Improving the solubility of anti-LINGO-1 monoclonal antibody Li33 by isotype switching and targeted mutagenesis

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.

Optimization of therapeutic antibodies for reduced self-association and non-specific binding via interpretable machine learning

Antibody development, delivery, and efficacy are influenced by antibody-antigen affinity interactions, off-target interactions that reduce antibody bioavailability and pharmacokinetics, and repulsive self-interactions that increase the stability of concentrated antibody formulations and reduce their corresponding viscosity. Yet identifying antibody variants with optimal combinations of these three types of interactions is challenging. Here we show that interpretable machine-learning classifiers, leveraging antibody structural features descriptive of their variable regions and trained on experimental data for a panel of 80 clinical-stage monoclonal antibodies, can identify antibodies with optimal combinations of low off-target binding in a common physiological-solution condition and low self-association in a common antibody-formulation condition. For three clinical-stage antibodies with suboptimal combinations of off-target binding and self-association, the classifiers predicted variable-region mutations that optimized non-affinity interactions while maintaining high-affinity antibody-antigen interactions. Interpretable machine-learning models may facilitate the optimization of antibody candidates for therapeutic applications.

Tau-targeting therapies for Alzheimer disease: current status and future directions

Alzheimer disease (AD) is the most common cause of dementia in older individuals. AD is characterized pathologically by amyloid-β (Aβ) plaques and tau neurofibrillary tangles in the brain, with associated loss of synapses and neurons, which eventually results in dementia. Many of the early attempts to develop treatments for AD focused on Aβ, but a lack of efficacy of these treatments in terms of slowing disease progression led to a change of strategy towards targeting of tau pathology. Given that tau shows a stronger correlation with symptom severity than does Aβ, targeting of tau is more likely to be efficacious once cognitive decline begins. Anti-tau therapies initially focused on post-translational modifications, inhibition of tau aggregation and stabilization of microtubules. However, trials of many potential drugs were discontinued because of toxicity and/or lack of efficacy. Currently, the majority of tau-targeting agents in clinical trials are immunotherapies. In this Review, we provide an update on the results from the initial immunotherapy trials and an overview of new therapeutic candidates that are in clinical development, as well as considering future directions for tau-targeting therapies.

Native SEC and Reversed-Phase LC-MS Reveal Impact of Fab Glycosylation of Anti-SARS-COV-2 Antibodies on Binding to the Receptor Binding Domain

The binding affinity of monoclonal antibodies (mAbs) for their intended therapeutic targets is often affected by chemical and post-translational modifications in the antigen binding (Fab) domains. A new two-dimensional analytical approach is described here utilizing native size exclusion chromatography (SEC) to separate populations of antibodies and bound antibody-antigen complexes for subsequent characterization of these modifications by reversed-phase (RP) liquid chromatography-mass spectrometry (LC-MS) at the intact antibody level. Previously, we utilized peptide mapping to measure modifications impacting binding. However, in this study, the large size of the modification (N-glycosylation) allowed assessing its impact from small amounts (∼20 ug) of intact antibody, without the need for peptide mapping. Here, we apply the native SEC-based competitive binding assay to quickly and qualitatively investigate the effects of Fab glycosylation of four antispike protein mAbs that were developed for use in the treatment of COVID-19 disease. Three of the mAbs were observed to have consensus N-glycosylation sites (N-X-T/S) in the Fab domains, a relatively rare occurrence in therapeutic mAbs. The goal of the study was to characterize the levels of Fab glycosylation present, as well as determine the impact of glycosylation on binding to the spike protein receptor binding domain (RBD) and the ability of the mAbs to inhibit RBD-ACE2 interaction at the intact antibody level, with minimal sample treatment and preparation. The three mAbs with Fab N-glycans were found to have glycosylation profiles ranging from full occupancy at each Fab (in one mAb) to partially glycosylated with mixed populations of two, one, or no glycan moieties. Competitive SEC analysis of mAb-RBD revealed that the glycosylated antibody populations outcompete their nonglycosylated counterparts for the available RBD molecules. This competitive SEC binding analysis was applied to investigate the three-body interaction of a glycosylated mAb blocking the interaction between endogenous binding partners RBD-ACE2, finding that both glycosylated and nonglycosylated mAb populations bound to RBD with high enough affinity to block RBD-ACE2 binding.

Aerosolization Performance of Immunoglobulin G by Jet and Mesh Nebulizers

Recently, many preclinical and clinical studies have been conducted on the delivery of therapeutic antibodies to the lungs using nebulizers, but standard treatment guidelines have not yet been established. Our objective was to compare nebulization performance according to the low temperature and concentration of immunoglobulin G (IgG) solutions in different types of nebulizers, and to evaluate the stability of IgG aerosols and the amount delivered to the lungs. The output rate of the mesh nebulizers decreased according to the low temperature and high concentration of IgG solution, whereas the jet nebulizer was unaffected by the temperature and concentration of IgG. An impedance change of the piezoelectric vibrating element in the mesh nebulizers was observed because of the lower temperature and higher viscosity of IgG solution. This affected the resonance frequency of the piezoelectric element and lowered the output rate of the mesh nebulizers. Aggregation assays using a fluorescent probe revealed aggregates in IgG aerosols from all nebulizers. The delivered dose of IgG to the lungs in mice was highest at 95 ng/mL in the jet nebulizer with the smallest droplet size. Evaluation of the performance of IgG solution delivered to the lungs by three types of nebulizers could provide valuable parameter information for determination on dose of therapeutic antibody by nebulizers.

Blueprint for antibody biologics developability

Large-molecule antibody biologics have revolutionized medicine owing to their superior target specificity, pharmacokinetic and pharmacodynamic properties, safety and toxicity profiles, and amenability to versatile engineering. In this review, we focus on preclinical antibody developability, including its definition, scope, and key activities from hit to lead optimization and selection. This includes generation, computational and in silico approaches, molecular engineering, production, analytical and biophysical characterization, stability and forced degradation studies, and process and formulation assessments. More recently, it is apparent these activities not only affect lead selection and manufacturability, but ultimately correlate with clinical progression and success. Emerging developability workflows and strategies are explored as part of a blueprint for developability success that includes an overview of the four major molecular properties that affect all developability outcomes: 1) conformational, 2) chemical, 3) colloidal, and 4) other interactions. We also examine risk assessment and mitigation strategies that increase the likelihood of success for moving the right candidate into the clinic.

