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Monoclonal antibodies are being used to treat a remarkable breadth of human disorders. Nevertheless, there are several key challenges at the earliest stages of antibody drug development that need to be addressed using simple and widely accessible methods, especially related to generating antibodies against membrane proteins and identifying antibody candidates with drug-like biophysical properties (high solubility and low viscosity). Here we highlight key bionanotechnologies for preparing functional and stable membrane proteins in diverse types of lipoparticles that are being used to improve antibody discovery and engineering efforts. We also highlight key bionanotechnologies for high-throughput and ultra-dilute screening of antibody biophysical properties during antibody discovery and optimization that are being used for identifying antibodies with superior combinations of in vitro (formulation) and in vivo (half-life) properties.

Neutralizing monoclonal antibodies and nanobodies have shown promising results as potential therapeutic agents for COVID-19. Identifying such antibodies and nanobodies requires evaluating the neutralization activity of a large number of lead molecules via biological assays, such as the virus neutralization test (VNT). These assays are typically time-consuming and demanding on lab facilities. Here, we present a rapid and quantitative assay that evaluates the neutralizing efficacy of an antibody or nanobody within 1.5 hours, does not require BSL-2 facilities, and consumes only 8 μL of low concentration (ng/mL) sample for each assay run. We tested the human angiotensin-converting enzyme 2 (ACE2) binding inhibition efficacy of seven antibodies and eight nanobodies and verified that the IC(50) values of our assay are comparable with those from SARS-CoV-2 pseudovirus neutralization tests. We also found that our assay could evaluate the neutralizing efficacy against three widespread SARS-CoV-2 variants. We observed increased affinity of these variants for ACE2, including the Beta and Gamma variants. Finally, we demonstrated that our assay enables rapid identification of an immune-evasive mutation of the SARS-CoV-2 spike protein utilizing a set of nanobodies with known binding epitopes.

Agonist antibodies that activate cellular signaling have emerged as promising therapeutics for treating myriad pathologies. Unfortunately, the discovery of rare antibodies with the desired agonist functions is a major bottleneck during drug development. Nevertheless, there has been important recent progress in discovering and optimizing agonist antibodies against a variety of therapeutic targets that are activated by diverse signaling mechanisms. Herein, we review emerging high-throughput experimental and computational methods for agonist antibody discovery as well as rational molecular engineering methods for optimizing their agonist activity.

Agonist antibodies that target immune checkpoints, such as those in the tumor necrosis factor receptor (TNFR) superfamily, are an important class of emerging therapeutics due to their ability to regulate immune cell activity, especially for treating cancer. Despite their potential, to date, they have shown limited clinical utility and further antibody optimization is urgently needed to improve their therapeutic potential. Here, we discuss key antibody engineering approaches for improving the activity of antibody agonists by optimizing their valency, specificity for different receptors (e.g., bispecific antibodies) and epitopes (e.g., biepitopic or biparatopic antibodies), and Fc affinity for Fcγ receptors (FcγRs). These powerful approaches are being used to develop the next generation of cancer immunotherapeutics with improved efficacy and safety.

SARS-CoV-2 variants with enhanced transmissibility represent a serious threat to global health. Here we report machine learning models that can predict the impact of receptor-binding domain (RBD) mutations on receptor (ACE2) affinity, which is linked to infectivity, and escape from human serum antibodies, which is linked to viral neutralization. Importantly, the models predict many of the known impacts of RBD mutations in current and former Variants of Concern on receptor affinity and antibody escape as well as novel sets of mutations that strongly modulate both properties. Moreover, these models reveal key opposing impacts of RBD mutations on transmissibility, as many sets of RBD mutations predicted to increase antibody escape are also predicted to reduce receptor affinity and vice versa. These models, when used in concert, capture the complex impacts of SARS-CoV-2 mutations on properties linked to transmissibility and are expected to improve the development of next-generation vaccines and biotherapeutics.

The rapidly evolving nature of antibody drug development has resulted in technologies that generate vast numbers (hundreds to thousands) of lead antibody candidates during early discovery. These candidates must be rapidly pared down to identify the most drug-like candidates for in-depth analysis of their safety and efficacy, which can only be performed on a limited number of antibodies due to time and resource requirements. One key biophysical property of successful antibody therapeutics is high specificity, defined as low levels of nonspecific binding or polyspecificity. Although there has been some progress in developing assays for detecting antibody polyspecificity, most of these assays are limited by poor sensitivity or assay formats that require proprietary antibody surface display methods, and some of these assays use complex and poorly defined polyspecificity reagents. Here we report the PolySpecificity Particle (PSP) assay, a sensitive flow cytometry assay for evaluating antibody nonspecific interactions that overcomes previous limitations and can be used for evaluating diverse types of IgGs, multispecific antibodies and Fc-fusion proteins. Our approach uses micron-sized magnetic beads coated with Protein A to capture antibodies at extremely dilute concentrations (

There is significant interest in formulating antibody therapeutics as concentrated liquid solutions, but early identification of developable antibodies with optimal manufacturability, stability, and delivery attributes remains challenging. Traditional methods of identifying developable mAbs with low self-association in common antibody formulations require relatively concentrated protein solutions (>1 mg/mL), and this single challenge has frustrated early-stage and large-scale identification of antibody candidates with drug-like colloidal properties. Here, we describe charge-stabilized self-interaction nanoparticle spectroscopy (CS-SINS), an affinity-capture nanoparticle assay that measures colloidal self-interactions at ultradilute antibody concentrations (0.01 mg/mL), and is predictive of antibody developability issues of high viscosity and opalescence that manifest at four orders of magnitude higher concentrations (>100 mg/mL). CS-SINS enables large-scale, high-throughput selection of developable antibodies during early discovery.

