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

Elucidation of the Reversible Self-Association Interface of a Diabody-Interleukin Fusion Protein Using Hydrogen-Exchange Mass Spectrometry and In Silico Modeling

Reversible self-association (RSA) of therapeutic proteins presents major challenges in the development of high-concentration formulations, especially those intended for subcutaneous administration. Understanding self-association mechanisms is therefore critical to the design and selection of candidates with acceptable developability to advance to clinical trials. The combination of experiments and in silico modeling presents a powerful tool to elucidate the interface of self-association. RSA of monoclonal antibodies has been studied extensively under different solution conditions and have been shown to involve interactions for both the antigen-binding fragment and the crystallizable fragment. Novel modalities such as bispecific antibodies, antigen-binding fragments, single-chain-variable fragments, and diabodies constitute a fast-growing class of antibody-based therapeutics that have unique physiochemical properties compared to monoclonal antibodies. In this study, the RSA interface of a diabody-interleukin 22 fusion protein (FP-1) was studied using hydrogen-deuterium exchange coupled with mass spectrometry (HDX-MS) in combination with in silico modeling. Taken together, the results show that a complex solution behavior underlies the self-association of FP-1 and that the interface thereof can be attributed to a specific segment in the variable light chain of the diabody. These findings also demonstrate that the combination of HDX-MS with in silico modeling is a powerful tool to guide the design and candidate selection of novel biotherapeutic modalities.

Hydrodynamic and thermodynamic analysis of PEGylated human serum albumin

Covalent labeling of therapeutic drugs and proteins with polyethylene glycol (PEGylation) is an important modification for improving stability, solubility, and half-life. PEGylation alters protein solution behavior through its impact on thermodynamic nonideality by increasing the excluded volume, and on hydrodynamic nonideality by increasing the frictional drag. To understand PEGylation's impact, we investigated the thermodynamic and hydrodynamic properties of a model system consisting of PEGylated human serum albumin derivatives using analytical ultracentrifugation (AUC) and dynamic light scattering (DLS). We constructed PEGylated human serum albumin derivatives of single, linear 5K, 10K, 20K, and 40K PEG chains and a single branched-chain PEG of 40K (2 × 20K). Sedimentation velocity (SV) experiments were analyzed using SEDANAL direct boundary fitting to extract ideal sedimentation coefficients so, hydrodynamic nonideality ks, and thermodynamic nonideality 2BM1SV terms. These quantities allow the determination of the Stokes radius Rs, the frictional ratio f/fo, and the swollen or entrained volume Vs/v, which measure size, shape, and solvent interaction. We performed sedimentation equilibrium experiments to obtain independent measurements of thermodynamic nonideality 2BM1SE. From DLS measurements, we determined the interaction parameter, kD, the concentration dependence of the apparent diffusion coefficient, D, and from extrapolation of D to c = 0 a second estimate of Rs. Rs values derived from SV and DLS measurements and ensemble model calculations (see complementary study) are then used to show that ks + kD = theoretical 2B22M1. In contrast, experimental BM1 values from SV and sedimentation equilibrium data collectively allow for similar analysis for protein-PEG conjugates and show that ks + kD = 1.02-1.07∗BM1, rather than the widely used ks + kD = 2BM1 developed for hard spheres. The random coil behavior of PEG dominates the colloidal properties of PEG-protein conjugates and exceeds the sum of a random coil and hard-sphere volume due to excess entrained water.

The origins of nonideality exhibited by monoclonal antibodies and Fab fragments in human serum

The development of therapeutic antibodies remains challenging, time-consuming, and expensive. A key contributing factor is a lack of understanding of how proteins are affected by complex biological environments such as serum and plasma. Nonideality due to attractive or repulsive interactions with cosolutes can alter the stability, aggregation propensity, and binding interactions of proteins in solution. Fluorescence correlation spectroscopy (FCS) can be used to measure apparent second virial coefficient (B2,app ) values for therapeutic and model monoclonal antibodies (mAbs) that capture the nature and strength of interactions with cosolutes directly in undiluted serum and similar complex biological media. Here, we use FCS-derived B2,app measurements to identify the components of human serum responsible for nonideal interactions with mAbs and Fab fragments. Most mAbs exhibit neutral or slightly attractive interactions with intact serum. Generally, mAbs display repulsive interactions with albumin and mildly attractive interactions with IgGs in the context of whole serum. Crucially, however, these attractive interactions are much stronger with pooled IgGs isolated from other serum components, indicating that the effects of serum nonideality can only be understood by studying the intact medium (rather than isolated components). Moreover, Fab fragments universally exhibited more attractive interactions than their parental mAbs, potentially rendering them more susceptible to nonideality-driven perturbations. FCS-based B2,app measurements have the potential to advance our understanding of how physiological environments impact protein-based therapeutics in general. Furthermore, incorporating such assays into preclinical biologics development may help de-risk molecules and make for a faster and more efficient development process.

