Improving monoclonal antibody selection and engineering using measurements of colloidal protein interactions

Computational Screening for mAb Colloidal Stability with Coarse-Grained, Molecular-Scale Simulations

Monoclonal antibodies (mAbs) are an important modality of protein therapeutics with broad applications for numerous diseases. However, colloidal instabilities occurring at high protein concentrations can limit the ability to develop stable, high-concentration liquid dosage forms that are required for patient-centric, device-mediated products. Therefore, it is advantageous to identify colloidally stable mAbs early in the discovery process to ensure that they are selected for development. Experimental screening for colloidal stability can be time- and resource-consuming and is most feasible at the later stages of drug development due to material requirements. Alternatively, computational approaches have emerging potential to provide efficient screening and focus developmental efforts on mAbs with the greatest developability potential, while providing mechanistic relationships for colloidal instability. In this work, coarse-grained, molecular-scale models were fine-tuned to screen for colloidal stability at amino-acid resolution. This model parameterization provides a framework to screen for mAb self-interactions and extrapolate to bulk solution behavior. This approach was applied to a wide array of mAbs under multiple buffer conditions, demonstrating the utility of the presented computational approach to augment early candidate screening and later formulation strategies for protein therapeutics.

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies

Biologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration-time curve (AUC0-672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL.

Developability assessment at early-stage discovery to enable development of antibody-derived therapeutics

Developability refers to the likelihood that an antibody candidate will become a manufacturable, safe and efficacious drug. Although the safety and efficacy of a drug candidate will be well considered by sponsors and regulatory agencies, developability in the narrow sense can be defined as the likelihood that an antibody candidate will go smoothly through the chemistry, manufacturing and control (CMC) process at a reasonable cost and within a reasonable timeline. Developability in this sense is the focus of this review. To lower the risk that an antibody candidate with poor developability will move to the CMC stage, the candidate's developability-related properties should be screened, assessed and optimized as early as possible. Assessment of developability at the early discovery stage should be performed in a rapid and high-throughput manner while consuming small amounts of testing materials. In addition to monoclonal antibodies, bispecific antibodies, multispecific antibodies and antibody-drug conjugates, as the derivatives of monoclonal antibodies, should also be assessed for developability. Moreover, we propose that the criterion of developability is relative: expected clinical indication, and the dosage and administration route of the antibody could affect this criterion. We also recommend a general screening process during the early discovery stage of antibody-derived therapeutics. With the advance of artificial intelligence-aided prediction of protein structures and features, computational tools can be used to predict, screen and optimize the developability of antibody candidates and greatly reduce the risk of moving a suboptimal candidate to the development stage.

Predicting Experimental B22 Values and the Effects of Histidine Charge States for Monoclonal Antibodies Using Coarse-Grained Molecular Simulations

Static light scattering (SLS) was used to characterize five monoclonal antibodies (MAbs) as a function of total ionic strength (TIS) at pH values between 5.5 and 7.0. Second osmotic virial coefficient (B₂₂) values were determined experimentally for each MAb as a function of TIS using low protein concentration SLS data. Coarse-grained molecular simulations were performed to predict the B₂₂ values for each MAb at a given pH and TIS. To include the effect of charge fluctuations of titratable residues in the B₂₂ calculations, a statistical approach was introduced in the Monte Carlo algorithm based on the protonation probability based on a given pH value and the Henderson-Hasselbalch equation. The charged residues were allowed to fluctuate individually, based on the sampled microstates and the influence of electrostatic interactions on net protein-protein interactions during the simulations. Compared to static charge simulations, the new approach provided improved results compared to experimental B₂₂ values at pH conditions near the pK_a of titratable residues.

Utility of High Resolution 2D NMR Fingerprinting in Assessing Viscosity of Therapeutic Monoclonal Antibodies

Purpose

The viscosity of highly concentrated therapeutic monoclonal antibody (mAb) formulations at concentrations ≥ 100 mg/mL can significantly affect the stability, processing, and drug product development for subcutaneous delivery. An early identification of a viscosity prone mAb during candidate selection stages are often beneficial for downstream processes. Higher order structure of mAbs may often dictate their viscosity behavior at high concentration. Thus it is beneficial to gauge or rank-order their viscosity behavior using noninvasive structural fingerprinting methods and to potentially screen for suitable viscosity lowering excipients.