Non-specificity as the sticky problem in therapeutic antibody development

Antibodies are highly potent therapeutic scaffolds with more than a hundred different 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.

Protein Design: From the Aspect of Water Solubility and Stability

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space

Therapeutic antibody development requires selection and engineering of molecules with high affinity and other drug-like biophysical properties. Co-optimization of multiple antibody properties remains a difficult and time-consuming process that impedes drug development. Here we evaluate the use of machine learning to simplify antibody co-optimization for a clinical-stage antibody (emibetuzumab) that displays high levels of both on-target (antigen) and off-target (non-specific) binding. We mutate sites in the antibody complementarity-determining regions, sort the antibody libraries for high and low levels of affinity and non-specific binding, and deep sequence the enriched libraries. Interestingly, machine learning models trained on datasets with binary labels enable predictions of continuous metrics that are strongly correlated with antibody affinity and non-specific binding. These models illustrate strong tradeoffs between these two properties, as increases in affinity along the co-optimal (Pareto) frontier require progressive reductions in specificity. Notably, models trained with deep learning features enable prediction of novel antibody mutations that co-optimize affinity and specificity beyond what is possible for the original antibody library. These findings demonstrate the power of machine learning models to greatly expand the exploration of novel antibody sequence space and accelerate the development of highly potent, drug-like antibodies.

Effect of the ADCC-modulating mutations and the selection of human IgG isotypes on physicochemical properties of Fc

Monoclonal antibodies, particularly IgGs and Ig-based molecules, are a well-established and growing class of biotherapeutic drugs. In order to improve efficacy, potency and pharmacokinetics of these therapeutic drugs, pharmaceutical industries have investigated significantly in engineering fragment crystallizable (Fc) domain of these drugs to optimize the interactions of these drugs and Fc gamma receptors (FcγRs) in recent ten years. The biological function of the therapeutics with the antibody-dependent cellular cytotoxicity (ADCC) enhanced double mutation (S239D/I332E) of isotype IgG1, the ADCC reduced double mutation (L234A/L235A) of isotype IgG1, and ADCC reduced isotype IgG4 has been well understood. However, limited information regarding the effect of these mutations or isotype difference on physicochemical properties (PCP), developability, and manufacturability of therapeutics bearing these different Fc regions is available. In this report, we systematically characterize the effects of the mutations and IgG4 isotype on conformation stability, colloidal stability, solubility, and storage stability at accelerated conditions in two buffer systems using six Fc variants. Our results provide a basis for selecting appropriate Fc region during development of IgG or Ig-based therapeutics and predicting effect of the mutations on CMC development process.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

New Opportunities in Glycan Engineering for Therapeutic Proteins

Glycans as sugar polymers are important metabolic, structural, and physiological regulators for cellular and biological functions. They are often classified as critical quality attributes to antibodies and recombinant fusion proteins, given their impacts on the efficacy and safety of biologics drugs. Recent reports on the conjugates of N-acetyl-galactosamine and mannose-6-phosphate for lysosomal degradation, Fab glycans for antibody diversification, as well as sialylation therapeutic modulations and O-linked applications, have been fueling the continued interest in glycoengineering. The current advancements of the human glycome and the development of a comprehensive network in glycosylation pathways have presented new opportunities in designing next-generation therapeutic proteins.

Simultaneous affinity maturation and developability enhancement using natural liability-free CDRs

Affinity maturation is often a necessary step for the development of potent therapeutic molecules. Many different diversification strategies have been used for antibody affinity maturation, including error-prone PCR, chain shuffling, and targeted complementary-determining region (CDR) mutation. Although effective, they can negatively impact antibody stability or alter epitope recognition. Moreover, they do not address the presence of sequence liabilities, such as glycosylation, asparagine deamidation, aspartate isomerization, aggregation motifs, and others. Such liabilities, if present or inadvertently introduced, can potentially create the need for new rounds of engineering, or even abolish the value of the antibody as a therapeutic molecule. Here, we demonstrate a sequence agnostic method to improve antibody affinities, while simultaneously eliminating sequence liabilities and retaining the same epitope binding as the parental antibody. This was carried out using a defined collection of natural CDRs as the diversity source, purged of sequence liabilities, and matched to the antibody germline gene family. These CDRs were inserted into the lead molecule in one or two sites at a time (LCDR1-2, LCDR3, HCDR1-2) while retaining the HCDR3 and framework regions unchanged. The final analysis of 92 clones revealed 81 unique variants, with each of 24 tested variants having the same epitope specificity as the parental molecule. Of these, the average affinity improved by over 100 times (to 96 pM), and the best affinity improvement was 231-fold (to 32 pM).

Targeting tau only extracellularly is likely to be less efficacious than targeting it both intra- and extracellularly

Aggregation of the tau protein is thought to be responsible for the neurodegeneration and subsequent functional impairments in diseases that are collectively named tauopathies. Alzheimer's disease is the most common tauopathy, but the group consists of over 20 different diseases, many of which have tau pathology as their primary feature. The development of tau therapies has mainly focused on preventing the formation of and/or clearing these aggregates. Of these, immunotherapies that aim to either elicit endogenous tau antibodies or deliver exogenous ones are the most common approach in clinical trials. While their mechanism of action can involve several pathways, both extra- and intracellular, pharmaceutical companies have primarily focused on antibody-mediated clearance of extracellular tau. As we have pointed out over the years, this is rather surprising because it is well known that most of pathological tau protein is found intracellularly. It has been repeatedly shown by several groups over the past decades that antibodies can enter neurons and that their cellular uptake can be enhanced by various means, particularly by altering their charge. Here, we will briefly describe the potential extra- and intracellular mechanisms involved in antibody-mediated clearance of tau pathology, discuss these in the context of recent failures of some of the tau antibody trials, and finally provide a brief overview of how the intracellular efficacy of tau antibodies can potentially be further improved by certain modifications that aim to enhance tau clearance via specific intracellular degradation pathways.