The identification of antibody variable regions in the heavy (VH) and light (VL) chains from hybridomas is necessary for the production of recombinant, sequence-defined monoclonal antibodies (mAbs) and antibody derivatives. This process has received renewed attention in light of recent reports of hybridomas having unintended specificities due to the production of non-antigen specific heavy and/or light chains for the intended antigen. Here we report a surprising finding and potential pitfall in variable domain sequencing of an anti-human CD63 hybridoma. We amplified multiple VL genes from the hybridoma cDNA, including the well-known aberrant Sp2/0 myeloma VK and a unique, full-length VL. After finding that the unique VL failed to yield a functional antibody, we discovered an additional full-length sequence with surprising similarity (~95% sequence identify) to the non-translated myeloma kappa chain but with a correction of its key frameshift mutation. Expression of the recombinant mAb confirmed that this highly homologous sequence is the antigen-specific light chain. Our results highlight the complexity of PCR-based cloning of antibody genes and strategies useful for identification of correct sequences.

There is intense and widespread interest in developing monoclonal antibodies as therapeutic agents to treat diverse human disorders. During early-stage antibody discovery, hundreds to thousands of lead candidates are identified, and those that lack optimal physical and chemical properties must be deselected as early as possible to avoid problems later in drug development. It is particularly challenging to characterize such properties for large numbers of candidates with the low antibody quantities, concentrations, and purities that are available at the discovery stage, and to predict concentrated antibody properties (e.g., solubility, viscosity) required for efficient formulation, delivery, and efficacy. Here we review key recent advances in developing and implementing high-throughput methods for identifying antibodies with desirable in vitro and in vivo properties, including favorable antibody stability, specificity, solubility, pharmacokinetics, and immunogenicity profiles, that together encompass overall drug developability. In particular, we highlight impressive recent progress in developing computational methods for improving rational antibody design and prediction of drug-like behaviors that hold great promise for reducing the amount of required experimentation. We also discuss outstanding challenges that will need to be addressed in the future to fully realize the great potential of using such analysis for minimizing development times and improving the success rate of antibody candidates in the clinic.

The success of antibody therapeutics is strongly influenced by their multifunctional nature that couples antigen recognition mediated by their variable regions with effector functions and half-life extension mediated by a subset of their constant regions. Nevertheless, the monospecific IgG format is not optimal for many therapeutic applications, and this has led to the design of a vast number of unique multispecific antibody formats that enable targeting of multiple antigens or multiple epitopes on the same antigen. Despite the diversity of these formats, a common challenge in generating multispecific antibodies is that they display suboptimal physical and chemical properties relative to conventional IgGs and are more difficult to develop into therapeutics. Here we review advances in the design and engineering of multispecific antibodies with drug-like properties, including favorable stability, solubility, viscosity, specificity and pharmacokinetic properties. We also highlight emerging experimental and computational methods for improving the next generation of multispecific antibodies, as well as their constituent antibody fragments, with natural IgG-like properties. Finally, we identify several outstanding challenges that need to be addressed to increase the success of multispecific antibodies in the clinic.

The aggregation of amyloidogenic polypeptides is strongly linked to several neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. Conformational antibodies that selectively recognize protein aggregates are leading therapeutic agents for selectively neutralizing toxic aggregates, diagnostic and imaging agents for detecting disease, and biomedical reagents for elucidating disease mechanisms. Despite their importance, it is challenging to generate high-quality conformational antibodies in a systematic and site-specific manner due to the properties of protein aggregates (hydrophobic, multivalent, and heterogeneous) and limitations of immunization (uncontrolled antigen presentation and immunodominant epitopes). Toward addressing these challenges, we have developed a systematic directed evolution procedure for affinity maturing antibodies against Alzheimer's Aβ fibrils and selecting variants with strict conformational and sequence specificity. We first designed a library based on a lead conformational antibody by sampling combinations of amino acids in the antigen-binding site predicted to mediate high antibody specificity. Next, we displayed this library on the surface of yeast, sorted it against Aβ42 aggregates, and identified promising clones using deep sequencing. The resulting antibodies displayed similar or higher affinities than clinical-stage Aβ antibodies (aducanumab and crenezumab). Moreover, the affinity-matured antibodies retained high conformational specificity for Aβ aggregates, as observed for aducanumab and unlike crenezumab. Notably, the affinity-maturated antibodies displayed extremely low levels of nonspecific interactions, as observed for crenezumab and unlike aducanumab. We expect that our systematic methods for generating antibodies with unique combinations of desirable properties will improve the generation of high-quality conformational antibodies specific for diverse types of aggregated conformers.

Biologics such as peptides and proteins possess a number of attractive attributes that make them particularly valuable as therapeutics, including their high activity, high specificity, and low toxicity. However, one of the key challenges associated with this class of drugs is their propensity to aggregate. Given the safety and immunogenicity concerns related to polypeptide aggregates, it is particularly important to sensitively detect aggregates in therapeutic drug formulations as part of the quality control process. Here, we report the development of conformation-specific antibodies that recognize polypeptide aggregates composed of a GLP-1 receptor agonist (liraglutide) and their integration into a sensitive immunoassay for detecting liraglutide amyloid fibrils. We sorted single-chain antibody libraries against liraglutide fibrils using yeast surface display and magnetic-activated cell sorting, and identified several antibodies with high conformational specificity. Interestingly, these antibodies cross-react with amyloid fibrils formed by several other polypeptides, revealing that they recognize molecular features common to different types of fibrils. Moreover, we find that our immunoassay using these antibodies is >50-fold more sensitive than the conventional method for detecting liraglutide aggregation (Thioflavin T fluorescence). We expect that our systematic approach for generating a sensitive, aggregate-specific immunoassay can be readily extended to other biologics to improve the quality and safety of formulated drug products.