Methods

In this study, Dynamic Light Scattering (DLS) and 2D NMR based methyl fingerprinting were used to correlate viscosity behavior of a set of Pfizer mAbs. The viscosities of mAbs were determined. Respective Fab and Fc domains were generated for studies.

Result

Methyl fingerprinting of intact mAbs allows for differentiation of viscosity prone mAbs from well behaved ones even at 30–40 mg/ml, where bulk viscosity of the solutions are near identical. For viscosity prone mAbs, peak broadening and or distinct chemical shift changes were noted in intact and fragment fingerprints, unlike the well-behaved mAbs, indicative of protein protein interactions (PPI).

Conclusion

Fab-Fab or Fab-Fc interactions may lead to formation of protein networks at high concentration. The early transients to these network formation may be manifested through peak broadening or peak shift in the 2D NMR spectrum of mAb/mAb fragments. Such insights go beyond rank ordering mAbs based on viscosity behavior, which can be obtained by other methods as well..

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-022-03200-6.

Deciphering the high viscosity of a therapeutic monoclonal antibody in high concentration formulations by microdialysis-hydrogen/deuterium exchange mass spectrometry

High concentration formulations of therapeutic monoclonal antibodies (mAbs) are highly desired for subcutaneous injection. However, high concentration formulations can exhibit unusual molecular behaviors, such as high viscosity or aggregation, that present challenges for manufacturing and administration. To understand the molecular mechanism of the high viscosity exhibited by high concentration protein formulations, we analyzed a human IgG4 (mAb1) at high protein concentrations using sedimentation velocity analytical ultracentrifugation (SV-AUC), X-ray crystallography, hydrogen/deuterium exchange mass spectrometry (HDX-MS), and protein surface patches analysis. Particularly, we developed a microdialysis HDX-MS method to determine intermolecular interactions at different protein concentrations. SV-AUC revealed that mAb1 displayed a propensity for self-association of Fab-Fab, Fab-Fc, and Fc-Fc. mAb1 crystal structure and HDX-MS results demonstrated self-association between complementarity-determining regions (CDRs) and Fc through electrostatic interactions. HDX-MS also indicated Fab-Fab interactions through hydrophobic surface patches constructed by mAb1 CDRs. Our multi-method approach, including fast screening of SV-AUC as well as interface analysis by X-ray crystallography and HDX-MS, helped to elucidate the high viscosity of mAb1 at high concentrations as induced by self-associations of Fab-Fc and Fab-Fab.

Measuring Self-Association of Antibody Lead Candidates with Dynamic Light Scattering

In this method chapter, we provide a brief overview of the key methods available to measure self-association of monoclonal antibodies (mAbs) and explain for which experimental throughputs they are usually applied. We then focus on dynamic light scattering (DLS) and describe experimental details on how to measure the diffusion interaction parameter (k_D) which is occasionally referred to as the gold standard for measuring self-association of proteins. The k_D is a well-established parameter to predict solution viscosity, which is one of the most critical developability parameters of mAbs. Finally, we present a pH and excipient screen that is designed to measure self-association with DLS under conditions that are relevant for bioprocessing and formulation of mAbs. The presented light scattering methods are well suited for lead candidate selections where it is essential to select mAbs with high developability potential for progression toward first human dose.

Improving antibody drug development using bionanotechnology

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.

An accelerated surface-mediated stress assay of antibody instability for developability studies

High physical stability is required for the development of monoclonal antibodies (mAbs) into successful therapeutic products. Developability assays are used to predict physical stability issues such as high viscosity and poor conformational stability, but protein aggregation remains a challenging property to predict. Among different types of stresses, air–water and solid–liquid interfaces are well known to potentially trigger protein instability and induce aggregation. Yet, in contrast to the increasing number of developability assays to evaluate bulk properties, there is still a lack of experimental methods to evaluate antibody stability against interfaces. Here, we investigate the potential of a hydrophobic nanoparticle surface-mediated stress assay to assess the stability of mAbs during the early stages of development. We evaluate this surface-mediated accelerated stability assay on a rationally designed library of 14 variants of a humanized IgG4, featuring a broad span of solubility values and other developability properties. The assay could identify variants characterized by high instability against agitation in the presence of air–water interfaces. Remarkably, for the set of investigated molecules, we observe strong correlations between the extent of aggregation induced by the surface-mediated stress assay and other developability properties of the molecules, such as aggregation upon storage at 45°C, self-association (evaluated by affinity-capture self-interaction nanoparticle spectroscopy) and nonspecific interactions (estimated by cross-interaction chromatography, stand-up monolayer chromatography (SMAC), SMAC*). This highly controlled surface-mediated stress assay has the potential to complement and increase the ability of the current set of screening techniques to assess protein aggregation and developability potential of mAbs during the early stages of drug development.