Impact of IgG subclass on molecular properties of monoclonal antibodies

Immunoglobulin G-based monoclonal antibodies (mAbs) have become a dominant class of biotherapeutics in recent decades. Approved antibodies are mainly of the subclasses IgG1, IgG2, and IgG4, as well as their derivatives. Over the decades, the selection of IgG subclass has frequently been based on the needs of Fc gamma receptor engagement and effector functions for the desired mechanism of action, while the effect on drug product developability has been less thoroughly characterized. One of the major reasons is the lack of systematic understanding of the impact of IgG subclass on the molecular properties. Several efforts have been made recently to compare molecular property differences among these IgG subclasses, but the conclusions from these studies are sometimes obscured by the interference from variable regions. To further establish mechanistic understandings, we conducted a systematic study by grafting three independent variable regions onto human IgG1, an IgG1 variant, IgG2, and an IgG4 variant constant domains and evaluating the impact of subclass and variable regions on their molecular properties. Structural and computational analysis revealed specific molecular features that potentially account for the differential behavior of the IgG subclasses observed experimentally. Our data indicate that IgG subclass plays a significant role on molecular properties, either through direct effects or via the interplay with the variable region, the IgG1 mAbs tend to have higher solubility than either IgG2 or IgG4 mAbs in a common pH 6 buffer matrix, and solution behavior relies heavily on the charge status of the antibody at the desirable pH.

Glycan Profile Analysis of Engineered Trastuzumab with Rationally Added Glycosylation Sequons Presents Significantly Increased Glycan Complexity

Protein aggregation constitutes a recurring complication in the manufacture and clinical use of therapeutic monoclonal antibodies (mAb) and mAb derivatives. Antibody aggregates can reduce production yield, cause immunogenic reactions, decrease the shelf-life of the pharmaceutical product and impair the capacity of the antibody monomer to bind to its cognate antigen. A common strategy to tackle protein aggregation involves the identification of surface-exposed aggregation-prone regions (APR) for replacement through protein engineering. It was shown that the insertion of N-glycosylation sequons on amino acids proximal to an aggregation-prone region can increase the physical stability of the protein by shielding the APR, thus preventing self-association of antibody monomers. We recently implemented this approach in the Fab region of full-size adalimumab and demonstrated that the thermodynamic stability of the Fab domain increases upon N-glycosite addition. Previous experimental data reported for this technique have lacked appropriate confirmation of glycan occupancy and structural characterization of the ensuing glycan profile. Herein, we mutated previously identified candidate positions on the Fab domain of Trastuzumab and employed tandem mass spectrometry to confirm attachment and obtain a detailed N-glycosylation profile of the mutants. The Trastuzumab glycomutants displayed a glycan profile with significantly higher structural heterogeneity compared to the HEK Trastuzumab antibody, which contains a single N-glycosylation site per heavy chain located in the CH2 domain of the Fc region. These findings suggest that Fab N-glycosites have higher accessibility to enzymes responsible for glycan maturation. Further, we have studied effects on additional glycosylation on protein stability via accelerated studies by following protein folding and aggregation propensities and observed that additional glycosylation indeed enhances physical stability and prevent protein aggregation. Our findings shed light into mAb glycobiology and potential implications in the application of this technique for the development of “biobetter” antibodies.

Glycosylation decreases aggregation and immunogenicity of adalimumab Fab secreted from Pichia pastoris

Glycoengineering of therapeutic proteins has been applied to improve the clinical efficacy of several therapeutics. Here, we examined the effect of glycosylation on the properties of the Fab of the therapeutic antibody, adalimumab. An N-glycosylation site was introduced at position 178 of the H chain constant region of adalimumab Fab through site-directed mutagenesis (H:L178N Fab), and the H:L178N Fab was produced in Pichia pastoris. Expressed mutant Fab contained long and short glycan chains (L-glyco Fab and S-glyco Fab, respectively). Under the condition of aggregation of Fab upon pH shift-induced stress, both of L-glyco Fab and S-glyco Fab were less prone to aggregation, with L-glyco Fab suppressing aggregation more effectively than the S-glyco Fab. Moreover, the comparison of the antigenicity of glycosylated and wild-type Fabs in mice revealed that glycosylation resulted in the suppression of antigenicity. Analysis of the pharmacokinetic behaviour of the Fab, L-glyco Fab and S-glyco Fab indicated that the half-lives of glycosylated Fabs in the rats were shorter than that of wild-type Fab, with L-glyco Fab having a shorter half-life than S-glyco Fab. Thus, we demonstrated that the glycan chain influences Fab aggregation and immunogenicity, and glycosylation reduces the elimination half-life in vivo.

Effective rational humanization of a PASylated anti-galectin-3 Fab for the sensitive PET imaging of thyroid cancer in vivo

The lack of a non-invasive test for malignant thyroid nodules makes the diagnosis of thyroid cancer (TC) challenging. Human galectin-3 (hGal3) has emerged as a promising target for medical TC imaging and diagnosis because of its exclusive overexpression in malignant thyroid tissues. We previously developed a human-chimeric αhGal3 Fab fragment derived from the rat monoclonal antibody (mAb) M3/38 with optimized clearance characteristics using PASylation technology. Here, we describe the elucidation of the hGal3 epitope recognized by mAb M3/38, X-ray crystallographic analysis of its complex with the chimeric Fab and, based on the three-dimensional structure, the rational humanization of the Fab by CDR grafting. Four CDR-grafted versions were designed using structurally most closely related fully human immunoglobulin VH/VL regions of which one-employing the acceptor framework regions of the HIV-1 neutralizing human antibody m66-showed the highest antigen affinity. By introducing two additional back-mutations to the rodent donor sequence, an affinity toward hGal3 indistinguishable from the chimeric Fab was achieved (KD = 0.34 ± 0.02 nM in SPR). The PASylated humanized Fab was site-specifically labelled with the fluorescent dye Cy7 and applied for the immuno-histochemical staining of human tissue sections representative for different TCs. The same protein was conjugated with the metal chelator Dfo, followed by radiolabelling with 89Zr(IV). The resulting protein tracer allowed the highly sensitive and specific PET/CT imaging of orthotopic tumors in mice, which was confirmed by quantitative analysis of radiotracer accumulation. Thus, the PASylated humanized αhGal3 Fab offers clinical potential for the diagnostic imaging of TC.