Summary The generation of high-affinity nanobodies for diverse biomedical applications typically requires immunization or affinity maturation. Here, we report a simple protocol using complementarity-determining region (CDR)-swapping mutagenesis to isolate high-affinity nanobodies from common framework libraries. This approach involves shuffling the CDRs of low-affinity variants during the sorting of yeast-displayed libraries to directly isolate high-affinity nanobodies without the need for lead isolation and optimization. We expect this approach, which we demonstrate for SARS-CoV-2 neutralizing nanobodies, will simplify the generation of high-affinity nanobodies. For complete details on the use and execution of this profile, please refer to Zupancic et al. (2021)., Graphical abstract, Highlights • Protocol enables direct isolation of high-affinity nanobodies from synthetic libraries • Individual CDRs are amplified and recombined to obtain nanobodies with shuffled CDRs • Libraries of CDR-shuffled nanobodies are rapidly sorted to obtain high-affinity clones • Monovalent and bivalent nanobody affinities are determined using flow cytometry, The generation of high-affinity nanobodies for diverse biomedical applications typically requires immunization or affinity maturation. Here, we report a simple protocol using complementarity-determining region (CDR)-swapping mutagenesis to isolate high-affinity nanobodies from common framework libraries. This approach involves shuffling the CDRs of low-affinity variants during the sorting of yeast-displayed libraries to directly isolate high-affinity nanobodies without the need for lead isolation and optimization. We expect this approach, which we demonstrate for SARS-CoV-2 neutralizing nanobodies, will simplify the generation of high-affinity nanobodies.

Specificity is one of the most important and complex properties that is central to both natural antibody function and therapeutic antibody efficacy. However, it has proven extremely challenging to define robust guidelines for predicting antibody specificity. Here we evaluated the physicochemical determinants of antibody specificity for multiple panels of antibodies, including >100 clinical-stage antibodies. Surprisingly, we find that the theoretical net charge of the complementarity-determining regions (CDRs) is a strong predictor of antibody specificity. Antibodies with positively charged CDRs have a much higher risk of low specificity than antibodies with negatively charged CDRs. Moreover, the charge of the entire set of six CDRs is a much better predictor of antibody specificity than the charge of individual CDRs, variable domains (VH or VL) or the entire variable fragment (Fv). The best indicators of antibody specificity in terms of CDR amino acid composition are reduced levels of arginine and lysine and increased levels of aspartic and glutamic acid. Interestingly, clinical-stage antibodies with negatively charged CDRs also have a lower risk for poor biophysical properties in general, including a reduced risk for high levels of self-association. These findings provide powerful guidelines for predicting antibody specificity and for identifying safe and potent antibody therapeutics.

Autonomous heavy-chain variable (VH) domains are the smallest functional antibody fragments, and they possess unique features, including small size and convex paratopes, which provide enhanced targeting of concave epitopes that are difficult to access with larger conventional antibodies. However, human VH domains have evolved to fold and function with a light chain partner, and alone, they typically suffer from low stability and high aggregation propensity. Development of autonomous human VH domains, in which aggregation propensity is reduced without compromising antigen recognition, has proven challenging. Here, we used an autonomous human VH domain as a scaffold to construct phage-displayed synthetic libraries in which aspartate was systematically incorporated at different paratope positions. In selections, the library yielded many anti-EphA1 receptor VH domains, which were characterized in detail. Structural analyses of a parental anti-EphA1 VH domain and an improved variant provided insights into the effects of aspartate and other substitutions on preventing aggregation while retaining function. Our naive libraries and in vitro selection procedures offer a systematic approach to generating highly functional autonomous human VH domains that resist aggregation and could be used for basic research and biomedical applications.

Antibodies commonly accumulate charged mutations in their complementarity-determining regions (CDRs) during affinity maturation to enhance electrostatic interactions. However, charged mutations can mediate non-specific interactions, and it is unclear to what extent CDRs can accumulate charged residues to increase antibody affinity without compromising specificity. This is especially concerning for positively charged CDR mutations that are linked to antibody polyspecificity. To better understand antibody affinity/specificity trade-offs, we have selected single-chain antibody fragments specific for the negatively charged and hydrophobic Alzheimer's amyloid β peptide using weak and stringent selections for antibody specificity. Antibody variants isolated using weak selections for specificity were enriched in arginine CDR mutations and displayed low specificity. Alanine-scanning mutagenesis revealed that the affinities of these antibodies were strongly dependent on their arginine mutations. Antibody variants isolated using stringent selections for specificity were also enriched in arginine CDR mutations, but these antibodies possessed significant improvements in specificity. Importantly, the affinities of the most specific antibodies were much less dependent on their arginine mutations, suggesting that over-reliance on arginine for affinity leads to reduced specificity. Structural modeling and molecular simulations reveal unique hydrophobic environments near the arginine CDR mutations. The more specific antibodies contained arginine mutations in the most hydrophobic portions of the CDRs, whereas the less specific antibodies contained arginine mutations in more hydrophilic regions. These findings demonstrate that arginine mutations in antibody CDRs display context-dependent impacts on specificity and that affinity/specificity trade-offs are governed by the relative contribution of arginine CDR residues to the overall antibody affinity.