Abbreviations:AC-SINS: Affinity-Capture Self-Interaction Nanoparticle Spectroscopy; AMS: Ammonium sulfate precipitation; ANS: 1-anilinonaphtalene-8-sulfonate; CIC: Cross-interaction chromatography; DLS: Dynamic light scattering; HIC: Hydrophobic interaction chromatography; HNSSA: Hydrophobic nanoparticles surface-stress assay; mAb: Monoclonal antibody; NP: Nanoparticle; SEC: Size exclusion chromatography; SMAC: Stand-up monolayer chromatography; WT: Wild type

Measuring aggregates, self-association, and weak interactions in concentrated therapeutic antibody solutions

Monoclonal antibodies are a class of biotherapeutics used for an increasing variety of disorders, including cancer, autoimmune, neurodegenerative, and viral diseases. Besides their antigen specificity, therapeutic use also mandates control of their solution interactions and colloidal properties in order to achieve a stable, efficacious, non-immunogenic, and low viscosity antibody solution at concentrations in the range of 50–150 mg/mL. This requires characterization of their reversible self-association, aggregation, and weak attractive and repulsive interactions governing macromolecular distance distributions in solution. Simultaneous measurement of these properties, however, has been hampered by solution nonideality. Based on a recently introduced sedimentation velocity method for measuring macromolecular size distributions in a mean-field approximation for hydrodynamic interactions, we demonstrate simultaneous measurement of polydispersity and weak and strong solution interactions in a panel of antibodies with concentrations up to 45 mg/mL. By allowing approximately an order of magnitude higher concentrations than previously possible in sedimentation velocity size distribution analysis, this approach can substantially improve efficiency and sensitivity for characterizing polydispersity and interactions of therapeutic antibodies at or close to formulation conditions.

Characterization of Opalescence in low Volume Monoclonal Antibody Solutions Enabled by Microscale Nephelometry

Monoclonal antibody (mAb)-based drugs are often prone to unfavorable solution behaviors including high viscosity, opalescence, phase separation, and aggregation at the high concentrations needed to enable patient-centric subcutaneous dosage forms. Given that these can have a detrimental impact on manufacturability, stability, and delivery, approaches to identifying, monitoring, and controlling these behaviors during drug development are critical. Opalescence presents a significant challenge due to its relationship to liquid-liquid phase separation. Quantitative characterization of opalescence via turbidimetry is often restrictive due to large volume requirements (>2 mL) and alternative microscale approaches based on light transmittance (Eckhardt et al., J Pharm Sci Technol. 1994, 48: 64-70) may pose challenging with respect to accuracy. To address the need for accurate and quantitative microscale opalescence measurements, we have evaluated the use of a 'de-tuned' static light scattering detector which requires <10 μL sample per measurement. We show that tuning of the laser power to a range far below that of traditional light scattering measurements results in a stable detector response that can be accurately calibrated to the nephelometric turbidity unit (NTU) scale using appropriate standards. The calibrated detector signal yields NTU values for mAbs and other protein solutions that are comparable to a commercial turbidimeter. We used this microscale approach to characterize the opalescence of 48 commercial mAb drug products and found that the majority have opalescence below 15 NTU. However, in products with mAb concentrations greater than 75 mg/mL, a broad range of opalescence was observed, in a few cases greater than 20 NTU. These measurements as well as nephelometric characterization of several IgG1 and IgG4 mAbs across a broad pH range highlight subclass-specific tendencies toward opalescence in high concentration solutions.