Quantifying misfolded protein oligomers as drug targets and biomarkers in Alzheimer and Parkinson diseases

Protein misfolding and aggregation are characteristic of a wide range of neurodegenerative disorders, including Alzheimer and Parkinson diseases. A hallmark of these diseases is the aggregation of otherwise soluble and functional proteins into amyloid aggregates. Although for many decades such amyloid deposits have been thought to be responsible for disease progression, it is now increasingly recognized that the misfolded protein oligomers formed during aggregation are, instead, the main agents causing pathological processes. These oligomers are transient and heterogeneous, which makes it difficult to detect and quantify them, generating confusion about their exact role in disease. The lack of suitable methods to address these challenges has hampered efforts to investigate the molecular mechanisms of oligomer toxicity and to develop oligomer-based diagnostic and therapeutic tools to combat protein misfolding diseases. In this Review, we describe methods to quantify misfolded protein oligomers, with particular emphasis on diagnostic applications as disease biomarkers and on therapeutic applications as target biomarkers. The development of these methods is ongoing, and we discuss the challenges that remain to be addressed to establish measurement tools capable of overcoming existing limitations and to meet present needs.

Drug-like antibodies with high affinity, diversity and developability directly from next-generation antibody libraries

Therapeutic antibodies must have "drug-like" properties. These include high affinity and specificity for the intended target, biological activity, and additional characteristics now known as "developability properties": long-term stability and resistance to aggregation when in solution, thermodynamic stability to prevent unfolding, high expression yields to facilitate manufacturing, low self-interaction, among others. Sequence-based liabilities may affect one or more of these characteristics. Improving the stability and developability of a lead antibody is typically achieved by modifying its sequence, a time-consuming process that often results in reduced affinity. Here we present a new antibody library format that yields high-affinity binders with drug-like developability properties directly from initial selections, reducing the need for further engineering or affinity maturation. The innovative semi-synthetic design involves grafting natural complementarity-determining regions (CDRs) from human antibodies into scaffolds based on well-behaved clinical antibodies. HCDR3s were amplified directly from B cells, while the remaining CDRs, from which all sequence liabilities had been purged, were replicated from a large next-generation sequencing dataset. By combining two in vitro display techniques, phage and yeast display, we were able to routinely recover a large number of unique, highly developable antibodies against clinically relevant targets with affinities in the subnanomolar to low nanomolar range. We anticipate that the designs and approaches presented here will accelerate the drug development process by reducing the failure rate of leads due to poor antibody affinities and developability.Abbreviations: AC-SINS: affinity-capture self-interaction nanoparticle spectroscopy; CDR: complementarity-determining region; CQA: critical quality attribute; ELISA: enzyme-linked immunoassay; FACS: fluorescence-activated cell sorting; Fv: fragment variable; GM-CSF: granulocyte-macrophage colony-stimulating factor; HCDR3: heavy chain CDR3; IFN2a: interferon α-2; IL6: interleukin-6; MACS: magnetic-activated cell sorting; NGS: next generation sequencing; PCR: polymerase chain reaction; SEC: size-exclusion chromatography; SPR: surface plasmon resonance; TGFβ-R2: transforming growth factor β-R2; VH: variable heavy; VK: variable kappa; VL: variable light; Vl: variable lambda.

First-order nucleation and subsequent growth promote liquid-liquid phase separation of a model IgG1 mAb

Although protein aggregation is commonly encountered during the manufacturing and storage of bio-therapeutics, the actual aggregation mechanism remains unclear, and little has been reported about the protein aggregation kinetics from time zero under particular solution conditions. In this study, we used real-time dynamic light scattering (DLS) to continuously monitor the time-dependent evolution of the Z-average hydrodynamic radius of a model IgG1 (JM2) immediately after the JM2 solution was subjected to various low temperatures (0-4 °C). We observed that JM2 aggregated to form nuclei first, and then it subsequently grew to small liquid droplets via a two-step, first-order, reversible process without causing irreversible structural changes: a slow first step defined as the "nucleation" step, wherein nuclei formed slowly until reaching a transitional time point (t_onset), and a much faster second step initiated after t_onset and the nucleus size of the protein increased rapidly, which eventually caused liquid droplet formation and liquid-liquid phase separation (LLPS). The "nucleation" rate constant (K_nucleation) and particle growth rate constant (K_growth), as well as t_onset, were found to be temperature, pH and concentration dependent. The aggregation of JM2 could be universally described by these two-step first-order kinetics: under conditions where JM2 aggregated very slowly, the second step was not observed within the experimental time scale, while under conditions where JM2 aggregated very rapidly, the first step could not be recorded. We believe that these three parameters, K_nucleation, K_growth, and t_onset, can be used to quantify and compare the aggregation kinetics of JM2 under different solution and temperature conditions and, furthermore, serve as a theoretical base to account for the key characteristics of the aggregation kinetics of JM2 and other protein therapeutics under conditions of interest.

Electrostatic interactions modulate the differential aggregation propensities of IgG1 and IgG4P antibodies and inform charged residue substitutions for improved developability

Native state aggregation is an important concern in the development of therapeutic antibodies. Enhanced knowledge of mAb native state aggregation mechanisms would permit sequence-based selection and design of therapeutic mAbs with improved developability. We investigated how electrostatic interactions affect the native state aggregation of seven human IgG1 and IgG4P mAb isotype pairs, each pair having identical variable domains that are different for each set of IgG1 and IgG4P constructs. Relative aggregation propensities were determined at pH 7.4, representing physiological conditions, and pH 5.0, representing commonly used storage conditions. Our work indicates that the net charge state of variable domains relative to the net charge state of the constant domains is predominantly responsible for the different native state aggregation behavior of IgG1 and IgG4P mAbs. This observation suggests that the global net charge of a multi domain protein is not a reliable predictor of aggregation propensity. Furthermore, we demonstrate a design strategy in the frameworks of variable domains to reduce the native state aggregation propensity of mAbs identified as being aggregation-prone. Importantly, substitution of specifically identified residues with alternative, human germline residues, to optimize Fv charge, resulted in decreased aggregation potential at pH 5.0 and 7.4, thus increasing developability.