The pharmacokinetic properties of antibodies are largely dictated by the pH-dependent binding of the IgG fragment crystallizable (Fc) domain to the human neonatal Fc receptor (hFcRn). Engineered Fc domains that confer a longer circulation half-life by virtue of more favorable pH-dependent binding to hFcRn are of great therapeutic interest. Here we developed a pH Toggle switch Fc variant containing the L309D/Q311H/N434S (DHS) substitutions, which exhibits markedly improved pharmacokinetics relative to both native IgG1 and widely used half-life extension variants, both in conventional hFcRn transgenic mice and in new knock-in mouse strains. engineered specifically to recapitulate all the key processes relevant to human antibody persistence in circulation, namely: (i) physiological expression of hFcRn, (ii) the impact of hFcγRs on antibody clearance and (iii) the role of competing endogenous IgG. DHS-IgG retains intact effector functions, which are important for the clearance of target pathogenic cells and also has favorable developability., Lee et al. report an engineered IgG1 Fc domain that behaves like an hFcRn binding pH toggle switch. The authors show that this new half-life extension Fc domain confers improved pharmacokinetics in new humanized knock-in mouse strains that recapitulate the key processes for antibody persistence in circulation.

The pharmacokinetic properties of antibodies are largely dictated by the pH-dependent binding of the IgG fragment crystallizable (Fc) domain to the human neonatal Fc receptor (hFcRn). Engineered Fc domains that confer a longer circulation half-life by virtue of more favorable pH-dependent binding to hFcRn are of great therapeutic interest. Here we developed a pH Toggle switch Fc variant containing the L309D/Q311H/N434S (DHS) substitutions, which exhibits markedly improved pharmacokinetics relative to both native IgG1 and widely used half-life extension variants, both in conventional hFcRn transgenic mice and in new knock-in mouse strains. engineered specifically to recapitulate all the key processes relevant to human antibody persistence in circulation, namely: (i) physiological expression of hFcRn, (ii) the impact of hFcγRs on antibody clearance and (iii) the role of competing endogenous IgG. DHS-IgG retains intact effector functions, which are important for the clearance of target pathogenic cells and also has favorable developability.

Monoclonal antibodies must be both chemically and physically stable to be developed into safe and effective drugs. Although there has been considerable progress in separately understanding the molecular determinants of antibody chemical and physical stability, it remains poorly understood how defects in one property (e.g., chemical stability) impact the other property (e.g., physical stability). Here, we have investigated the impact of a common chemical modification (deamidation) on the physical stability of two monoclonal antibodies as a function of pH (from pH 3.8 to 7.4). Interestingly, we find that deamidation has significant, antibody-specific impacts on physical stability at low pH values that are common during antibody purification. Deamidation causes increases in self-association and/or aggregation at low pH (3.8), and a key contributor to this behavior appears to be deamidation-dependent increases in antibody hydrophobicity at low pH. Our findings highlight pH-dependent impacts of deamidation on antibody colloidal stability and aggregation, which are important to understand in order to improve the development and production of potent antibody therapeutics with high chemical and physical stabilities.

Sensitive detection of protein aggregates is important for evaluating the quality of biopharmaceuticals and detecting misfolded proteins in several neurodegenerative diseases. However, it is challenging to detect extremely low concentrations (10 ppm) of aggregated protein in the presence of high concentrations of soluble protein. Glucagon, a peptide hormone used in the treatment of extreme hypoglycemia, is aggregation-prone and forms amyloid fibrils. Detection of glucagon fibrils using conformation-specific antibodies is an attractive approach for identifying such aggregates during process and formulation development. Therefore, we have used yeast surface display and magnetic-activated cell sorting to sort single-chain antibody libraries to identify antibody variants with high conformational specificity for glucagon fibrils. Notably, we find several high-affinity antibodies that display excellent selectivity for glucagon fibrils, and we have integrated these antibodies into a sensitive immunoassay. Surprisingly, the sensitivity of our assay-which involves direct (nonantibody mediated) glucagon immobilization in microtiter plates-can be significantly enhanced by pretreating the microtiter plates with various types of globular proteins before glucagon immobilization. Moreover, increased total concentrations of glucagon peptide also significantly improve the sensitivity of our assay, which appears to be due to the strong seeding activity of immobilized fibrils at high glucagon concentrations. Our final assay is highly sensitive (fibril detection limit of ~0.5-1 ppm) and is20 times more sensitive than detection using a conventional, amyloid-specific fluorescent dye (Thioflavin T). We expect that this type of sensitive immunoassay can be readily integrated into the drug development process to improve the generation of safe and potent peptide therapeutics.

Successful development of monoclonal antibodies (mAbs) for therapeutic applications requires identification of mAbs with favorable biophysical properties (high solubility and low viscosity) in addition to potent bioactivities. Nevertheless, mAbs can also display complex, nonconventional biophysical properties that impede their development such as formation of soluble aggregates and subvisible particles as well as nonspecific interactions with various types of surfaces such as nonadsorptive chromatography columns. Here we have investigated the potential of using antibody self-interaction measurements obtained via affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS) at dilute concentrations (0.01 mg/mL) for ranking a panel of 12 mAbs in terms of their expected biophysical properties at higher concentrations (1-30 mg/mL). Several mAb properties (solubility, % monomer, size-exclusion elution time and % recovery) displayed modest correlation with each other, as some mAbs with deficiencies in one or more properties (e.g., solubility) failed to show deficiencies in other properties (e.g., % monomer). The ranking of mAbs in terms of their level of self-association was correlated with their solubility ranking. However, the correlation was even stronger between the average ranking of the four biophysical properties and the AC-SINS measurements. This finding suggests that weak self-interactions detected via AC-SINS can manifest themselves in different ways and lead to complex biophysical properties. Our findings highlight the potential for using high-throughput self-interaction measurements to improve the identification of mAbs that possess a collection of excellent biophysical properties without the need for cumbersome analysis of each individual property during early candidate selection.