Global multi-method analysis of interaction parameters for reversibly self-associating macromolecules at high concentrations

Weak macromolecular interactions assume a dominant role in the behavior of highly concentrated solutions, and are at the center of a variety of fields ranging from colloidal chemistry to cell biology, neurodegenerative diseases, and manufacturing of protein drugs. They are frequently measured in different biophysical techniques in the form of second virial coefficients, and nonideality coefficients of sedimentation and diffusion, which may be related mechanistically to macromolecular distance distributions in solution and interparticle potentials. A problem arises for proteins where reversible self-association often complicates the concentration-dependent behavior, such that grossly inconsistent coefficients are measured in experiments based on different techniques, confounding quantitative conclusions. Here we present a global multi-method analysis that synergistically bridges gaps in resolution and sensitivity of orthogonal techniques. We demonstrate the method with a panel of monoclonal antibodies exhibiting different degrees of self-association. We show how their concentration-dependent behavior, examined by static and dynamic light scattering and sedimentation velocity, can be jointly described in a self-consistent framework that separates nonideality coefficients from self-association properties, and thereby extends the quantitative interpretation of nonideality coefficients to probe dynamics in highly concentrated protein solutions.

Characterization and Modeling of Reversible Antibody Self-Association Provide Insights into Behavior, Prediction, and Correction

Reversible antibody self-association, while having major developability and therapeutic implications, is not fully understood or readily predictable and correctable. For a strongly self-associating humanized mAb variant, resulting in unacceptable viscosity, the monovalent affinity of self-interaction was measured in the low μM range, typical of many specific and biologically relevant protein-protein interactions. A face-to-face interaction model extending across both the heavy-chain (HC) and light-chain (LC) Complementary Determining Regions (CDRs) was apparent from biochemical and mutagenesis approaches as well as computational modeling. Light scattering experiments involving individual mAb, Fc, Fab, and Fab'2 domains revealed that Fabs self-interact to form dimers, while bivalent mAb/Fab'2 forms lead to significant oligomerization. Site-directed mutagenesis of aromatic residues identified by homology model patch analysis and self-docking dramatically affected self-association, demonstrating the utility of these predictive approaches, while revealing a highly specific and tunable nature of self-binding modulated by single point mutations. Mutagenesis at these same key HC/LC CDR positions that affect self-interaction also typically abolished target binding with notable exceptions, clearly demonstrating the difficulties yet possibility of correcting self-association through engineering. Clear correlations were also observed between different methods used to assess self-interaction, such as Dynamic Light Scattering (DLS) and Affinity-Capture Self-Interaction Nanoparticle Spectroscopy (AC-SINS). Our findings advance our understanding of therapeutic protein and antibody self-association and offer insights into its prediction, evaluation and corrective mitigation to aid therapeutic development.

A New Approach to Assess mAb Aggregation

A proof of concept for new methodology to detect and potentially quantify mAb aggregation is presented. Assay development included using an aggregated mAb as bait for screening of a phage display peptide library and identifying those peptides with random sequence which can recognize mAb aggregates. The selected peptides can be used for developing homogeneous quantitative methods to assess mAb aggregation. Results indicate that a peptide-binding method coupled with fluorescence polarization detection can detect mAb aggregation and potentially monitor the propensity of therapeutic protein candidates to aggregate.

Affinity Maturation Enhances Antibody Specificity but Compromises Conformational Stability

Monoclonal antibodies (mAbs) have recently emerged as one of the most promising classes of biotherapeutics. A potential advantage of B cell-derived mAbs as therapeutic agents is that they have been subjected to natural filtering mechanisms, which may enrich for B cell receptors (BCRs) with favorable biophysical properties. Here, we evaluated 400 human mAbs for polyreactivity, hydrophobicity, and thermal stability using high-throughput screening assays. Overall, mAbs derived from memory B cells and long-lived plasma cells (LLPCs) display reduced levels of polyreactivity, hydrophobicity, and thermal stability compared with naive B cell-derived mAbs. Somatic hypermutation (SHM) is inversely associated with all three biophysical properties, as well as BCR expression levels. Finally, the developability profiles of the human B cell-derived mAbs are comparable with those observed for clinical mAbs, suggesting their high therapeutic potential. The results provide insight into the biophysical consequences of affinity maturation and have implications for therapeutic antibody engineering and development.

