Profiling the Biophysical Developability Properties of Common IgG1 Fc Effector Silencing Variants.

Therapeutic antibodies represent the most significant modality in biologics, with around 150 approved drugs on the market. In addition to specific target binding mediated by the variable fragments (Fvs) of the heavy and light chains, antibodies possess effector functions through binding of the constant region (Fc) to Fcγ receptors (FcγR), which allow immune cells to attack and kill target cells using a variety of mechanisms. However, for some applications, including T-cell-engaging bispecifics, this effector function is typically undesired. Mutations within the lower hinge and the second constant domain (CH2) of IgG1 that comprise the FcγR binding interface reduce or eliminate effector function ("Fc silencing") while retaining binding to the neonatal Fc receptor (FcRn), important for normal antibody pharmacokinetics (PKs). Comprehensive profiling of biophysical developability properties would benefit the choice of constant region variants for development. Here, we produce a large panel of representative mutations previously described in the literature and in many cases in clinical or approved molecules, generate select combinations thereof, and characterize their binding and biophysical properties. We find that some commonly used CH2 mutations, including D265A and P331S, are effective in reducing binding to FcγR but significantly reduce stability, promoting aggregation, particularly under acidic conditions commonly employed in manufacturing. We highlight mutation sets that are particularly effective for eliminating Fc effector function with the retention of WT-like stability, including L234A, L235A, and S267K (LALA-S267K), L234A, L235E, and S267K (LALE-S267K), L234A, L235A, and P329A (LALA-P329A), and L234A, L235E, and P329G (LALE-P329G).

Identifying developability risks for clinical progression of antibodies using high-throughput in vitro and in silico approaches.

With the growing significance of antibodies as a therapeutic class, identifying developability risks early during development is of paramount importance. Several high-throughput in vitro assays and in silico approaches have been proposed to de-risk antibodies during early stages of the discovery process. In this review, we have compiled and collectively analyzed published experimental assessments and computational metrics for clinical antibodies. We show that flags assigned based on in vitro measurements of polyspecificity and hydrophobicity are more predictive of clinical progression than their in silico counterparts. Additionally, we assessed the performance of published models for developability predictions on molecules not used during model training. We find that generalization to data outside of those used for training remains a challenge for models. Finally, we highlight the challenges of reproducibility in computed metrics arising from differences in homology modeling, in vitro assessments relying on complex reagents, as well as curation of experimental data often used to assess the utility of high-throughput approaches. We end with a recommendation to enable assay reproducibility by inclusion of controls with disclosed sequences, as well as sharing of structural models to enable the critical assessment and improvement of in silico predictions.

Antibody-mediated protection against symptomatic COVID-19 can be achieved at low serum neutralizing titers.

Multiple studies of vaccinated and convalescent cohorts have demonstrated that serum neutralizing antibody (nAb) titers correlate with protection against coronavirus disease 2019 (COVID-19). However, the induction of multiple layers of immunity after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure has complicated the establishment of nAbs as a mechanistic correlate of protection (CoP) and hindered the definition of a protective nAb threshold. Here, we show that a half-life-extended monoclonal antibody (adintrevimab) provides about 50% protection against symptomatic COVID-19 in SARS-CoV-2-naïve adults at serum nAb titers on the order of 1:30. Vaccine modeling results support a similar 50% protective nAb threshold, suggesting that low titers of serum nAbs protect in both passive antibody prophylaxis and vaccination settings. Extrapolation of adintrevimab pharmacokinetic data suggests that protection against susceptible variants could be maintained for about 3 years. The results provide a benchmark for the selection of next-generation vaccine candidates and support the use of broad, long-acting monoclonal antibodies as alternatives or supplements to vaccination in high-risk populations.

Antibody-mediated protection against symptomatic COVID-19 can be achieved at low serum neutralizing titers.

Multiple studies of vaccinated and convalescent cohorts have demonstrated that serum neutralizing antibody (nAb) titers correlate with protection against COVID-19. However, the induction of multiple layers of immunity following SARS-CoV-2 exposure has complicated the establishment of nAbs as a mechanistic correlate of protection (CoP) and hindered the definition of a protective nAb threshold. Here, we show that a half-life extended monoclonal antibody (adintrevimab) provides approximately 50% protection against symptomatic COVID-19 in SARS-CoV-2-naive adults at low serum nAb titers on the order of 1:30. Vaccine modeling supports a similar 50% protective nAb threshold, suggesting low levels of serum nAb can protect in both monoclonal and polyclonal settings. Extrapolation of adintrevimab pharmacokinetic data suggests that protection against susceptible variants could be maintained for approximately 3 years. The results provide a benchmark for the selection of next-generation vaccine candidates and support the use of broad, long-acting monoclonal antibodies as an alternative or supplement to vaccination in high-risk populations.