Antibodies that recognize amyloidogenic aggregates with high conformational and sequence specificity are important for detecting and potentially treating a wide range of neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. However, these types of antibodies are challenging to generate because of the large size, hydrophobicity, and heterogeneity of protein aggregates. To address this challenge, we developed a method for generating antibodies specific for amyloid aggregates. First, we grafted amyloidogenic peptide segments from the target polypeptide [Alzheimer's amyloid-β (Aβ) peptide] into the complementarity-determining regions (CDRs) of a stable antibody scaffold. Next, we diversified the grafted and neighboring CDR sites using focused mutagenesis to sample each WT or grafted residue, as well as one to five of the most commonly occurring amino acids at each site in human antibodies. Finally, we displayed these antibody libraries on the surface of yeast cells and selected antibodies that strongly recognize Aβ-amyloid fibrils and only weakly recognize soluble Aβ. We found that this approach enables the generation of monovalent and bivalent antibodies with nanomolar affinity for Aβ fibrils. These antibodies display high conformational and sequence specificity as well as low levels of nonspecific binding and recognize a conformational epitope at the extreme N terminus of human Aβ. We expect that this systematic approach will be useful for generating antibodies with conformational and sequence specificity against a wide range of peptide and protein aggregates associated with neurodegenerative disorders.

Self-association of monoclonal antibodies (mAbs) at high concentrations can result in developability challenges such as poor solubility, aggregation, opalescence and high viscosity. There is a significant unmet need for methods that can evaluate self-association propensities of concentrated mAbs at the earliest stages in antibody discovery to avoid downstream issues. We have previously developed a method (affinity-capture self-interaction nanoparticle spectroscopy, AC-SINS) that is capable of detecting weak antibody self-interactions using unusually dilute mAb solutions (tens of µg/ml). Here we optimize and implement this assay for characterization of unpurified and highly dilute mAbs directly in cell culture media. This assay was applied to screen 87 mAbs obtained via immunization. Our measurements reveal a wide range of self-associative propensities for mAbs that bind to the same antigen and which differ mainly in their complementarity-determining regions. The least associative mAbs identified by AC-SINS were confirmed to be highly soluble when purified and concentrated by three to five orders of magnitude. This approach represents a key advance in screening mAb variants using unpurified antibody samples, and it holds significant potential to both improve initial candidate selection as well as to guide protein engineering efforts to improve the properties of specific mAb candidates.

A diverse range of proteins can assemble into amyloid fibrils, a process that generally results in a loss of function and an increase in toxicity. The occurrence and rate of conversion is strongly dependent on several factors including molecular structure and exposure to hydrodynamic forces. To investigate the origins of shear-induced enhancement in the rate of fibrillization, a stable rotating Couette flow was used to evaluate the kinetics of amyloid formation under uniform shear for two similar insulin species (human and bovine) that demonstrate unique fibrillization kinetics. The presence of shear-induced nuclei predicted by previous studies is supported by observations of a lag between the consumption of soluble insulin and the precipitation of amyloid aggregates. The apparent fibrillization rate generally increases with shear. However, a two-parameter kinetic model revealed that the nucleation rate has a maximum value at intermediate shear rates. The fibril elongation rate increases monotonically with shear and is similar for both insulin variants, suggesting that increased elongation rates are related to mixing. Differences between human and bovine insulin kinetics under shear are attributable to the nucleation step.

The effectiveness of therapeutic monoclonal antibodies (mAbs) is governed not only by their bioactivity, but also by their biophysical properties. Assays for rapidly evaluating the biophysical properties of mAbs are valuable for identifying those most likely to exhibit superior properties such as high solubility, low viscosity and slow serum clearance. Analytical hydrophobic interaction chromatography (HIC), which is performed at high salt concentrations to enhance hydrophobic interactions, is an attractive assay for identifying mAbs with low hydrophobicity. However, this assay is low throughput and thus not amenable to processing the large numbers of mAbs that are commonly generated during antibody discovery. Therefore, we investigated whether an alternative, higher throughput, assay could be developed that is based on evaluating antibody self-association at high salt concentrations using affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS). Our approach is to coat gold nanoparticles with polyclonal anti-human antibodies, use these conjugates to immobilize human mAbs, and evaluate mAb self-interactions by measuring the plasmon wavelengths of the antibody conjugates as a function of ammonium sulfate concentration. We find that hydrophobic mAbs, as identified by HIC, generally show significant self-association at low to moderate ammonium sulfate concentrations, while hydrophilic mAbs typically show self-association only at high ammonium sulfate concentrations. The correlation between AC-SINS and HIC measurements suggests that our assay, which can evaluate tens to hundreds of mAbs in a parallel manner and requires only small (microgram) amounts of antibody, will enable early identification of mAb candidates with low hydrophobicity and improved biophysical properties.

In vitro antibody discovery and/or affinity maturation are often performed using antibody fragments (Fabs), but most monovalent Fabs are reformatted as bivalent IgGs (monoclonal antibodies, mAbs) for therapeutic applications. One problem related to reformatting antibodies is that the bivalency of mAbs can lead to increased antibody self-association and poor biophysical properties (e.g., reduced antibody solubility and increased viscosity). Therefore, it is important to identify monovalent Fabs early in the discovery and/or optimization process that will display favorable biophysical properties when reformatted as bivalent mAbs. Here we demonstrate a facile approach for evaluating Fab self-association in a multivalent assay format that is capable of identifying antibodies with low self-association and favorable colloidal properties when reformatted as bivalent mAbs. Our approach (self-interaction nanoparticle spectroscopy, SINS) involves immobilizing Fabs on gold nanoparticles in a multivalent format (multiple Fabs per nanoparticle) and evaluating their self-association behavior via shifts in the plasmon wavelength or changes in the absorbance values. Importantly, we find that SINS measurements of Fab self-association are correlated with self-interaction measurements of bivalent mAbs and are useful for identifying antibodies with favorable biophysical properties. Moreover, the significant differences in the levels of self-association detected for Fabs and mAbs with similar frameworks can be largely explained by the physicochemical properties of the complementarity-determining regions (CDRs). Comparison of the properties of the CDRs in this study relative to those of approved therapeutic antibodies reveals several key factors (net charge, fraction of charged residues, and presence of self-interaction motifs) that strongly influence antibody self-association behavior. Increased positive charge in the CDRs was observed to correlate with increased risk of high self-association for the mAbs in this study and clinical-stage antibodies. We expect that these findings will be useful for improving the development of therapeutic antibodies that are well suited for high concentration applications.