Germinality does not necessarily define mAb expression and thermal stability

The production potential of recombinant monoclonal antibody (mAb) expressing cell lines depends, among other factors, on the intrinsic antibody structure determined by the amino acid sequence. In this study, we investigated the influence of somatic mutations in the V(D)J sequence of four individual, mature model mAbs on the expression potential. Therefore, we defined four couples, each consisting of one naturally occurring mAb (2G12, Ustekinumab, 4B3, and 2F5) and the corresponding germline-derived cognate mAb (353/11, 554/12, 136/63, and 236/14). For all eight mAb variants, recombinant Chinese hamster ovary (CHO) cell lines were developed with mAbs expressed from a defined chromosomal locus. The presented workflow investigates critical parameters including productivity, intra- and extracellular product profile, XBP1 splicing, thermal stability, and in silico hydrophobicity. Significant differences in productivity were even observed between the germline-derived mAbs which did not undergo somatic mutagenesis. Accordingly, back-to-germline mutations of mature mAbs are not necessarily reflecting improved expression and stability but indicate opportunities and limits of mAb engineering. From our studies, we conclude that germinalization represents a potential to improve mAb properties depending on the antibody’s germline family, highlighting the fact that mAbs should be treated individually.

Optimizing selectivity of anion hydrophobic multimodal chromatography for purification of a single-chain variable fragment

Single-chain variable fragments (scFv) are widely used in several fields. However, they can be challenging to purify unless using expensive Protein L-based affinity adsorbents or affinity tags. In this work, a purification process for a scFv using mixed-mode (MM) chromatography was developed by design of experiments (DoE) and proteomics for host cell protein (HCP) quantification. Capture of scFv from human embryonic kidney 293 (HEK293) cell feedstocks was performed by hydrophobic charge induction chromatography (MEP HyperCel™), whereafter polishing was performed by anion hydrophobic MM chromatography (Capto Adhere™). The DoE designs of the polishing step included both binding and flow-through modes, the latter being the standard mode for HCP removal. Chromatography with Capto Adhere™ in binding-mode with elution by linear salt gradient at pH 7.5 resulted in optimal yield, purity and HCP reduction factor of 98.9 > 98.5%, and 14, respectively. Totally, 258 different HCPs were removed, corresponding to 84% of identified HCPs. The optimized conditions enabled binding of the scFv to Capto Adhere™ below its theoretical pI, while the majority of HCPs were in the flow-through. Surface property maps indicated the presence of hydrophobic patches in close proximity to negatively charged patches that could potentially play a role in this unique selectivity.

Constructive approach for synthesis of a functional IgG using a reconstituted cell-free protein synthesis system

IgG is an indispensable biological experimental tool as well as a widely-used therapeutic protein. However, cell culture-based expression of monoclonal IgG is costly and time-consuming, making this process difficult to use for high-throughput screening in early-stage evaluation of biologics. With the goal of establishing a fast, simple, and robust high-throughput expression system for IgG, we implemented the synthesis of functional aglycosylated IgG by constructive approach based on a reconstituted prokaryotic cell-free protein synthesis system (PURE system). Optimization of the PURE system revealed that the following factors and reaction conditions were needed for IgG synthesis: (1) inclusion of the disulfide bond isomerase DsbC, (2) adjustment of the GSH/GSSG ratio, (3) inclusion of the molecular chaperone DnaK and its cofactors, and (4) use of an extended incubation time. Synthesis temperature and template DNA ratio (light chain-/heavy chain-encoding) also had been optimized for each IgG. Under optimal conditions, peak production of the anti-HER2 antibody trastuzumab reached 124 µg/mL. Furthermore, the active forms of other IgGs, including IgG1, IgG2, and IgG4 subclasses, also were synthesized. These results provide basic information for the development of novel high-throughput expression and functional screening systems for IgG, as well as useful information for understanding the IgG synthesis process.

Structure, heterogeneity and developability assessment of therapeutic antibodies

Increasing attention has been paid to developability assessment with the understanding that thorough evaluation of monoclonal antibody lead candidates at an early stage can avoid delays during late-stage development. The concept of developability is based on the knowledge gained from the successful development of approximately 80 marketed antibody and Fc-fusion protein drug products and from the lessons learned from many failed development programs over the last three decades. Here, we reviewed antibody quality attributes that are critical to development and traditional and state-of-the-art analytical methods to monitor those attributes. Based on our collective experiences, a practical workflow is proposed as a best practice for developability assessment including in silico evaluation, extended characterization and forced degradation using appropriate analytical methods that allow characterization with limited material consumption and fast turnaround time.

