolution structural model of full-length, antibody-bound HA in a native viral membrane and describe key molecular interactions that determine the binding affinity of the antibody to the viral membrane. The model allowed us to identify key residues in the antibody that interact with and bind to the membrane. Guided by the simulation predictions, the virus neutralization activity of the antibody was evaluated by mutagenesis experiments and infectivity assays. In alignment with the simulation results, the experiments show that mutating the predicted basic residues located away from the antigen binding site in the antibody decreases the neutralizing activity by up to an order of magnitude. Based on the results, we propose that the direct interaction of membrane-proximal antibodies with the viral membrane plays a role in their neutralizing activity against the virus. Introducing additional basic side chains enhancing phospholipid-binding is expected to further stabilize the HA-antibody. Given the rapid evolution of the influenza virus, the developed model provides a framework for rational design and development of more effective therapeutic antibodies.

Development of machine learning models for prediction of antibody non-specificity.

For the development of therapeutic antibodies, it is acknowledged that optimal target binding affinity should be accompanied by high specificity. In recent years, there has been an increased focus on lowering non-specific binding during early-stage drug development. In particular, non-specificity has been recognised as a root-cause for failure in numerous antibody-based drug programs due to unexpected pharmacokinetics and elevated toxicity. Hence, there is a need for predictive tools for flagging and deselecting non-specific antibodies at an early stage to mitigate failure at clinical late-stage development. From a computational design perspective, prediction has remained a challenge as non-specificity is currently a poorly understood biophysical phenomena, typically involving weak interactions to various, unrelated targets and surfaces. In this work, we describe the development of sequence-based machine learning (ML) models for prediction of antibody non-specificity. A dataset of >1000 antibody sequences paired with their respective non-specificity flag, defined by ELISA using a panel of common antigens, were retrieved from public sources (Jain et al., 2017; Boughter et al., 2020). The sequences were embedded using state-of-the-art protein language models for representation of their physiochemical properties, whereafter the vectorized embeddings were served as features for training of binary classifiers for non-specificity flags. A total of 12 different antibody domain-specific models were generated. Highest predictability of non-specificity was obtained for ML algorithms trained on the heavy-chain variable domain (VH), and the complementarity determining regions (CDRs), and resulted in a mean accuracy of 73% across 3-, 5-, and 10-fold cross-validations. The classification probability of non-specificity followed an uptrend with the experimental data (non-specificity flags), thereby mimicking regression behaviour. Altogether, our work demonstrates feasibility for prediction of non-specific binding from the antibody sequence, and that the non-specificity primarily stems from the VH domain, with main contributions from the heavy-chain CDRs.

Recombinant Soluble Henipavirus Glycoprotein Preparation.

Henipaviruses possess two envelope glycoproteins, the attachment (G) and the fusion (F) proteins that mediate cellular entry and are the major targets of virus-neutralizing antibody responses. Recombinant expression technologies have been used to produce soluble G and F proteins (sG and sF) that retain native-like oligomeric conformations and epitopes, which are advantageous for the development and characterization of vaccines and antiviral antibody therapeutics. In addition to Hendra virus and Nipah virus tetrameric sG and trimeric sF production, we also describe the expression and purification of Cedar virus tetrameric sG and Ghana virus trimeric sF glycoproteins. These henipavirus glycoproteins were also used as immunizing antigens to generate monoclonal antibodies, and binding was demonstrated with a pan-henipavirus multiplex microsphere immunoassay.

Development of therapeutic antibodies for the treatment of infection diseases and future aspect

Development of therapeutic antibodies for the treatment of infection diseases and future aspect

An anti-CD98 antibody displaying pH-dependent Fc-mediated tumour-specific activity against multiple cancers in CD98-humanized mice.

The cell-surface glycoprotein CD98-a subunit of the LAT1/CD98 amino acid transporter-is an attractive target for cancer immunotherapies, but its widespread expression has hampered the development of CD98-targeting antibody therapeutics. Here we report that an anti-CD98 antibody, identified via the screening of phage-display libraries of CD98 single-chain variable fragments with mutated complementarity-determining regions, preserves the physiological function of CD98 and elicits broad-spectrum crystallizable-fragment (Fc)-mediated anti-tumour activity (requiring Fcγ receptors for immunoglobulins, macrophages, dendritic cells and CD8+ T cells, as well as other components of the innate and adaptive immune systems) in multiple xenograft and syngeneic tumour models established in CD98-humanized mice. We also show that a variant of the anti-CD98 antibody with pH-dependent binding, generated by solving the structure of the antibody-CD98 complex, displayed enhanced tumour-specific activity and pharmacokinetics. pH-dependent antibody variants targeting widely expressed antigens may lead to superior therapeutic outcomes.

A high-throughput neutralizing assay for antibodies and sera evaluation against Epstein-Barr virus

BackgroundEpstein-Barr virus (EBV) is a wide-spread human herpesvirus that is highly associated with infectious mononucleosis and several malignancies. Evaluation of EBV neutralizing antibody titers is important for serological studies, vaccine development and monoclonal antibody screening. The traditional method based on antibody inhibition of EBV transformation of B cells is very time-consuming. A more practical flow cytometry-based (FCM) approach to evaluate neutralizing titers is not amenable to achieving high-throughput evaluation of large-scale samples. A high-throughput approach is urgently needed.ResultsHere, we present a rapid and high-throughput method based on high content imaging system (HCIS) analysis. EBV titers determined by the HCIS-based assay were similar to those obtained by the FCM-based assay. Neutralizing titers of sera and monoclonal antibodies measured by the HCIS-based assay strongly correlated with titers measured by the FCM-based assay. HCIS assays showed a strong correlation between B cell infection neutralizing titers and the anti-gp350 IgG titers in healthy EBV carriers and monkey sera. Finally, anti-gHgL IgG titers from sera of healthy EBV carriers significantly correlated with epithelial cell infection neutralizing titers.ConclusionsThis HCIS-based assay is a high-throughput assay to determine viral titers and evaluate neutralizing potentials of sera and monoclonal antibodies. This HCIS-based assay will aid the development of vaccines and therapeutic monoclonal antibody against EBV.

