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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.

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.

Monoclonal antibodies are attractive therapeutic agents because of their impressive biological activities and favorable biophysical properties. Nevertheless, antibodies are susceptible to various types of chemical modifications, and the impact of such modifications on antibody physical stability and aggregation remains understudied. Here, we report a systematic analysis of the impact of methionine oxidation, tryptophan oxidation, and asparagine deamidation on antibody conformational and colloidal stability, hydrophobicity, solubility, and aggregation. Interestingly, we find little correlation between the impact of these chemical modifications on antibody conformational stability and aggregation. Methionine oxidation leads to significant reductions in antibody conformational stability while having little impact on antibody aggregation except at extreme conditions (low pH and elevated temperature). Conversely, tryptophan oxidation and asparagine deamidation have little impact on antibody conformational stability while promoting aggregation at a wide range of solution conditions, and the aggregation mechanisms appear linked to unique types of reducible and nonreducible covalent crosslinks and, in some cases, to increased levels of attractive colloidal interactions. These findings highlight that even related types of chemical modifications can lead to dissimilar antibody aggregation mechanisms, and evaluating these findings for additional antibodies will be important for improving the systematic generation of antibodies with high chemical and physical stability.

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.

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.

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.

There is widespread interest in facile methods for generating potent neutralizing antibodies, nanobodies, and other affinity proteins against SARS-CoV-2 and related viruses to address current and future pandemics. While isolating antibodies from animals and humans are proven approaches, these methods are limited to the affinities, specificities, and functional activities of antibodies generated by the immune system. Here we report a surprisingly simple directed evolution method for generating nanobodies with high affinities and neutralization activities against SARS-CoV-2. We demonstrate that complementarity-determining region swapping between low-affinity lead nanobodies, which we discovered unintentionally but find is simple to implement systematically, results in matured nanobodies with unusually large increases in affinity. Importantly, the matured nanobodies potently neutralize both SARS-CoV-2 pseudovirus and live virus, and possess drug-like biophysical properties. We expect that our methods will improve in vitro nanobody discovery and accelerate the generation of potent neutralizing nanobodies against diverse coronaviruses., Graphical abstract, Zupancic et al. report potent neutralizing nanobodies against SARS-CoV-2. They demonstrate an approach that involves swapping the complementarity-determining regions of low-affinity clones to generate matured nanobodies with large increases in affinity and neutralization activity.

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.

Tau aggregates into paired helical filaments within neurons, a pathological hallmark of Alzheimer's disease. Heparin promotes tau aggregation and recently has been shown to be involved in the cellular uptake of tau aggregates. Although the tau-heparin interaction has been extensively studied, little is known about the glycan determinants of this interaction. Here, we used surface plasmon resonance (SPR) and NMR spectroscopy to characterize the interaction between two tau fragments, K18 and K19, and several polysaccharides, including heparin, heparin oligosaccharides, chemically modified heparin, and related glycans. Using a heparin-immobilized chip, SPR revealed that tau K18 and K19 bind heparin with a K-D of 0.2 and 70 mu M, respectively. In SPR competition experiments, N-desulfation and 2-O-desulfation had no effect on heparin binding to K18, whereas 6-O-desulfation severely reduced binding, suggesting a critical role for 6-O-sulfation in the tau-heparin interaction. The tau-heparin interaction became stronger with longer-chain heparin oligosaccharides. As expected for an electrostatics-driven interaction, a moderate amount of salt (0.3 M NaCl) abolished binding. NMR showed the largest chemical-shift perturbation (CSP) in R2 in tau K18, which was absent in K19, revealing differential binding sites in K18 and K19 to heparin. Dermatan sulfate binding produced minimal CSP, whereas dermatan disulfate, with the additional 6-O-sulfo group, induced much larger CSP. 2-O-desulfated heparin induced much larger CSP in K18 than 6-O-desulfated heparin. Our data demonstrate a crucial role for the 6-O-sulfo group in the tau-heparin interaction, which to our knowledge has not been reported before.

Background The prevalence of high fat diets (HFD), diet-induced obesity (DIO) and Type 2 diabetes continues to increase, associated with cognitive impairment in both humans and rodent models. Mechanisms transducing these impairments remain largely unknown: one possibility is that a common mechanism may be involved in the cognitive impairment seen in obese and/or diabetic states and in dementia, specifically Alzheimer's disease (AD). DIO is well established as a risk factor for development of AD. Oligomeric amyloid-β (Aβ) is neurotoxic, and we showed that intrahippocampal oligomeric Aβ produces cognitive and metabolic dysfunction similar to that seen in DIO or diabetes. Moreover, animal models of DIO show elevated brain Aβ, a hallmark of AD, suggesting that this may be one source of cognitive impairment in both conditions. Methods Intrahippocampal administration of a novel anti-Aβ domain antibody for aggregated Aβ, or a control domain antibody, to control or HFD-induced DIO rats. Spatial learning measured in a conditioned contextual fear (CCF) task after domain antibody treatment; postmortem, hippocampal NMDAR and AMPAR were measured. Results DIO caused impairment in CCF, and this impairment was eliminated by intrahippocampal administration of the active domain antibody. Measurement of hippocampal proteins suggests that DIO causes dysregulation of hippocampal AMPA receptors, which is also reversed by acute domain antibody administration. Conclusions Our findings support the concept that oligomeric Aβ within the hippocampus of DIO animals may not only be a risk factor for development of AD but may also cause cognitive impairment before the development of dementia. General Significance and Interest Our work integrates the engineering of domain antibodies with conformational- and sequence-specificity for oligomeric amyloid beta with a clinically relevant model of diet-induced obesity in order to demonstrate not only the pervasive effects of obesity on several aspects of brain biochemistry and behavior, but also the bioengineering of a successful treatment against the long-term detrimental effects of a pre-diabetic state on the brain. We show for the first time that cognitive impairment linked to obesity and/or insulin resistance may be due to early accumulation of oligomeric beta-amyloid in the brain, and hence may represent a pre-Alzheimer's state.

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 (