Assessing the binding properties of the anti-PD-1 antibody landscape using label-free biosensors.

Here we describe an industry-wide collaboration aimed at assessing the binding properties of a comprehensive panel of monoclonal antibodies (mAbs) against programmed cell death protein 1 (PD-1), an important checkpoint protein in cancer immunotherapy and validated therapeutic target, with well over thirty unique mAbs either in clinical development or market-approved in the United States, the European Union or China. The binding kinetics of the PD-1/mAb interactions were measured by surface plasmon resonance (SPR) using a Carterra LSA instrument and the results were compared to data collected on a Biacore 8K. The effect of chip type on the SPR-derived binding rate constants and affinities were explored and the results compared with solution affinities from Meso Scale Discovery (MSD) and Kinetic Exclusion Assay (KinExA) experiments. When using flat chip types, the LSA and 8K platforms yielded near-identical kinetic rate and affinity constants that matched solution phase values more closely than those produced on 3D-hydrogels. Of the anti-PD-1 mAbs tested, which included a portion of those known to be in clinical development or approved, the affinities spanned from single digit picomolar to nearly 425 nM, challenging the dynamic range of our methods. The LSA instrument was also used to perform epitope binning and ligand competition studies which revealed over ten unique competitive binding profiles within this group of mAbs.

The uniqueness of flow in probing the aggregation behavior of clinically relevant antibodies.

The development of therapeutic monoclonal antibodies (mAbs) can be hindered by their tendency to aggregate throughout their lifetime, which can illicit immunogenic responses and render mAb manufacturing unfeasible. Consequently, there is a need to identify mAbs with desirable thermodynamic stability, solubility, and lack of self-association. These behaviors are assessed using an array of in silico and in vitro assays, as no single assay can predict aggregation and developability. We have developed an extensional and shear flow device (EFD), which subjects proteins to defined hydrodynamic forces which mimic those experienced in bioprocessing. Here, we utilize the EFD to explore the aggregation propensity of 33 IgG1 mAbs, whose variable domains are derived from clinical antibodies. Using submilligram quantities of material per replicate, wide-ranging EFD-induced aggregation (9-81% protein in pellet) was observed for these mAbs, highlighting the EFD as a sensitive method to assess aggregation propensity. By comparing the EFD-induced aggregation data to those obtained previously from 12 other biophysical assays, we show that the EFD provides distinct information compared with current measures of adverse biophysical behavior. Assessing a candidate's liability to hydrodynamic force thus adds novel insight into the rational selection of developable mAbs that complements other assays.

Connecting the sequence dots: shedding light on the genesis of antibodies reported to be designed in silico.

Two recent publications out of the same research laboratory report on structure-based in silico design of antibodies against viral targets without sequence disclosure. Cross-referencing the published data to patent databases, we established the sequence identity of said computationally designed antibodies. In both cases, the antibodies align with high sequence identity to previously reported antibodies of the same specificity. This clear underlying sequence relationship, which is far closer than the antibody templates reported to seed the computational design, suggests an alternative origin of the computationally designed antibodies. The lack of both reproducible computational algorithms and of output sequences in the initial publications obscures the relationship to previously reported antibodies, and sows doubt as to the genesis narrative described therein.

Deamidation and isomerization liability analysis of 131 clinical-stage antibodies.

Contemporary in vivo and in vitro discovery platform technologies greatly increase the odds of identifying high-affinity monoclonal antibodies (mAbs) towards essentially any desired biologically relevant epitope. Lagging discovery throughput is the ability to select for highly developable mAbs with drug-like properties early in the process. Upstream consideration of developability metrics should reduce the frequency of failures in later development stages. As the field moves towards incorporating biophysical screening assays in parallel to discovery processes, similar approaches should also be used to ensure robust chemical stability. Optimization of chemical stability in the early stages of discovery has the potential to reduce complications in formulation development and improve the potential for successful liquid formulations. However, at present, our knowledge of the chemical stability characteristics of clinical-stage therapeutic mAbs is fragmented and lacks comprehensive comparative assessment. To address this knowledge gap, we produced 131 mAbs with amino acid sequences corresponding to the variable regions of clinical-stage mAbs, subjected these to low and high pH stresses and identified the resulting modifications at amino acid-level resolution via tryptic peptide mapping. Among this large set of mAbs, relatively high frequencies of asparagine deamidation events were observed in CDRs H2 and L1, while CDRs H3, H2 and L1 contained relatively high frequencies of instances of aspartate isomerization.

Prediction of delayed retention of antibodies in hydrophobic interaction chromatography from sequence using machine learning.