An automated interface for sedimentation velocity analysis in SEDFIT

Sedimentation velocity analytical ultracentrifugation (SV-AUC) is an indispensable tool for the study of particle size distributions in biopharmaceutical industry, for example, to characterize protein therapeutics and vaccine products. In particular, the diffusion-deconvoluted sedimentation coefficient distribution analysis, in the software SEDFIT, has found widespread applications due to its relatively high resolution and sensitivity. However, a lack of suitable software compatible with Good Manufacturing Practices (GMP) has hampered the use of SV-AUC in this regulatory environment. To address this, we have created an interface for SEDFIT so that it can serve as an automatically spawned module with controlled data input through command line parameters and output of key results in files. The interface can be integrated in custom GMP compatible software, and in scripts that provide documentation and meta-analyses for replicate or related samples, for example, to streamline analysis of large families of experimental data, such as binding isotherm analyses in the study of protein interactions. To test and demonstrate this approach we provide a MATLAB script mlSEDFIT.

Lymphocyte activation gene 3 is increased and affects cytokine production in rheumatoid arthritis

BACKGROUND

Lymphocyte activation gene-3 (LAG-3) inhibits T cell activation and interferes with the immune response by binding to MHC-II. As antigen presentation is central in rheumatoid arthritis (RA) pathogenesis, we studied aspects of LAG-3 as a serological marker and mediator in the pathogenesis of RA. Since Galectin-3 (Gal-3) is described as an additional binding partner for LAG-3, we also aimed to study the functional importance of this interaction.

METHODS

Plasma levels of soluble (s) LAG-3 were measured in early RA patients (eRA, n = 99) at baseline and after 12 months on a treat-to-target protocol, in self-reportedly healthy controls (HC, n = 32), and in paired plasma and synovial fluid (SF) from chronic RA patients (cRA, n = 38). Peripheral blood mononuclear cells (PBMCs) and synovial fluid mononuclear cells (SFMCs) were examined for LAG-3 expression by flow cytometry. The binding and functional outcomes of LAG-3 and Gal-3 interaction were assessed with surface plasmon resonance (SPR) and in cell cultures using rh-LAG3, an antagonistic LAG-3 antibody and a Gal-3 inhibitor.

RESULTS

Baseline sLAG-3 in the plasma was increased in eRA compared to HC and remained significantly elevated throughout 12 months of treatment. A high level of sLAG-3 at baseline was associated with the presence of IgM-RF and anti-CCP as well as radiographic progression. In cRA, sLAG-3 was significantly increased in SF compared with plasma, and LAG-3 was primarily expressed by activated T cells in SFMCs compared to PBMCs. Adding recombinant human LAG-3 to RA cell cultures resulted in decreased cytokine secretion, whereas blocking LAG-3 with an antagonistic antibody resulted in increased cytokine secretion. By SPR, we found a dose-dependent binding between LAG-3 and Gal-3. However, inhibiting Gal-3 in cultures did not further change cytokine production.

CONCLUSIONS

sLAG-3 in the plasma and synovial fluid is increased in both early and chronic RA patients, particularly in the inflamed joint. High levels of sLAG-3 are associated with autoantibody seropositivity and radiographic progression in eRA, and LAG-3 plays a biologically active role in cRA by decreasing inflammatory cytokine production. This functional outcome is not affected by Gal-3 interference. Our results suggest that LAG-3 is a faceted regulator of inflammation in early and chronic RA.

An automated interface for sedimentation velocity analysis in SEDFIT

Sedimentation velocity analytical ultracentrifugation (SV-AUC) is an indispensable tool for the study of particle size distributions in biopharmaceutical industry, for example, to characterize protein therapeutics and vaccine products. In particular, the diffusion-deconvoluted sedimentation coefficient distribution analysis, in the software SEDFIT, has found widespread applications due to its relatively high resolution and sensitivity. However, a lack of available software compatible with Good Manufacturing Practices (GMP) has hampered the use of SV-AUC in this regulatory environment. To address this, we have created an interface for SEDFIT so that it can serve as an automatically spawned module with controlled data input through command line parameters and output of key results in files. The interface can be integrated in custom GMP compatible software, and in scripts that provide documentation and meta-analyses for replicate or related samples, for example, to streamline analysis of large families of experimental data, such as binding isotherm analyses in the study of protein interactions. To test and demonstrate this approach we provide a MATLAB script mlSEDFIT.

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.