Physicochemical Rules for Identifying Monoclonal Antibodies with Drug-like Specificity

The ability of antibodies to recognize their target antigens with high specificity is fundamental to their natural function. Nevertheless, therapeutic antibodies display variable and difficult-to-predict levels of nonspecific and self-interactions that can lead to various drug development challenges, including antibody aggregation, abnormally high viscosity, and rapid antibody clearance. Here we report a method for predicting the overall specificity of antibodies in terms of their relative risk for displaying high levels of nonspecific or self-interactions at physiological conditions. We find that individual and combined sets of chemical rules that limit the maximum and minimum numbers of certain solvent-exposed amino acids in antibody variable regions are strong predictors of specificity for large panels of preclinical and clinical-stage antibodies. We also demonstrate how the chemical rules can be used to identify sites that mediate nonspecific interactions in suboptimal antibodies and guide the design of targeted sublibraries that yield variants with high antibody specificity. These findings can be readily used to improve the selection and engineering of antibodies with drug-like specificity.

Expression vector cassette engineering for recombinant therapeutic production in mammalian cell systems

Human tissue plasminogen activator was the first recombinant therapy protein that successfully produced in Chinese hamster ovary cells in 1986 and approved for clinical use. Since then, more and more therapeutic proteins are being manufactured in mammalian cells, and the technologies for recombinant protein production in this expression system have developed rapidly, with the optimization of both upstream and downstream processes. One of the most promising strategies is expression vector cassette optimization based on the expression vector cassette. In this review paper, these approaches and developments are summarized, and the future strategy on the utilizing of expression cassettes for the production of recombinant therapeutic proteins in mammalian cells is discussed.

Enhancing the stability of adalimumab by engineering additional glycosylation motifs

Monoclonal antibodies (mAbs) are of high value in the diagnostic and treatment of many debilitating diseases such as cancers, auto-immune disorders and infections. Unfortunately, protein aggregation is one of the ongoing challenges, limiting the development and application of mAbs as therapeutic products by decreasing half-life, increasing immunogenicity and reducing activity. We engineered an aggregation-prone region of adalimumab, the top selling mAb product worldwide - with additional glycosylation sites to enhance its resistance to aggregation by steric hindrance as a next generation biologic. We found that the addition of N-glycans in the Fab domain significantly enhanced its conformational stability, with some variants increasing the melting temperature of the Fab domain by >6 °C. The mutations tested had minimal impact on antigen binding affinity, or affinity to Fcγ receptors responsible for effector function. Our findings highlight the significant utility of this rational engineering approach for enhancing the conformational stability of therapeutic mAbs and other next-generation antibody formats.

An in vivo platform to select and evolve aggregation-resistant proteins

Protein biopharmaceuticals are highly successful, but their utility is compromised by their propensity to aggregate during manufacture and storage. As aggregation can be triggered by non-native states, whose population is not necessarily related to thermodynamic stability, prediction of poorly-behaving biologics is difficult, and searching for sequences with desired properties is labour-intensive and time-consuming. Here we show that an assay in the periplasm of E. coli linking aggregation directly to antibiotic resistance acts as a sensor for the innate (un-accelerated) aggregation of antibody fragments. Using this assay as a directed evolution screen, we demonstrate the generation of aggregation resistant scFv sequences when reformatted as IgGs. This powerful tool can thus screen and evolve ‘manufacturable’ biopharmaceuticals early in industrial development. By comparing the mutational profiles of three different immunoglobulin scaffolds, we show the applicability of this method to investigate protein aggregation mechanisms important to both industrial manufacture and amyloid disease.

Protein aggregation remains a significant challenge for manufacturing of protein biopharmaceuticals. Here, the authors demonstrate the use of directed evolution and an assay for in vivo innate protein aggregation-propensity to generate aggregation-resistant scFv fragments.

Binding symmetry and surface flexibility mediate antibody self-association

Solution stability is an important factor in the optimization of engineered biotherapeutic candidates such as monoclonal antibodies because of its possible effects on manufacturability, pharmacology, efficacy and safety. A detailed atomic understanding of the mechanisms governing self-association of natively folded protein monomers is required to devise predictive tools to guide screening and re-engineering along the drug development pipeline. We investigated pairs of affinity-matured full-size antibodies and observed drastically different propensities to aggregate from variants differing by a single amino-acid. Biophysical testing showed that antigen-binding fragments (Fabs) from the aggregating antibodies also reversibly associated with equilibrium dissociation constants in the low-micromolar range. Crystal structures (PDB accession codes 6MXR, 6MXS, 6MY4, 6MY5) and bottom-up hydrogen-exchange mass spectrometry revealed that Fab self-association occurs in a symmetric mode that involves the antigen complementarity-determining regions. Subtle local conformational changes incurred upon point mutation of monomeric variants foster formation of complementary polar interactions and hydrophobic contacts to generate a dimeric Fab interface. Testing of popular in silico tools generally indicated low reliabilities for predicting the aggregation propensities observed. A structure-aggregation data set is provided here in order to stimulate further improvements of in silico tools for prediction of native aggregation. Incorporation of intermolecular docking, conformational flexibility, and short-range packing interactions may all be necessary features of the ideal algorithm.

The solution structure of the human IgG2 subclass is distinct from those for human IgG1 and IgG4 providing an explanation for their discrete functions

Human IgG2 antibody displays distinct therapeutically-useful properties compared with the IgG1, IgG3, and IgG4 antibody subclasses. IgG2 is the second most abundant IgG subclass, being able to bind human FcγRII/FcγRIII but not to FcγRI or complement C1q. Structural information on IgG2 is limited by the absence of a full-length crystal structure for this. To this end, we determined the solution structure of human myeloma IgG2 by atomistic X-ray and neutron-scattering modeling. Analytical ultracentrifugation disclosed that IgG2 is monomeric with a sedimentation coefficient (s20, w0) of 7.2 S. IgG2 dimer formation was ≤5% and independent of the buffer conditions. Small-angle X-ray scattering in a range of NaCl concentrations and in light and heavy water revealed that the X-ray radius of gyration (Rg ) is 5.2-5.4 nm, after allowing for radiation damage at higher concentrations, and that the neutron Rg value of 5.0 nm remained unchanged in all conditions. The X-ray and neutron distance distribution curves (P(r)) revealed two peaks, M1 and M2, that were unchanged in different buffers. The creation of >123,000 physically-realistic atomistic models by Monte Carlo simulations for joint X-ray and neutron-scattering curve fits, constrained by the requirement of correct disulfide bridges in the hinge, resulted in the determination of symmetric Y-shaped IgG2 structures. These molecular structures were distinct from those for asymmetric IgG1 and asymmetric and symmetric IgG4 and were attributable to the four hinge disulfides. Our IgG2 structures rationalize the existence of the human IgG1, IgG2, and IgG4 subclasses and explain the receptor-binding functions of IgG2.