Biophysical characterization and molecular simulation of electrostatically driven self-association of a single-chain antibody

Colloidal protein-protein interactions (PPI) are often expected to impact key behaviors of proteins in solution, such as aggregation rates and mechanisms, aggregate structure, protein solubility, and solution viscosity. PPI of an anti-fluorescein single chain antibody variable fragment (scFv) were characterized experimentally at low to intermediate ionic strength using a combination of static light scattering and sedimentation equilibrium ultracentrifugation. Surprisingly, the results indicated that interactions were strongly net-attractive and electrostatics promoted self-association. Only repulsive interactions were expected based on prior work and calculations based a homology model of a related scFv crystal structure. However, the crystal structure lacks the charged, net-neutral linker sequence. PyRosetta was used to generate a set of scFv structures with different linker conformations, and coarse-grained Monte Carlo simulations were used to evaluate the effect of different linker configurations via second osmotic virial coefficient (B₂₂ ) simulations. The results show that the configuration of the linker has a significant effect on the calculated B₂₂ values, and can result in strong electrostatic attractions between oppositely charged residues on the protein surface. This is particularly relevant for development of non-natural antibody products, where charged linkers and other loop regions may be prevalent. The results also provide a preliminary computational framework to evaluate the effect of unstructured linkers on experimental protein-protein interaction parameters such as B₂₂ .

A role for macromolecular crowding in off-target binding of therapeutic antibodies

The nonspecific binding of certain therapeutic antibodies to tissues or to soluble biomolecules can accelerate their clearance from the circulation and undermine their benefit to patients. This article proposes that tandem amino acid repeat sequences in antibody hypervariable segments, particularly the complementarity determining regions (CDRs), can enhance this off-target binding. This hypothesis is based on two sets of observations. First, in a limited number of cases, antibodies with clusters of amino acid repeats in their CDRs have significantly higher clearance rates in experimental animals than otherwise identical antibodies without the repeats. Second, tandem amino acid repeats are abundant in intracellular hub proteins where they appear to promote the promiscuous binding of these proteins to a wide variety of other molecules. These nonspecific hub protein interactions are highly favored by the intense macromolecular crowding that permeates the cytoplasm. A survey of the variable region sequences of 137 antibodies in various stages of development revealed that 26 have at least one CDR containing a cluster of three closely spaced amino acid repeats. If the overall hypothesis is valid, then it suggests strategies for site-directed mutagenesis to improve pharmacokinetic behavior and for the design of more reliable in vitro binding assays to predict off-target binding in vivo.

Challenges in Predicting Protein-Protein Interactions from Measurements of Molecular Diffusivity

Dynamic light scattering can be used to measure the diffusivity of a protein within a formulation. The dependence of molecular diffusivity on protein concentration (traditionally expressed in terms of the interaction parameter k_D) is often used to infer whether protein-protein interactions are repulsive or attractive, resulting in solutions that are colloidally stable or unstable, respectively. However, a number of factors unrelated to intermolecular forces can also impact protein diffusion, complicating this interpretation. Here, we investigate the influence of multicomponent diffusion in a ternary protein-salt-water system on protein diffusion and k_D in the context of Nernst-Planck theory. This analysis demonstrates that large changes in protein diffusivity with protein concentration can result even for hard-sphere systems in the absence of protein-protein interactions. In addition, we show that dynamic light scattering measurements of diffusivity made at low ionic strength cannot be reliably used to detect protein conformational changes. We recommend comparing experimentally determined k_D values to theoretically predicted excluded-volume contributions, which will allow a more accurate assessment of protein-protein interactions.

Tracking Antibody Distribution with Near-Infrared Fluorescent Dyes: Impact of Dye Structure and Degree of Labeling on Plasma Clearance

Monoclonal antibodies labeled with near-infrared (NIR) fluorophores have potential use in disease detection, intraoperative imaging, and pharmacokinetic characterization of therapeutic antibodies in both the preclinical and clinical setting. Recent work has shown conjugation of NIR fluorophores to antibodies can potentially alter antibody disposition at a sufficiently high degree of labeling (DoL); however, other reports show minimal impact after labeling with NIR fluorophores. In this work, we label two clinically approved antibodies, Herceptin (trastuzumab) and Avastin (bevacizumab), with NIR dyes IRDye 800CW (800CW) or Alexa Fluor 680 (AF680), at 1.2 and 0.3 dyes/antibody and examine the impact of fluorophore conjugation on antibody plasma clearance and tissue distribution. At 0.3 DoL, AF680 conjugates exhibited similar clearance to unlabeled antibody over 17 days while 800CW conjugates diverged after 4 days, suggesting AF680 is a more suitable choice for long-term pharmacokinetic studies. At the 1.2 DoL, 800CW conjugates cleared faster than unlabeled antibodies after several hours, in agreement with other published reports. The tissue biodistribution for bevacizumab–800CW and −AF680 conjugates agreed well with literature reported biodistributions using radiolabels. However, the greater tissue autofluorescence at 680 nm resulted in limited detection above background at low (∼2 mg/kg) doses and 0.3 DoL for AF680, indicating that 800CW is more appropriate for short-term biodistribution measurements and intraoperative imaging. Overall, our work shows a DoL of 0.3 or less for non-site-specifically labeled antibodies (with a Poisson distribution) is ideal for limiting the impact of NIR fluorophores on antibody pharmacokinetics.