Determination of specific and non-specific protein-protein interactions for beta-lactoglobulin by analytical ultracentrifugation and membrane osmometry experiments

Protein-protein interactions are essential for the understanding of biological processes. Specific protein aggregation is an important aspect for many biological systems. In particular, electrostatic interactions play the key role for protein-protein interactions, as many amino acids have pH-dependent charge states. Moreover, protein dissociation is directly related to the solution pH, ionic strength, temperature and protein concentration. The subtle interplay between different specific and non-specific interactions is demonstrated for beta-lactoglobulin (BLG) with a focus on low salt concentrations, thus mimicking technically relevant processing conditions. BLG is a well-characterized model system, proven to attain its monomer-dimer equilibrium strongly dependent upon the pH of the solution. In this manuscript, we present a unique combination of analytical ultracentrifugation and membrane osmometry experiments, which quantifies specific and non-specific interactions, i.e. in terms of the dimer dissociation constants and the second osmotic virial coefficient, at pH 3 and 7 and sodium chloride concentrations of 10 mM and 100 mM. This provides direct insight to protein-protein interactions for a system with a concentration-dependent monomer-dimer equilibrium. Moreover, using a coarse-grained extended DLVO model in combination with molecular dynamics simulations, we quantify non-specific monomer-monomer, monomer-dimer and dimer-dimer interactions as well as the binding free energy of BLG dimerization from theoretical calculations. The experimentally determined interactions are shown to be mainly governed by electrostatic interactions and further agree with free energy calculations. Our experimental protocol aims to determine non-specific and specific interactions for a dynamically interacting system and provides an understanding of protein-protein interactions for BLG at low salt concentrations.

Effects of Monovalent Salt on Protein-Protein Interactions of Dilute and Concentrated Monoclonal Antibody Formulations

In this study, we used sodium chloride (NaCl) to extensively modulate non-specific protein-protein interactions (PPI) of a humanized anti-streptavidin monoclonal antibody class 2 molecule (ASA-IgG2). The changes in PPI with varying NaCl (C_NaCl) and monoclonal antibody (mAb) concentration (C_mAb) were assessed using the diffusion interaction parameter k_D and second virial coefficient B₂₂ measured from solutions with low to moderate C_mAb. The effective structure factor S(q)_eff measured from concentrated mAb solutions using small-angle X-ray and neutron scattering (SAXS/SANS) was also used to characterize the PPI. Our results found that the nature of net PPI changed not only with C_NaCl, but also with increasing C_mAb. As a result, parameters measured from dilute and concentrated mAb samples could lead to different predictions on the stability of mAb formulations. We also compared experimentally determined viscosity results with those predicted from interaction parameters, including k_D and S(q)_eff. The lack of a clear correlation between interaction parameters and measured viscosity values indicates that the relationship between viscosity and PPI is concentration-dependent. Collectively, the behavior of flexible mAb molecules in concentrated solutions may not be correctly predicted using models where proteins are considered to be uniform colloid particles defined by parameters derived from low C_mAb.

Best Practices for Aggregate Quantitation of Antibody Therapeutics by Sedimentation Velocity Analytical Ultracentrifugation

Analytical ultracentrifugation (AUC) is a critical analytical tool supporting the development and manufacture of protein therapeutics. AUC is routinely used as an assay orthogonal to size exclusion chromatography for aggregate quantitation. This article distills the experimental and analysis procedures used by the authors for sedimentation velocity AUC into a series of best-practices considerations. The goal of this distillation is to help harmonize aggregate quantitation approaches across the biopharmaceutical industry. We review key considerations for sample and instrument suitability, experimental design, and data analysis best practices and conversely, highlight potential pitfalls to accurate aggregate analysis. Our goal is to provide experienced users benchmarks against which they can standardize their analyses and to provide guidance for new AUC analysts that will aid them to become proficient in this fundamental technique.

Nanoencapsulation as a General Solution for Lyophilization of Labile Substrates

Protein macromolecules occur naturally at the nanoscale. The use of a dedicated nanoparticle as a lyophilization excipient, however, has not been reported. Because biopolymeric and lipid nanoparticles often denature protein macromolecules and commonly lack the structural rigidity to survive the freeze-drying process, we hypothesized that surrounding an individual protein substrate with a nanoscale, thermostable exoshell (tES) would prevent aggregation and protect the substrate from denaturation during freezing, sublimation, and storage. We systematically investigated the properties of tES, including secondary structure and its homogeneity, throughout the process of lyophilization and found that tES have a near 100% recovery following aqueous reconstitution. We then tested the hypothesis that tES could encapsulate a model substrate, horseradish peroxidase (HRP), using charge complementation and pH-mediated controlled assembly. HRP were encapsulated within the 8 nm internal tES aqueous cavity using a simplified loading procedure. Time-course experiments demonstrated that unprotected HRP loses 95% of activity after 1 month of lyophilized storage. After encapsulation within tES nanoparticles, 70% of HRP activity was recovered, representing a 14-fold improvement and this effect was reproducible across a range of storage temperatures. To our knowledge, these results represent the first reported use of nanoparticle encapsulation to stabilize a functional macromolecule during lyophilization. Thermostable nanoencapsulation may be a useful method for the long-term storage of labile proteins.