Current Advancements in Addressing Key Challenges of Therapeutic Antibody Design, Manufacture, and Formulation

Therapeutic antibody technology heavily dominates the biologics market and continues to present as a significant industrial interest in developing novel and improved antibody treatment strategies. Many noteworthy advancements in the last decades have propelled the success of antibody development; however, there are still opportunities for improvement. In considering such interest to develop antibody therapies, this review summarizes the array of challenges and considerations faced in the design, manufacture, and formulation of therapeutic antibodies, such as stability, bioavailability and immunological engagement. We discuss the advancement of technologies that address these challenges, highlighting key antibody engineered formats that have been adapted. Furthermore, we examine the implication of novel formulation technologies such as nanocarrier delivery systems for the potential to formulate for pulmonary delivery. Finally, we comprehensively discuss developments in computational approaches for the strategic design of antibodies with modulated functions.

Process optimization and protein engineering mitigated manufacturing challenges of a monoclonal antibody with liquid-liquid phase separation issue by disrupting inter-molecule electrostatic interactions

We report a case study in which liquid-liquid phase separation (LLPS) negatively impacted the downstream manufacturability of a therapeutic mAb. Process parameter optimization partially mitigated the LLPS, but limitations remained for large-scale manufacturing. Electrostatic interaction driven self-associations and the resulting formation of high-order complexes are established critical properties that led to LLPS. Through chain swapping substitutions with a well-behaved antibody and subsequent study of their solution behaviors, we found the self-association interactions between the light chains (L_Cs) of this mAb are responsible for the LLPS behavior. With the aid of in silico homology modeling and charged-patch analysis, seven charged residues in the L_C complementarity-determining regions (CDRs) were selected for mutagenesis, then evaluated for self-association and LLPS properties. Two charged residues in the light chain (K30 and D50) were identified as the most significant to the LLPS behaviors and to the antigen-binding affinity. Four adjacent charged residues in the light chain (E49, K52, R53, and R92) also contributed to self-association, and thus to LLPS. Molecular engineering substitution of these charged residues with a neutral or oppositely-charged residue disrupted the electrostatic interactions. A double-mutation in CDR2 and CDR3 resulted in a variant that retained antigen-binding affinity and eliminated LLPS. This study demonstrates the critical nature of surface charged resides on LLPS, and highlights the applied power of in silico protein design when applied to improving physiochemical characteristics of therapeutic antibodies. Our study indicates that in silico design and effective protein engineering may be useful in the development of mAbs that encounter similar LLPS issues.

Understanding and overcoming trade-offs between antibody affinity, specificity, stability and solubility

The widespread use of monoclonal antibodies for therapeutic applications has led to intense interest in optimizing several of their natural properties (affinity, specificity, stability, solubility and effector functions) as well as introducing non-natural activities (bispecificity and cytotoxicity mediated by conjugated drugs). A common challenge during antibody optimization is that improvements in one property (e.g., affinity) can lead to deficits in other properties (e.g., stability). Here we review recent advances in understanding trade-offs between different antibody properties, including affinity, specificity, stability and solubility. We also review new approaches for co-optimizing multiple antibody properties and discuss how these methods can be used to rapidly and systematically generate antibodies for a wide range of applications.

Variable Domain N-Linked Glycans Acquired During Antigen-Specific Immune Responses Can Contribute to Immunoglobulin G Antibody Stability

Immunoglobulin G (IgG) can contain N-linked glycans in the variable domains, the so-called Fab glycans, in addition to the Fc glycans in the C_H2 domains. These Fab glycans are acquired following introduction of N-glycosylation sites during somatic hypermutation and contribute to antibody diversification. We investigated whether Fab glycans may—in addition to affecting antigen binding—contribute to antibody stability. By analyzing thermal unfolding profiles of antibodies with or without Fab glycans, we demonstrate that introduction of Fab glycans can improve antibody stability. Strikingly, removal of Fab glycans naturally acquired during antigen-specific immune responses can deteriorate antibody stability, suggesting in vivo selection of stable, glycosylated antibodies. Collectively, our data show that variable domain N-linked glycans acquired during somatic hypermutation can contribute to IgG antibody stability. These findings indicate that introducing Fab glycans may represent a mechanism to improve therapeutic/diagnostic antibody stability.

Optimizing antibody expression: The nuts and bolts

Antibodies are extensively utilized entities in biomedical research, and in the development of diagnostics and therapeutics. Many of these applications require high amounts of antibodies. However, meeting this ever-increasing demand of antibodies in the global market is one of the outstanding challenges. The need to maintain a balance between demand and supply of antibodies has led the researchers to discover better means and methods for optimizing their expression. These strategies aim to increase the volumetric productivity of the antibodies along with the reduction of associated manufacturing costs. Recent years have witnessed major advances in recombinant protein technology, owing to the introduction of novel cloning strategies, gene manipulation techniques, and an array of cell and vector engineering techniques, together with the progress in fermentation technologies. These innovations were also highly beneficial for antibody expression. Antibody expression depends upon the complex interplay of multiple factors that may require fine tuning at diverse levels to achieve maximum yields. However, each antibody is unique and requires individual consideration and customization for optimizing the associated expression parameters. This review provides a comprehensive overview of several state-of-the-art approaches, such as host selection, strain engineering, codon optimization, gene optimization, vector modification and process optimization that are deemed suitable for enhancing antibody expression.