Therapeutic Antibodies in Cancer Treatment in the UK

The growing understanding of the molecular mechanisms of carcinogenesis accelerated the development of monoclonal therapeutic antibodies to specifically target multiple cancer pathways. Recombinant protein therapeutics now constitute a large proportion of yearly approved medicines. Oncology, autoimmune diseases and to a smaller degree the prophylaxis of organ transplant rejection are their main application areas. As of the date of this review, 37 monoclonal antibody products are approved for use in cancer treatments in the United Kingdom. Currently, the antibody therapeutics market is dominated by monoclonal immunoglobulins (IgGs). New types of recombinant antibody therapeutics developed more recently include bispecific recombinant antibodies and other recombinantly produced functional proteins. This review focuses on the approved therapeutic antibodies used in cancer treatment in the UK today and describes their antigen targets and molecular mechanisms involved. We provide convenient links to the relevant databases and other relevant resources for all antigens and antibodies mentioned. This review provides a comprehensive summary of the different monoclonal antibodies that are currently in clinical use primarily in malignancy, including their function, which is of importance to those in the medical field and allied specialties.

Non-specificity as the sticky problem in therapeutic antibody development.

Antibodies are highly potent therapeutic scaffolds with more than a hundreddifferent products approved on the market. Successful development of antibody-based drugs requires a trade-off between high target specificity and target binding affinity. In order to better understand this problem, we here review non-specific interactions and explore their fundamental physicochemical origins. We discuss the role of surface patches - clusters of surface-exposed amino acid residues with similar physicochemical properties - as inducers of non-specific interactions. These patches collectively drive interactions including dipole-dipole, π-stacking and hydrophobic interactions to complementary moieties. We elucidate links between these supramolecular assembly processes and macroscopic development issues, such as decreased physical stability and poor in vivo half-life. Finally, we highlight challenges and opportunities for optimizing protein binding specificity and minimizing non-specificity for future generations of therapeutics.

Paragraph-antibody paratope prediction using graph neural networks with minimal feature vectors.

The development of new vaccines and antibody therapeutics typically takes several years and requires over $1bn in investment. Accurate knowledge of the paratope (antibody binding site) can speed up and reduce the cost of this process by improving our understanding of antibody-antigen binding. We present Paragraph, a structure-based paratope prediction tool that outperforms current state-of-the-art tools using simpler feature vectors and no antigen information. Source code is freely available at www.github.com/oxpig/Paragraph. Supplementary data are available at Bioinformatics online.

A broadly protective human monoclonal antibody targeting the sialidase activity of influenza A and B virus neuraminidases

Improved vaccines and antiviral agents that provide better, broader protection against seasonal and emerging influenza viruses are needed. The viral surface glycoprotein hemagglutinin (HA) is a primary target for the development of universal influenza vaccines and therapeutic antibodies. The other major surface antigen, neuraminidase (NA), has been less well studied as a potential target and fewer broadly reactive anti-NA antibodies have been identified. In this study, we isolate three human monoclonal antibodies that recognize NA from A/H1N1 subtypes, and find that one of them, clone DA03E17, binds to the NA of A/H3N2, A/H5N1, A/H7N9, B/Ancestral-lineage, B/Yamagata-lineage, and B/Victoria-lineage viruses. DA03E17 inhibits the neuraminidase activity by direct binding to the enzyme active site, and provides in vitro and in vivo protection against infection with several types of influenza virus. This clone could, therefore, be useful as a broadly protective therapeutic agent. Moreover, the neutralizing epitope of DA03E17 could be useful in the development of an NA-based universal influenza vaccine.

Development of functional anti-Gn nanobodies specific for SFTSV based on next-generation sequencing and proteomics.

Severe fever with thrombocytopenia syndrome (SFTS) is an acute infectious disease caused by novel bunyavirus (SFTSV), with a mortality rate of 6.3% ~ 30%. To date, there is no specific treatment for SFTS. Previously, we demonstrated that SFTSV surface glycoprotein (Glycoprotein N, Gn) was a potential target for the development of SFTS vaccine or therapeutic antibodies, and anti-Gn neutralizing antibodies played a protective role in SFTS infection. Compared with traditional antibodies, nanobodies from camelids have various advantages, including small molecular weight, high affinity, low immunogenicity, convenient production by gene engineering, etc. In this study, we combined next-generation sequencing (NGS) with proteomics technology based on affinity purification-mass spectrometry (AP-MS) and bioinformatics analysis to high-throughput screen monoclonal anti-Gn nanobodies from camel immunized with Gn protein. We identified 19 anti-Gn monoclonal nanobody sequences, of which six sequences were selected for recombinant protein expression and purification. Among these six anti-Gn nanobodies, nanobody 57,493 was validated to be highly specific for Gn. The innovative high-throughput technical route developed in this study could also be expanded to the production of nanobodies specific for other viruses like SARS-CoV-2.