The ability of antibodies to accumulate affinity-enhancing mutations in their complementarity-determining regions (CDRs) without compromising thermodynamic stability is critical to their natural function. However, it is unclear if affinity mutations in the hypervariable CDRs generally impact antibody stability and to what extent additional compensatory mutations are required to maintain stability during affinity maturation. Here we have experimentally and computationally evaluated the functional contributions of mutations acquired by a human variable (VH) domain that was evolved using strong selections for enhanced stability and affinity for the Alzheimer’s Aβ42 peptide. Interestingly, half of the key affinity mutations in the CDRs were destabilizing. Moreover, the destabilizing effects of these mutations were compensated for by a subset of the affinity mutations that were also stabilizing. Our findings demonstrate that the accumulation of both affinity and stability mutations is necessary to maintain thermodynamic stability during extensive mutagenesis and affinity maturation in vitro, which is similar to findings for natural antibodies that are subjected to somatic hypermutation in vivo. These findings for diverse antibodies and antibody fragments specific for unrelated antigens suggest that the formation of the antigen-binding site is generally a destabilizing process and that co-enrichment for compensatory mutations is critical for maintaining thermodynamic stability.

Antibodies with conformational specificity are important for detecting and interfering with polypeptide aggregation linked to several human disorders. We are developing a motif-grafting approach for designing lead antibody candidates specific for amyloid-forming polypeptides such as the Alzheimer peptide (Aβ). This approach involves grafting amyloidogenic peptide segments into the complementarity-determining regions (CDRs) of single-domain (VH) antibodies. Here we have investigated the impact of polar mutations inserted at the edges of a large hydrophobic Aβ42 peptide segment (Aβ residues 17-42) in CDR3 on the solubility and conformational specificity of the corresponding VH domains. We find that VH expression and solubility are strongly enhanced by introducing multiple negatively charged or asparagine residues at the edges of CDR3, whereas other polar mutations are less effective (glutamine and serine) or ineffective (threonine, lysine, and arginine). Moreover, Aβ VH domains with negatively charged CDR3 mutations show significant preference for recognizing Aβ fibrils relative to Aβ monomers, whereas the same VH domains with other polar CDR3 mutations recognize both Aβ conformers. We observe similar behavior for a VH domain grafted with a large hydrophobic peptide from islet amyloid polypeptide (residues 8-37) that contains negatively charged mutations at the edges of CDR3. These findings highlight the sensitivity of antibody binding and solubility to residues at the edges of CDRs, and provide guidelines for designing other grafted antibody fragments with hydrophobic binding loops.

The ability of antibodies to bind to target molecules with high affinity and specificity has led to their widespread use in diagnostic and therapeutic applications. Nevertheless, a limitation of antibodies is their propensity to self-associate and aggregate at high concentrations and elevated temperatures. The large size and multidomain architecture of full-length monoclonal antibodies have frustrated systematic analysis of how antibody sequence and structure regulate antibody solubility. In contrast, analysis of single and multidomain antibody fragments that retain the binding activity of mono-clonal antibodies has provided valuable insights into the determinants of antibody aggregation. Here we review advances in engineering antibody frameworks, domain interfaces, and antigen-binding loops to prevent aggregation of natively and nonnatively folded antibody fragments. We also highlight advances and unmet challenges in developing robust strategies for engineering large, multidomain antibodies to resist aggregation.

Several protein conformational disorders (Parkinson and prion diseases) are linked to aberrant folding of proteins into prefibrillar oligomers and amyloid fibrils. Although prefibrillar oligomers are more toxic than their fibrillar counterparts, it is difficult to decouple the origin of their dissimilar toxicity because oligomers and fibrils differ both in terms of structure and size. Here we report the characterization of two oligomers of the 42-residue amyloid β (Aβ42) peptide associated with Alzheimer disease that possess similar size and dissimilar toxicity. We find that Aβ42 spontaneously forms prefibrillar oligomers at Aβ concentrations below 30 μm in the absence of agitation, whereas higher Aβ concentrations lead to rapid formation of fibrils. Interestingly, Aβ prefibrillar oligomers do not convert into fibrils under quiescent assembly conditions but instead convert into a second type of oligomer with size and morphology similar to those of Aβ prefibrillar oligomers. Strikingly, this alternative Aβ oligomer is non-toxic to mammalian cells relative to Aβ monomer. We find that two hydrophobic peptide segments within Aβ (residues 16-22 and 30-42) are more solvent-exposed in the more toxic Aβ oligomer. The less toxic oligomer is devoid of β-sheet structure, insoluble, and non-immunoreactive with oligomer- and fibril-specific antibodies. Moreover, the less toxic oligomer is incapable of disrupting lipid bilayers, in contrast to its more toxic oligomeric counterpart. Our results suggest that the ability of non-fibrillar Aβ oligomers to interact with and disrupt cellular membranes is linked to the degree of solvent exposure of their central and C-terminal hydrophobic peptide segments.