MOTIVATION: The hydrophobicity of a monoclonal antibody is an important biophysical property relevant for its developability into a therapeutic. In addition to characterizing heterogeneity, Hydrophobic Interaction Chromatography (HIC) is an assay that is often used to quantify the hydrophobicity of an antibody to assess downstream risks. Earlier studies have shown that retention times in this assay can be correlated to amino-acid or atomic propensities weighted by the surface areas obtained from protein 3-dimensional structures. The goal of this study is to develop models to enable prediction of delayed HIC retention times directly from sequence. RESULTS: We utilize the randomforest machine learning approach to estimate the surface exposure of amino-acid side-chains in the variable region directly from the antibody sequence. We obtain mean-absolute errors of 4.6% for the prediction of surface exposure. Using experimental HIC data along with the estimated surface areas, we derive an amino-acid propensity scale that enables prediction of antibodies likely to have delayed retention times in the assay. We achieve a cross-validation Area Under Curve of 0.85 for the Receiver Operating Characteristic curve of our model. The low computational expense and high accuracy of this approach enables real-time assessment of hydrophobic character to enable prioritization of antibodies during the discovery process and rational engineering to reduce hydrophobic liabilities. AVAILABILITY AND IMPLEMENTATION: Structure data, aligned sequences, experimental data and prediction scores for test-cases, and R scripts used in this work are provided as part of the Supplementary Material. CONTACT: tushar.jain@adimab.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Biophysical properties of the clinical-stage antibody landscape.

Antibodies are a highly successful class of biological drugs, with over 50 such molecules approved for therapeutic use and hundreds more currently in clinical development. Improvements in technology for the discovery and optimization of high-potency antibodies have greatly increased the chances for finding binding molecules with desired biological properties; however, achieving drug-like properties at the same time is an additional requirement that is receiving increased attention. In this work, we attempt to quantify the historical limits of acceptability for multiple biophysical metrics of "developability." Amino acid sequences from 137 antibodies in advanced clinical stages, including 48 approved for therapeutic use, were collected and used to construct isotype-matched IgG1 antibodies, which were then expressed in mammalian cells. The resulting material for each source antibody was evaluated in a dozen biophysical property assays. The distributions of the observed metrics are used to empirically define boundaries of drug-like behavior that can represent practical guidelines for future antibody drug candidates.

Broad epitope coverage of a human in vitro antibody library.

Successful discovery of therapeutic antibodies hinges on the identification of appropriate affinity binders targeting a diversity of molecular epitopes presented by the antigen. Antibody campaigns that yield such broad "epitope coverage" increase the likelihood of identifying candidates with the desired biological functions. Accordingly, epitope binning assays are employed in the early discovery stages to partition antibodies into epitope families or "bins" and prioritize leads for further characterization and optimization. The collaborative program described here, which used hen egg white lysozyme (HEL) as a model antigen, combined 3 key capabilities: 1) access to a diverse panel of antibodies selected from a human in vitro antibody library; 2) application of state-of-the-art high-throughput epitope binning; and 3) analysis and interpretation of the epitope binning data with reference to an exhaustive set of published antibody:HEL co-crystal structures. Binning experiments on a large merged panel of antibodies containing clones from the library and the literature revealed that the inferred epitopes for the library clones overlapped with, and extended beyond, the known structural epitopes. Our analysis revealed that nearly the entire solvent-exposed surface of HEL is antigenic, as has been proposed for protein antigens in general. The data further demonstrated that synthetic antibody repertoires provide as wide epitope coverage as those obtained from animal immunizations. The work highlights molecular insights contributed by increasingly higher-throughput binning methods and their broad utility to guide the discovery of therapeutic antibodies representing a diverse set of functional epitopes.

High throughput cross-interaction measures for human IgG1 antibodies correlate with clearance rates in mice.

Although improvements in technology for the isolation of potential therapeutic antibodies have made the process increasingly predictable, the development of biologically active monoclonal antibodies (mAbs) into drugs can often be impeded by developability issues such as poor expression, solubility, and promiscuous cross-reactivity. Establishing early stage developability screening assays capable of predicting late stage behavior is therefore of high value to minimize development risks. Toward this goal, we selected a panel of 16 monoclonal antibodies (mAbs) representing different developability profiles, in terms of self- and cross-interaction propensity, and examined their downstream behavior from expression titer to accelerated stability and pharmacokinetics in mice. Clearance rates showed significant rank-order correlations to 2 cross-interaction related assays, with the closest correlation to a non-specificity assay on the surface of yeast. Additionally, 2 self-association assays correlated with each other but not to mouse clearance rate. This case study suggests that combining assays capable of high throughput screening of self- and cross-interaction early in the discovery stage could significantly lower downstream development risks.

An alternative assay to hydrophobic interaction chromatography for high-throughput characterization of monoclonal antibodies.

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.

High-throughput screening for developability during early-stage antibody discovery using self-interaction nanoparticle spectroscopy.

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.

Addressing polyspecificity of antibodies selected from an in vitro yeast presentation system: a FACS-based, high-throughput selection and analytical tool.