A new approach to quantification of mAb aggregates using peptide affinity probes

Using mAbs as therapeutic molecules is complicated by the propensity of mAbs to aggregate at elevated concentrations, which can lead to a variety of adverse events in treatment. Here, we describe a proof-of-concept for new methodology to detect and quantify mAb aggregation. Assay development included using an aggregated mAb as bait for screening of phage display peptide library and identifying those peptides with random sequence which can recognize mAb aggregates. Once identified, the selected peptides can be used for developing quantitative methods to assess mAb aggregation. Results indicate that a peptide binding method coupled with mass spectrometric detection of bound peptide can quantify mAb aggregation and potentially be useful for monitoring aggregation propensity of therapeutic protein candidates.

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.

Quantitative Impact of Plasma Clearance and Down-regulation on GLP-1 Receptor Molecular Imaging

PURPOSE

Quantitative molecular imaging of beta cell mass (BCM) would enable early detection and treatment monitoring of type 1 diabetes. The glucagon-like peptide-1 (GLP-1) receptor is an attractive target due to its beta cell specificity and cell surface location. We quantitatively investigated the impact of plasma clearance and receptor internalization on targeting efficiency in healthy B6 mice.

PROCEDURES

Four exenatide-based probes were synthesized that varied in molecular weight, binding affinity, and plasma clearance. The GLP-1 receptor internalization rate and in vivo receptor expression were quantified.

RESULTS

Receptor internalization (54,000 receptors/cell in vivo) decreased significantly within minutes, reducing the benefit of a slower-clearing agent. The multimers and albumin binding probes had higher kidney and liver uptake, respectively.

CONCLUSIONS

Slow plasma clearance is beneficial for GLP-1 receptor peptide therapeutics. However, for exendin-based imaging of islets, down-regulation of the GLP-1 receptor and non-specific background uptake result in a higher target-to-background ratio for fast-clearing agents.

Antibody Aggregation: Insights from Sequence and Structure

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

Molecular perspective of antibody aggregates and their adsorption on Protein A resin

Antibody aggregate is a common issue in therapeutic antibodies, which may compromise product efficacy and cause adverse effects. Antibody aggregate level is normally controlled in bioprocessing by polishing steps after Protein A capture. This paper studied the Higher Order Structures (HOS) of antibody aggregates (dimer H1 and H2) and their adsorption on Protein A resin and thus elucidated the mechanism using Protein A capture for enhanced aggregate removal. The HOS of antibody aggregates and their complex with Protein A were characterized using HDX-MS combined with SEC-MALS, Protein Conformational Array (PCA), and molecular modeling. The aggregate size and Protein A binding ratio suggested that H2 has much more compact structure than H1. HDX-MS and PCA further revealed that H1 was formed by single Fab-Fab interaction while H2 formed by Fab-Fab and likely Fc-Fc interaction. On Protein A resin, both the molar binding ratio and the correlation between protein size and ligand distance support that each monomer can only bind one Protein A ligand, while each dimer can bind two ligands, thus resulting in stronger resin binding. Furthermore, dimer H2 binds stronger than dimer H1 due to its compact structure. By integrating biophysical analysis and molecular modeling with process development, this study revealed the antibody aggregate structures and the mechanism of aggregate removal using Protein A chromatography. It also provided a general strategy for in-depth product and process understanding in antibody and other biologics development.