Monoclonal antibodies are typically monomeric and nonviscous at low concentrations, yet they display highly variable associative and viscous behavior at elevated concentrations. Although measurements of antibody self-association are critical for understanding this complex behavior, traditional biophysical methods are not capable of characterizing such concentration-dependent self-association in a high-throughput manner. Here we describe a nanoparticle-based method, termed self-interaction nanoparticle spectroscopy, that is capable of rapidly measuring concentration-dependent self-interactions for three human monoclonal antibodies with unique solution behaviors. We demonstrate that gold nanoparticles conjugated with antibodies at low protein concentrations (

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.

A limitation of using mAbs as therapeutic molecules is their propensity to associate with themselves and/or with other molecules via nonaffinity (colloidal) interactions. This can lead to a variety of problems ranging from low solubility and high viscosity to off-target binding and fast antibody clearance. Measuring such colloidal interactions is challenging given that they are weak and potentially involve diverse target molecules. Nevertheless, assessing these weak interactions-especially during early antibody discovery and lead candidate optimization-is critical to preventing problems that can arise later in the development process. Here we review advances in developing and implementing sensitive methods for measuring antibody colloidal interactions as well as using these measurements for guiding antibody selection and engineering. These systematic efforts to minimize nonaffinity interactions are expected to yield more effective and stable mAbs for diverse therapeutic applications. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 103:3356-3363, 2014.

One of the most significant challenges in developing therapeutic monoclonal antibodies (mAbs) is their unpredictable solubilities and viscosities at the high concentrations required for subcutaneous delivery. This challenge has motivated the development of screening assays that rapidly identify mAb variants with minimal self-association propensities and/or formulation conditions that suppress mAb self-association. Here we report an improved version of self-interaction nanoparticle spectroscopy (SINS)capable of characterizing both repulsive and attractive self-interactions between diverse mAbs. The basis of SINS is that self-interactions between mAbs immobilized on gold nanoparticles increase (repulsion) or decrease (attraction)interparticle distances, which shift the wavelength of maximum absorbance (plasmon wavelength) in opposite directions.We find that the robustness of SINS is improved by varying the amount of immobilized mAb by co-adsorbing a polyclonal antibody. The slopes of the plasmon wavelength shifts as a function of the amount of immobilized mAb (0.01–0.1 mg/mL) are correlated with diffusion interaction parameters measured at two to three orders of magnitude higher antibody concentrations. The ability of SINS to rapidly screen mAb self-association in a microplate format using dilute mAb solutions makes it well suited for use in diverse settings ranging from antibody discovery to formulation.

The discovery of monoclonal antibodies (mAbs) that bind to a particular molecular target is now regarded a routine exercise. However, the successful development of mAbs that (1) express well, (2) elicit a desirable biological effect upon binding, and (3) remain soluble and display low viscosity at high concentrations is often far more challenging. Therefore, high throughput screening assays that assess self-association and aggregation early in the selection process are likely to yield mAbs with superior biophysical properties. Here, we report an improved version of affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS) that is capable of screening large panels of antibodies for their propensity to self-associate. AC-SINS is based on concentrating mAbs from dilute solutions around gold nanoparticles pre-coated with polyclonal capture (e.g., anti-Fc) antibodies. Interactions between immobilized mAbs lead to reduced inter-particle distances and increased plasmon wavelengths (wavelengths of maximum absorbance), which can be readily measured by optical means. This method is attractive because it is compatible with dilute and unpurified mAb solutions that are typical during early antibody discovery. In addition, we have improved multiple aspects of this assay for increased throughput and reproducibility. A data set comprising over 400 mAbs suggests that our modified assay yields self-interaction measurements that are well-correlated with other lower throughput assays such as cross-interaction chromatography. We expect that the simplicity and throughput of our improved AC-SINS method will lead to improved selection of mAbs with excellent biophysical properties during early antibody discovery.

Subcutaneous delivery of concentrated monoclonal antibodies (mAbs) is complicated by the propensity of mAbs to self-associate at elevated concentrations, which can lead to undesirable solution properties such as aggregation and abnormally high viscosity. Therefore, the selection of mAb candidates with low propensity to self-associate during early antibody discovery can significantly reduce challenges that may occur later during antibody development. However, it is difficult to use conventional biophysical methods for measuring weak mAb self-interactions during antibody discovery given the large number of antibody candidates as well as their low concentrations and purities. Nevertheless, significant progress has been made recently in adapting conventional biophysical methods as well as developing new ones for early identification of mAbs with low self-association propensities, which we highlight in this editorial. These advances should improve the selection of mAb candidates suitable for the extreme requirements of concentrated formulations necessary for subcutaneous delivery of therapeutic antibodies.

Therapeutic antibodies need to be highly resistant to aggregation due to the high concentrations required for subcutaneous delivery and the potential immunogenicity of antibody aggregates. Human antibody fragments-such as single-domain antibodies (VH or VL)-are typically much less soluble than full-length antibodies. Nevertheless, some aggregation-resistant VH domains have been discovered that are negatively charged at neutral pH and/or enriched in negatively charged residues within the complementarity-determining regions (CDRs). To better understand how to engineer diverse domain antibodies to resist aggregation, we have investigated the solubilizing activity of positively and negatively charged mutations within hydrophobic CDRs of multiple VH scaffolds that differ in their net charge. We find that negatively charged mutations inserted near the edges of hydrophobic CDRs are more effective than positively charged ones at inhibiting aggregation for VH scaffolds that are negatively or near-neutrally charged. In contrast, positively charged CDR mutations prevent aggregation better than negatively charged ones for a VH scaffold that is highly positively charged. Our findings suggest that the net charge of the antibody scaffold is a key determinant of the optimal CDR mutations for preventing aggregation. We expect that our findings will improve the design of aggregation-resistant antibodies with single- and multidomain scaffolds.