Low expression, poor solubility, and polyspecificity are significant obstacles that have impeded the development of antibodies discovered from in vitro display libraries. Current biophysical characterization tools that identify these 'developability' problems are typically only applied after the discovery process, and thus limited to perhaps a few hundred candidates. We report a flow cytometric assay using a polyspecificity reagent (PSR) that allows for the identification and counter selection of polyspecific antibodies both during and after the selection process. The reported assay correlates well with cross-interaction chromatography, a surrogate for antibody solubility, as well as a baculovirus particle enzyme-linked immunosorbent assay, a surrogate for in vivo clearance. However, unlike these assays, PSR labeling is compatible both with screening of individual antibodies as well as selections of large antibody libraries. To this end, we demonstrate the ability to counter-select against polyspecificity while enriching for antigen affinity from a diverse antibody library, which enables simultaneous evolution of both antigen binding and superior non-target-related properties during the discovery process.

Coordinate expression and functional profiling identify an extracellular proteolytic signaling pathway.

A multidisciplinary method combining transcriptional data, specificity profiling, and biological characterization of an enzyme may be used to predict novel substrates. By integrating protease substrate profiling with microarray gene coexpression data from nearly 2,000 human normal and cancerous tissue samples, three fundamental components of a protease-activated signaling pathway were identified. We find that MT-SP1 mediates extracellular signaling by regulating the local activation of the prometastatic growth factor MSP-1. We demonstrate MT-SP1 expression in peritoneal macrophages, and biochemical methods confirm the ability of MT-SP1 to cleave and activate pro-MSP-1 in vitro and in a cellular context. MT-SP1 induced the ability of MSP-1 to inhibit nitric oxide production in bone marrow macrophages. Addition of HAI-1 or an MT-SP1-specific antibody inhibitor blocked the proteolytic activation of MSP-1 at the cell surface of peritoneal macrophages. Taken together, our work indicates that MT-SP1 is sufficient for MSP-1 activation and that MT-SP1, MSP-1, and the previously shown MSP-1 tyrosine kinase receptor RON are required for peritoneal macrophage activation. This work shows that this triad of growth factor, growth factor activator protease, and growth factor receptor is a protease-activated signaling pathway. Individually, MT-SP1 and RON overexpression have been implicated in cancer progression and metastasis. Transcriptional coexpression of these genes suggests that this signaling pathway may be involved in several human cancers.

Three-dimensional structures of a humanized anti-IFN-gamma Fab (HuZAF) in two crystal forms.

Three-dimensional structures were determined for two crystal forms (orthorhombic P2(1)2(1)2(1) and monoclinic C2) of the Fab from the humanized version of a murine monoclonal antibody (AF2) that possesses binding and potent neutralizing activity against human interferon gamma (IFN-gamma). This humanized antibody (HuZAF; USAN name fontolizumab) is currently in phase II clinical trials for the treatment of Crohn's disease. HuZAF exhibits binding and IFN-gamma neutralizing capacities that closely approximate those of the original antibody. It is shown that HuZAF, whose VH domain was designed using a best-sequence-fit approach, is closer structurally to its mouse precursor than is a version whose VH was constructed using a human sequence with lower homology to the original mouse sequence. This work thus offers direct structural evidence in support of the best-sequence-fit approach and adds to previous results of biological and biochemical evaluations of distinctly engineered antibodies that also favored the use of a best-sequence-fit strategy. A second crystal type appeared during attempts to crystallize the Fab-IFN-gamma complex. The antibody-antigen complex that existed in solution dissociated in the crystallization mixture. A conformationally altered but unliganded HuZAF protein crystallized in a different space group (C2), with two Fab molecules in the asymmetric unit. In this crystal lattice, no space was available for accommodating the IFN-gamma antigen. Thus, there are currently three slightly different structures of the HuZAF Fab.

Development of humanized monoclonal antibody TMA-15 which neutralizes Shiga toxin 2.

A murine monoclonal antibody (MAb), VTm1.1, specifically recognizing and neutralizing Shiga toxin 2 (Stx2), was obtained. To prevent a humoral response against murine antibody when used clinically, a humanized antibody was constructed by combining the complementarity-determining regions of VTm1.1 with human framework and constant regions. In addition, several amino acids in the framework were changed to improve the binding affinity of the antibody and further reduce its potential immunogenicity. The humanized antibody, TMA-15, recognized the B-subunit of Stx2 and had affinity for Stx2 of 3.3 x 10(-9) M, within two-fold of that of the original murine antibody. TMA-15 neutralized the cytotoxicity of Stx2 and several different Stx2 variants in vitro, and it completely protected mice from death in a Stx2-challenged mice model. These results suggest that TMA-15 will have clinical potency in Stx-producing Escherichia coli infections, including E. coli O157 infections.