Engineering the surface properties of a human monoclonal antibody prevents self-association and rapid clearance in vivo

Uncontrolled self-association is a major challenge in the exploitation of proteins as therapeutics. Here we describe the development of a structural proteomics approach to identify the amino acids responsible for aberrant self-association of monoclonal antibodies and the design of a variant with reduced aggregation and increased serum persistence in vivo. We show that the human monoclonal antibody, MEDI1912, selected against nerve growth factor binds with picomolar affinity, but undergoes reversible self-association and has a poor pharmacokinetic profile in both rat and cynomolgus monkeys. Using hydrogen/deuterium exchange and cross-linking-mass spectrometry we map the residues responsible for self-association of MEDI1912 and show that disruption of the self-interaction interface by three mutations enhances its biophysical properties and serum persistence, whilst maintaining high affinity and potency. Immunohistochemistry suggests that this is achieved via reduction of non-specific tissue binding. The strategy developed represents a powerful and generic approach to improve the properties of therapeutic proteins.

Nanoyeast and Other Cell Envelope Compositions for Protein Studies and Biosensor Applications

Rapid progress in disease biomarker discovery has increased the need for robust detection technologies. In the past several years, the designs of many immunoaffinity reagents have focused on lowering costs and improving specificity while also promoting stability. Antibody fragments (scFvs) have long been displayed on the surface of yeast and phage libraries for selection; however, the stable production of such fragments presents challenges that hamper their widespread use in diagnostics. Membrane and cell wall proteins similarly suffer from stability problems when solubilized from their native environment. Recently, cell envelope compositions that maintain membrane proteins in native or native-like lipid environment to improve their stability have been developed. This cell envelope composition approach has now been adapted toward stabilizing antibody fragments by retaining their native cell wall environment. A new class of immunoaffinity reagents has been developed that maintains antibody fragment attachment to yeast cell wall. Herein, we review recent strategies that incorporate cell wall fragments with functional scFvs, which are designed for easy production while maintaining specificity and stability when in use with simple detection platforms. These cell wall based antibody fragments are globular in structure, and heterogeneous in size, with fragments ranging from tens to hundreds of nanometers in size. These fragments appear to retain activity once immobilized onto biosensor surfaces for the specific and sensitive detection of pathogen antigens. They can be quickly and economically generated from a yeast display library and stored lyophilized, at room temperature, for up to a year with little effect on stability. This new format of scFvs provides stability, in a simple and low-cost manner toward the use of scFvs in biosensor applications. The production and "panning" of such antibody cell wall composites are also extremely facile, enabling the rapid adoption of stable and inexpensive affinity reagents for emerging infectious threats.

Rational design of therapeutic mAbs against aggregation through protein engineering and incorporation of glycosylation motifs applied to bevacizumab

The aggregation of biotherapeutics is a major hindrance to the development of successful drug candidates; however, the propensity to aggregate is often identified too late in the development phase to permit modification to the protein's sequence. Incorporating rational design for the stability of proteins in early discovery has numerous benefits. We engineered out aggregation-prone regions on the Fab domain of a therapeutic monoclonal antibody, bevacizumab, to rationally design a biobetter drug candidate. With the purpose of stabilizing bevacizumab with respect to aggregation, 2 strategies were undertaken: single point mutations of aggregation-prone residues and engineering a glycosylation site near aggregation-prone residues to mask these residues with a carbohydrate moiety. Both of these approaches lead to comparable decreases in aggregation, with an up to 4-fold reduction in monomer loss. These single mutations and the new glycosylation pattern of the Fab domain do not modify binding to the target. Biobetters with increased stability against aggregation can therefore be generated in a rational manner, by either removing or masking the aggregation-prone region or crowding out protein-protein interactions.

Recent Progress toward Engineering HIV-1-Specific Neutralizing Monoclonal Antibodies

The recent discoveries of broadly potent neutralizing human monoclonal antibodies represent a new generation of antiretrovirals for the treatment and prophylaxis. Antibodies are generally considered more effective and safer and have been proved to provide passive protection against mucosal challenge in humanized mice and macaques. Several neutralizing Abs could protect animals against HIV-1 but are not effective when used in an established infected model for therapy. In order to overcome the limitation of antiviral activities, multiple antibody-engineering technologies have been explored to generate "the better" neutralizing antibodies against HIV-1 since bNAbs attack viral entry by various mechanisms. Thus, a promising direction of research is to discover and exploit rational antibody combination or engineered antibodies (eAbs) as potential candidate therapeutics against HIV-1. It has been reported that inclusion of fusion-neutralizing antibodies in a set of bNAbs could improve their overall activities and neutralizing spectrum. Here, we review several routes for engineering bNAbs, such as design and generation of bispecific antibodies, specific glycosylation of antibodies to enhance antiviral activity, and variable region-specific modification guided by structure and computer, as well as reviewing antibody-delivery technologies by non-viral vector, viral vector, and human hematopoietic stem/progenitor cells transduced with a lentiviral construct. We also discuss the optimized antiviral activities and benefits of these strategy and potential mechanisms.

Antibody Aggregation: Insights from Sequence and Structure

Monoclonal antibodies (mAbs) are the fastest-growing biological therapeutics with important applications ranging from cancers, autoimmunity diseases and metabolic disorders to emerging infectious diseases. Aggregation of mAbs continues to be a major problem in their developability. Antibody aggregation could be triggered by partial unfolding of its domains, leading to monomer-monomer association followed by nucleation and growth. Although the aggregation propensities of antibodies and antibody-based proteins can be affected by the external experimental conditions, they are strongly dependent on the intrinsic antibody properties as determined by their sequences and structures. In this review, we describe how the unfolding and aggregation susceptibilities of IgG could be related to their cognate sequences and structures. The impact of antibody domain structures on thermostability and aggregation propensities, and effective strategies to reduce aggregation are discussed. Finally, the aggregation of antibody-drug conjugates (ADCs) as related to their sequence/structure, linker payload, conjugation chemistry and drug-antibody ratio (DAR) is reviewed.

Engineering broadly neutralizing antibodies for HIV prevention and therapy

A combination of advances spanning from isolation to delivery of potent HIV-specific antibodies has begun to revolutionize understandings of antibody-mediated antiviral activity. As a result, the set of broadly neutralizing and highly protective antibodies has grown in number, diversity, potency, and breadth of viral recognition and neutralization. These antibodies are now being further enhanced by rational engineering of their anti-HIV activities and coupled to cutting edge gene delivery and strategies to optimize their pharmacokinetics and biodistribution. As a result, the prospects for clinical use of HIV-specific antibodies to treat, clear, and prevent HIV infection are gaining momentum. Here we discuss the diverse methods whereby antibodies are being optimized for neutralization potency and breadth, biodistribution, pharmacokinetics, and effector function with the aim of revolutionizing HIV treatment and prevention options.