Amyloid protein aggregates are associated with dozens of devastating diseases including Alzheimer's, Parkinson's, ALS, and diabetes type 2. While structure-based discovery of compounds has been effective in combating numerous infectious and metabolic diseases, ignorance of amyloid structure has hindered similar approaches to amyloid disease. Here we show that knowledge of the atomic structure of one of the adhesive, steric-zipper segments of the amyloid-beta (Aβ) protein of Alzheimer's disease, when coupled with computational methods, identifies eight diverse but mainly flat compounds and three compound derivatives that reduce Aβ cytotoxicity against mammalian cells by up to 90%. Although these compounds bind to Aβ fibers, they do not reduce fiber formation of Aβ. Structure-activity relationship studies of the fiber-binding compounds and their derivatives suggest that compound binding increases fiber stability and decreases fiber toxicity, perhaps by shifting the equilibrium of Aβ from oligomers to fibers. DOI:http://dx.doi.org/10.7554/eLife.00857.001.

Monoclonal antibodies are attractive therapeutics for treating a wide range of human disorders due to their exquisite binding specificity and high binding affinity. However, a limitation of antibodies is their highly variable and difficult-to-predict propensities to aggregate when concentrated during purification and delivery. Despite the large size and complex structure of antibodies, recent findings suggest that antibody solubility can be dramatically improved using rational design methods in addition to conventional selection methods. Here, we review key advances and unmet challenges in engineering the variable and constant regions of antibody fragments and full-length antibodies to resist aggregation without reducing their binding affinity. These experimental and computational discoveries should accelerate the development of robust algorithms for designing aggregation-resistant antibodies.

Antibodies hold significant potential for inhibiting toxic protein aggregation associated with conformational disorders such as Alzheimer’s and Huntington’s diseases. However, near-stoichiometric antibody concentrations are typically required to completely inhibit protein aggregation. We posited that the molecular interactions mediating amyloid fibril formation could be harnessed to generate antibodies with potent antiaggregation. Here we report that grafting small amyloidogenic peptides (6–10 residues) into the complementarity-determining regions of a single-domain (V H ) antibody yields potent domain antibody inhibitors of amyloid formation. Grafted AMyloid-Motif AntiBODIES (gammabodies) presenting hydrophobic peptides from Aβ (Alzheimer’s disease), α-Synuclein (Parkinson's disease), and islet amyloid polypeptide (type 2 diabetes) inhibit fibril assembly of each corresponding polypeptide at low substoichiometric concentrations (1:10 gammabody:monomer molar ratio). In contrast, sequence- and conformation-specific antibodies that were obtained via immunization are unable to prevent fibrillization at the same substoichiometric concentrations. Gammabodies prevent amyloid formation by converting monomers and/or fibrillar intermediates into small complexes that are unstructured and benign. We expect that our antibody design approach—which eliminates the need for immunization or screening to identify sequence-specific domain antibody inhibitors—can be readily extended to generate potent aggregation inhibitors of other amyloidogenic polypeptides linked to human disease.

Antibodies commonly contain hydrophobic residues within their complementarity-determining regions (CDRs) that mediate binding to target antigens. Unfortunately, hydrophobic CDRs can also promote antibody aggregation, which is especially concerning for therapeutic antibodies due to the immunogenicity of antibody aggregates. Here we investigate how the sequences of CDRs within single-domain (V(H)) antibodies specific for the Alzheimer's amyloid β peptide can be engineered to resist aggregation without reducing binding affinity. We find that domain antibodies containing clusters of hydrophobic residues within their third CDR (CDR3) are prone to aggregate within days at 25°C and minutes above 70°C. However, inserting two or more negatively charged residues at each edge of CDR3 potently suppresses antibody aggregation without altering binding affinity. We also find that inserting charged mutations at one edge of CDR3 (N- or C-terminal) prevents aggregation, but only if such mutations are located at the edge closest to most hydrophobic portion of CDR3. In contrast, charged mutations outside of CDR3 fail to suppress aggregation. Our findings demonstrate that the sequence of CDR loops can be engineered in a systematic manner to improve antibody solubility without altering binding affinity or specificity.

High-affinity antibodies are critical for numerous diagnostic and therapeutic applications, yet their utility is limited by their variable propensity to aggregate either at low concentrations for antibody fragments or high concentrations for full-length antibodies. Therefore, determining the sequence and structural features that differentiate aggregation-resistant antibodies from aggregation-prone ones is critical to improving their activity. We have investigated the molecular origins of antibody aggregation for human V(H) domain antibodies that differ only in the sequence of the loops containing their complementarity determining regions (CDRs), yet such antibodies possess dramatically different aggregation propensities in a manner not correlated with their conformational stabilities. We find the propensity of these antibodies to aggregate after being transiently unfolded is not a distributed property of the CDR loops, but can be localized to aggregation hotspots within and near the first CDR (CDR1). Moreover, we have identified a triad of charged mutations within CDR1 and a single charged mutation adjacent to CDR1 that endow the poorly soluble variant with the desirable biophysical properties of the aggregation-resistant antibody. Importantly, we find that several other charged mutations in CDR1, non-CDR loops and the antibody scaffold are incapable of preventing aggregation. We expect that our identification of aggregation hotspots that govern antibody aggregation within and proximal to CDR loops will guide the design and selection of antibodies that not only possess high affinity and conformational stability, but also extreme resistance to aggregation.