Multiparatopic antibodies induce targeted downregulation of programmed death-ligand 1.

Programmed death-ligand 1 (PD-L1) drives inhibition of antigen-specific T cell responses through engagement of its receptor programmed death-1 (PD-1) on activated T cells. Overexpression of these immune checkpoint proteins in the tumor microenvironment has motivated the design of targeted antibodies that disrupt this interaction. Despite clinical success of these antibodies, response rates remain low, necessitating novel approaches to enhance performance. Here, we report the development of antibody fusion proteins that block immune checkpoint pathways through a distinct mechanism targeting molecular trafficking. By engaging multiple receptor epitopes on PD-L1, our engineered multiparatopic antibodies induce rapid clustering, internalization, and degradation in an epitope- and topology-dependent manner. The complementary mechanisms of ligand blockade and receptor downregulation led to more durable immune cell activation and dramatically reduced PD-L1 availability in mouse tumors. Collectively, these multiparatopic antibodies offer mechanistic insight into immune checkpoint protein trafficking and how it may be manipulated to reprogram immune outcomes.

Poly(Beta-Amino Ester)s as High-Yield Transfection Reagents for Recombinant Protein Production.

Purpose: Transient transfection is an essential tool for recombinant protein production, as it allows rapid screening for expression without stable integration of genetic material into a target cell genome. Poly(ethylenimine) (PEI) is the current gold standard for transient gene transfer, but transfection efficiency and the resulting protein yield are limited by the polymer's toxicity. This study investigated the use of a class of cationic polymers, poly(beta-amino ester)s (PBAEs), as reagents for transient transfection in comparison to linear 25 kDa PEI, a commonly used transfection reagent. Methods: Transfection efficiency and protein production were assessed in human embryonic kidney 293F (HEK) and Chinese hamster ovary-S (CHO) cell suspensions using PBAE-based nanoparticles in comparison to linear 25 kDa PEI. Production of both a cytosolic reporter and secreted antibodies was investigated. Results: In both HEK and CHO cells, several PBAEs demonstrated superior transfection efficiency and enhanced production of a cytosolic reporter compared to linear 25 kDa PEI. This result extended to secreted proteins, as a model PBAE increased the production of 3 different secreted antibodies compared to linear 25 kDa PEI at culture scales ranging from 20 to 2000 mL. In particular, non-viral gene transfer using the lead PBAE/plasmid DNA nanoparticle formulation led to robust transfection of mammalian cells across different constructs, doses, volumes, and cell types. Conclusion: These results show that PBAEs enhance transfection efficiency and increase protein yield compared to a widespread commercially available reagent, making them attractive candidates as reagents for use in recombinant protein production.

A versatile design platform for glycoengineering therapeutic antibodies.

Manipulation of glycosylation patterns, i.e., glycoengineering, is incorporated in the therapeutic antibody development workflow to ensure clinical safety, and this approach has also been used to modulate the biological activities, functions, or pharmacological properties of antibody drugs. Whereas most existing glycoengineering strategies focus on the canonical glycans found in the constant domain of immunoglobulin G (IgG) antibodies, we report a new strategy to leverage the untapped potential of atypical glycosylation patterns in the variable domains, which naturally occur in 15% to 25% of IgG antibodies. Glycosylation sites were added to the antigen-binding regions of two functionally divergent, interleukin-2-binding monoclonal antibodies. We used computational tools to rationally install various N-glycosylation consensus sequences into the antibody variable domains, creating "glycovariants" of these molecules. Strikingly, almost all the glycovariants were successfully glycosylated at their newly installed N-glycan sites, without reduction of the antibody's native function. Importantly, certain glycovariants exhibited modified activities compared to the parent antibody, showing the potential of our glycoengineering strategy to modulate biological function of antibodies involved in multi-component receptor systems. Finally, when coupled with a high-flux sialic acid precursor, a glycovariant with two installed glycosylation sites demonstrated superior in vivo half-life. Collectively, these findings validate a versatile glycoengineering strategy that introduces atypical glycosylation into therapeutic antibodies in order to improve their efficacy and, in certain instances, modulate their activity early in the drug development process.

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.

Emerging technologies in protein interface engineering for biomedical applications.

Protein interactions communicate critical information from the environment into cells to orchestrate functional responses relevant to health and disease. Whereas the natural repertoire of protein interfaces is finite, biomolecular engineering tools provide access to an unlimited scope of potential interactions that can be custom-designed for affinity, specificity, mechanism, or other properties of interest. This review highlights recent developments in protein interface engineering that offer insight into human physiology to inform the design of new pharmaceuticals, with a particular focus on immunotherapeutics. We cover three innovative and translationally promising approaches: (1) reprogramming receptor oligomerization to manipulate signaling pathways; (2) computational protein interface design strategies; and (3) engineering bioorthogonal protein interaction networks.

Net charge of antibody complementarity-determining regions is a key predictor of specificity.

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.

Biophysical and Sequence-Based Methods for Identifying Monovalent and Bivalent Antibodies with High Colloidal Stability.

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.

Facile Affinity Maturation of Antibody Variable Domains Using Natural Diversity Mutagenesis.

The identification of mutations that enhance antibody affinity while maintaining high antibody specificity and stability is a time-consuming and laborious process. Here, we report an efficient methodology for systematically and rapidly enhancing the affinity of antibody variable domains while maximizing specificity and stability using novel synthetic antibody libraries. Our approach first uses computational and experimental alanine scanning mutagenesis to identify sites in the complementarity-determining regions (CDRs) that are permissive to mutagenesis while maintaining antigen binding. Next, we mutagenize the most permissive CDR positions using degenerate codons to encode wild-type residues and a small number of the most frequently occurring residues at each CDR position based on natural antibody diversity. This mutagenesis approach results in antibody libraries with variants that have a wide range of numbers of CDR mutations, including antibody domains with single mutations and others with tens of mutations. Finally, we sort the modest size libraries (~10 million variants) displayed on the surface of yeast to identify CDR mutations with the greatest increases in affinity. Importantly, we find that single-domain (VHH) antibodies specific for the α-synuclein protein (whose aggregation is associated with Parkinson's disease) with the greatest gains in affinity (>5-fold) have several (four to six) CDR mutations. This finding highlights the importance of sampling combinations of CDR mutations during the first step of affinity maturation to maximize the efficiency of the process. Interestingly, we find that some natural diversity mutations simultaneously enhance all three key antibody properties (affinity, specificity, and stability) while other mutations enhance some of these properties (e.g., increased specificity) and display trade-offs in others (e.g., reduced affinity and/or stability). Computational modeling reveals that improvements in affinity are generally not due to direct interactions involving CDR mutations but rather due to indirect effects that enhance existing interactions and/or promote new interactions between the antigen and wild-type CDR residues. We expect that natural diversity mutagenesis will be useful for efficient affinity maturation of a wide range of antibody fragments and full-length antibodies.