A polar ring endows improved specificity to an antibody fragment

Engineering monovalent Fab fragments into bivalent formats like IgGs or F(ab')2 can lead to aggregation presumably because of nonspecific off-target interactions that induce aggregation. In an effort to further understand the molecular determinants of nonspecific interactions for engineered antibodies and natively folded proteins in general, we focused on a synthetic Fab with low nanomolar affinity to histone chaperone Anti-silencing factor 1 (Asf1) that demonstrates off-target binding through low solubility (∼5 mg/mL) in the multivalent F(ab') 2 state. Here, we generated phage display-based shotgun scanning libraries to introduce aspartate as a negative design element into the antibody paratope. The antibody-combining site was amenable to aspartate substitution at numerous positions within the antigen binding loops and one variant, Tyr(L93) Asp/His(L94) Asp/Thr(H100b) Asp, possessed high solubility (>100 mg/ml). Furthermore, the mutations decreased nonspecific interactions measured by column interaction chromatography and ELISA in the multivalent antibody format while maintaining high affinity to the antigen. Structural determination of the antibody-antigen complex revealed that the aspartate-permissive residues formed a polar ring around the structural and functional paratope, recapitulating the canonical feature of naturally occurring protein-protein interactions. This observation may inform future strategies for the design and engineering of molecular recognition.

Antibody engineering for increased potency, breadth and half-life

Purpose of review

This review highlights recent developments in HIV-1 antibody engineering and discusses the effects of increased polyreactivity on serum half-lives of engineered antibodies.

Recent findings

Recent studies have uncovered a wealth of information about the relationship between the sequences and efficacies of anti-HIV-1 antibodies through a combination of bioinformatics, structural characterization and in vivo studies. This knowledge has stimulated efforts to enhance antibody breadth and potency for therapeutic use. Although some engineered antibodies have shown increased polyreactivity and short half-lives, promising efforts are circumventing these problems.

Summary

Antibodies are desirable as therapeutics due to their ability to recognize targets with both specificity and high affinity. Furthermore, the ability of antibodies to stimulate Fc-mediated effector functions can increase their utility. Thus, mAbs have become central to strategies for the treatment of various diseases. Using both targeted and library-based approaches, antibodies can be engineered to improve their therapeutic properties. This article will discuss recent antibody engineering efforts to improve the breadth and potency of anti-HIV-1 antibodies. The polyreactivity of engineered HIV-1 bNAbs and the effect on serum half-life will be explored along with strategies to overcome problems introduced by engineering antibodies. Finally, advances in creating bispecific anti-HIV-1 reagents are discussed.

Overcoming low yields of plant-made antibodies by a protein engineering approach

The commercial development of plant-based antibody production platforms is often limited by low and variable yields, but little is known about the factors that affect antibody accumulation during and after translation. Here, we present a strategy to identify yield-limiting regions in the transcript and protein. We exchanged variable heavy chain (VH) domain sequences between two human antibodies at structurally conserved positions, thus creating ten chimeric VH domains containing sequences from M12 (∼1000 μg/g leaf fresh weight [FW]) and 4E10 (∼100 μg/g FW). After transient expression in Nicotiana benthamiana leaves, we measured mRNA and protein levels by quantitative real-time PCR and surface plasmon resonance spectroscopy, respectively. Transcript levels were similar for all constructs, but antibody levels ranged from ∼250 μg/g to over 2000 μg/g FW. Analysis of the expression levels showed that: i) 4E10 yields were only marginally increased by suppression of post-transcriptional gene silencing; ii) the CDR3 of 4E10 contains a protease site; and iii) a bipartite, yield-limiting region exists in the CDR2/CDR3. Our findings highlight the strong impact of cotranslational and posttranslational events on antibody yields and show that protein engineering is a powerful tool that can be used to overcome the remaining limitations affecting antibody production in plants.

Resolving self-association of a therapeutic antibody by formulation optimization and molecular approaches

A common challenge encountered during development of high concentration monoclonal antibody formulations is preventing self-association. Depending on the antibody and its formulation, self-association can be seen as aggregation, precipitation, opalescence or phase separation. Here we report on an unusual manifestation of self-association, formation of a semi-solid gel or "gelation." Therapeutic monoclonal antibody C4 was isolated from human B cells based on its strong potency in neutralizing bacterial toxin in animal models. The purified antibody possessed the unusual property of forming a firm, opaque white gel when it was formulated at concentrations >30 mg/mL and the temperature was <6°C. Gel formation was reversible with temperature. Gelation was affected by salt concentration or pH, suggesting an electrostatic interaction between IgG monomers. A comparison of the C4 amino acid sequences to consensus germline sequences revealed differences in framework regions. A C4 variant in which the framework sequence was restored to the consensus germline sequence did not gel at 100 mg/mL at temperatures as low as 1°C. Additional genetic analysis was used to predict the key residue(s) involved in the gelation. Strikingly, a single substitution in the native antibody, replacing heavy chain glutamate 23 with lysine (E23K), was sufficient to prevent gelation. These results indicate that the framework region is involved in intermolecular interactions. The temperature dependence of gelation may be related to conformational changes near glutamate 23 or the regions it interacts with. Molecular engineering of the framework can be an effective approach to resolve the solubility issues of therapeutic antibodies.

Advances in Antibody Design

The use of monoclonal antibodies as therapeutics requires optimizing several of their key attributes. These include binding affinity and specificity, folding stability, solubility, pharmacokinetics, effector functions, and compatibility with the attachment of additional antibody domains (bispecific antibodies) and cytotoxic drugs (antibody-drug conjugates). Addressing these and other challenges requires the use of systematic design methods that complement powerful immunization and in vitro screening methods. We review advances in designing the binding loops, scaffolds, domain interfaces, constant regions, post-translational and chemical modifications, and bispecific architectures of antibodies and fragments thereof to improve their bioactivity. We also highlight unmet challenges in antibody design that must be overcome to generate potent antibody therapeutics.