Mechanistic and quantitative insight into cell surface targeted molecular imaging agent design

Molecular imaging agent design involves simultaneously optimizing multiple probe properties. While several desired characteristics are straightforward, including high affinity and low non-specific background signal, in practice there are quantitative trade-offs between these properties. These include plasma clearance, where fast clearance lowers background signal but can reduce target uptake, and binding, where high affinity compounds sometimes suffer from lower stability or increased non-specific interactions. Further complicating probe development, many of the optimal parameters vary depending on both target tissue and imaging agent properties, making empirical approaches or previous experience difficult to translate. Here, we focus on low molecular weight compounds targeting extracellular receptors, which have some of the highest contrast values for imaging agents. We use a mechanistic approach to provide a quantitative framework for weighing trade-offs between molecules. Our results show that specific target uptake is well-described by quantitative simulations for a variety of targeting agents, whereas non-specific background signal is more difficult to predict. Two in vitro experimental methods for estimating background signal in vivo are compared – non-specific cellular uptake and plasma protein binding. Together, these data provide a quantitative method to guide probe design and focus animal work for more cost-effective and time-efficient development of molecular imaging agents.

Measurements of Monoclonal Antibody Self-Association Are Correlated with Complex Biophysical Properties

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.

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.

Hydrogen exchange mass spectrometry reveals protein interfaces and distant dynamic coupling effects during the reversible self-association of an IgG1 monoclonal antibody

There is a need for new analytical approaches to better characterize the nature of the concentration-dependent, reversible self-association (RSA) of monoclonal antibodies (mAbs) directly, and with high resolution, when these proteins are formulated as highly concentrated solutions. In the work reported here, hydrogen exchange mass spectrometry (HX-MS) was used to define the concentration-dependent RSA interface, and to characterize the effects of association on the backbone dynamics of an IgG1 mAb (mAb-C). Dynamic light scattering, chemical cross-linking, and solution viscosity measurements were used to determine conditions that caused the RSA of mAb-C. A novel HX-MS experimental approach was then applied to directly monitor differences in local flexibility of mAb-C due to RSA at different protein concentrations in deuterated buffers. First, a stable formulation containing lyoprotectants that permitted freeze-drying of mAb-C at both 5 and 60 mg/mL was identified. Upon reconstitution with RSA-promoting deuterated solutions, the low vs. high protein concentration samples displayed different levels of solution viscosity (i.e., approx. 1 to 75 mPa.s). The reconstituted mAb-C samples were then analyzed by HX-MS. Two specific sequences covering complementarity-determining regions CDR2H and CDR2L (in the variable heavy and light chains, respectively) showed significant protection against deuterium uptake (i.e., decreased hydrogen exchange). These results define the major protein-protein interfaces associated with the concentration-dependent RSA of mAb-C. Surprisingly, certain peptide segments in the V_H domain, the constant domain (C_H2), and the hinge region (C_H1-C_H2 interface) concomitantly showed significant increases in local flexibility at high vs. low protein concentrations. These results indicate the presence of longer-range, distant dynamic coupling effects within mAb-C occurring upon RSA.

High-throughput assay for measuring monoclonal antibody self-association and aggregation in serum

Subcutaneous delivery is one of the preferred administration routes for therapeutic monoclonal antibodies (mAbs). High antibody dosing requirements and small injection volumes necessitate formulation and delivery of highly concentrated mAb solutions. Such elevated antibody concentrations can lead to undesirable solution behaviors such as mAb self-association and aggregation, which are relatively straightforward to detect using various biophysical methods because of the high purity and concentration of antibody formulations. However, the biophysical properties of mAbs in serum can also impact antibody activity, but these properties are less well understood because of the difficulty characterizing mAbs in such a complex environment. Here we report a high-throughput assay for directly evaluating mAb self-association and aggregation in serum. Our approach involves immobilizing polyclonal antibodies specific for human mAbs on gold nanoparticles, and then using these conjugates to capture human antibodies at a range of subsaturating to saturating mAb concentrations in serum. Antibody aggregation is detected at subsaturating mAb concentrations via blue-shifted plasmon wavelengths due to the reduced efficiency of capturing mAb aggregates relative to monomers, which reduces affinity cross-capture of mAbs by multiple conjugates. In contrast, antibody self-association is detected at saturating mAb concentrations via red-shifted plasmon wavelengths due to attractive interparticle interactions between immobilized mAbs. The high-throughput nature of this assay along with its compatibility with unusually dilute mAb solutions (0.1-10 μg per mL) should make it useful for identifying antibody candidates with high serum stability during early antibody discovery.