Characterization of DNA-protein complexes by nanoparticle tracking analysis and their association with systemic lupus erythematosus

Nanotechnology enables investigations of single biomacromolecules, but technical challenges have limited the application in liquid biopsies, for example, blood plasma. Nonetheless, tools to characterize single molecular species in such samples represent a significant unmet need with the increasing appreciation of the physiological importance of protein structural changes at nanometer scale. Mannose-binding lectin (MBL) is an oligomeric plasma protein and part of the innate immune system through its ability to activate complement. MBL also serves a role as a scavenger for cellular debris, especially DNA. This may link functions of MBL with several inflammatory diseases in which cell-free DNA now appears to play a role, but mechanistic insight has been lacking. By making nanoparticle tracking analysis possible in human plasma, we now show that superoligomeric structures of MBL form nanoparticles with DNA. These oligomers correlate with disease activity in systemic lupus erythematosus patients. With the direct quantification of the hydrodynamic radius, calculations following the principles of Taylor dispersion in the blood stream connect the size of these complexes to endothelial inflammation, which is among the most important morbidities in lupus. Mechanistic insight from an animal model of lupus supported that DNA-stabilized superoligomers stimulate the formation of germinal center B cells and drive loss of immunological tolerance. The formation involves an inverse relationship between the concentration of MBL superoligomers and antibodies to double-stranded DNA. Our approach implicates the structure of DNA-protein nanoparticulates in the pathobiology of autoimmune diseases.

Protein-protein interactions at high concentrations: Effects of ArgHCl and NaCl on the stability, viscosity and aggregation mechanisms of protein solution

The aim of this work was to use the diffusion coefficient ration (D_m/D_line) as a parameter to characterize the stability of protein at high concentration, to compare the effects of ArgHCl and NaCl on the interaction of highly concentrated proteins under different pH conditions, and to explore the correlation with protein stability. For this purpose, a high-concentration bovine serum albumin solution (BSA) was selected as the model system, and the diffusion coefficient, aggregation degree, conformational stability, and solution viscosity of the protein were studied by dynamic light scattering (DLS) and spectral detection techniques. The result showed that there was a significant correlation between the D_m/D_line and the protein aggregation. The D_m/D_line of the protein was minimum at pH 7.4, which corresponded to the maximum degree of aggregation and the highest solution viscosity. At pH 7.4, the hydrophobic interactions and the increased conformational stability of ArgHCl maximized the stability of the protein and reduced the viscosity of the solution by 69.3%. At pH 3.0, the strong charge shielding effect of ArgHCl and NaCl and the decreased conformational stability induced protein aggregation and the gel formation. These findings provided valuable insights into the mechanism of protein aggregation and the diffusion coefficient ration (D_m/D_line) could be a potential tool for the pre-formulation studies.

Probing sedimentation non-ideality of particulate systems using analytical centrifugation

Analytical centrifugation is a versatile technique for the quantitative characterization of colloidal systems including colloidal stability. The recent developments in data acquisition and evaluation allow the accurate determination of particle size, shape anisotropy and particle density. High precision analytical centrifugation is in particular suited for the study of particle interactions and concentration-dependent sedimentation coefficients. We present a holistic approach for the quantitative determination of sedimentation non-ideality via analytical centrifugation for polydisperse, plain and amino-functionalized silica particles spanning over one order of magnitude in particle size between 100 nm and 1200 nm. These systems typically behave as neutral hard spheres as predicted by auxiliary lattice Boltzmann simulations. The extent of electrostatic interactions and their impact on sedimentation non-ideality can be quantified by the repulsion range, which is the ratio of the Debye length and the average interparticle distance. Experimental access to the repulsion range is provided through conductivity measurements. With the experimental repulsion range at hand, we estimate the effect of polydispersity on concentration-dependent sedimentation properties through a combination of lattice Boltzmann and Brownian dynamics simulations. Finally, we determine the concentration-dependent sedimentation properties of charge-stabilized, fluorescently-labeled silica particles with a nominal particle size of 30 nm and reduced interparticle distance, hence an elevated repulsion range. Overall, our results demonstrate how the influence of hard-sphere type and electrostatic interactions can be quantified when probing sedimentation non-ideality of particulate systems using analytical centrifugation even for systems exhibiting moderate sample heterogeneity and complex interactions.

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.