An Expanded Conformation of an Antibody Fab Region by X-Ray Scattering, Molecular Dynamics, and smFRET Identifies an Aggregation Mechanism

Molecular Dynamics Simulations Reveal How Competing Protein-Surface Interactions for Glycine, Citrate, and Water Modulate Stability in Antibody Fragment Formulations

The design of stable formulations remains a major challenge for protein therapeutics, particularly the need to minimize aggregation. Experimental formulation screens are typically based on thermal transition midpoints (Tm), and forced degradation studies at elevated temperatures. Both approaches give limited predictions of long-term storage stability, particularly at low temperatures. Better understanding of the mechanisms of action for formulation of excipients and buffers could lead to improved strategies for formulation design. Here, we identified a complex impact of glycine concentration on the experimentally determined stability of an antibody Fab fragment and then used molecular dynamics simulations to reveal mechanisms that underpin these complex behaviors. Tm values increased monotonically with glycine concentration, but associated ΔSvh measurements revealed more complex changes in the native ensemble dynamics, which reached a maximum at 30 mg/mL. The aggregation kinetics at 65 °C were similar at 0 and 20 mg/mL glycine, but then significantly slower at 50 mg/mL. These complex behaviors indicated changes in the dominant stabilizing mechanisms as the glycine concentration was increased. MD revealed a complex balance of glycine self-interaction, and differentially preferred interactions of glycine with the Fab as it displaced hydration-shell water, and surface-bound water and citrate buffer molecules. As a result, glycine binding to the Fab surface had different effects at different concentrations, and led from preferential interactions at low concentrations to preferential exclusion at higher concentrations. During preferential interaction, glycine displaced water from the Fab hydration shell, and a small number of water and citrate molecules from the Fab surface, which reduced the protein dynamics as measured by root-mean-square fluctuation (RMSF) on the short time scales of MD. By contrast, the native ensemble dynamics increased according to ΔSvh, suggesting increased conformational changes on longer time scales. The aggregation kinetics did not change at low glycine concentrations, and so the opposing dynamics effects either canceled out or were not directly relevant to aggregation. During preferential exclusion at higher glycine concentrations, glycine could only bind to the Fab surface through the displacement of citrate buffer molecules already favorably bound on the Fab surface. Displacement of citrate increased the flexibility (RMSF) of the Fab, as glycine formed fewer bridging hydrogen bonds to the Fab surface. Overall, the slowing of aggregation kinetics coincided with reduced flexibility in the Fab ensemble at the very highest glycine concentrations, as determined by both RMSF and ΔSvh, and occurred at a point where glycine binding displaced neither water nor citrate. These final interactions with the Fab surface were driven by mass action and were the least favorable, leading to a macromolecular crowding effect under the regime of preferential exclusion that stabilized the dynamics of Fab.

Predictive Model Building for Aggregation Kinetics Based on Molecular Dynamics Simulations of an Antibody Fragment

Computational methods including machine learning and molecular dynamics simulations have strong potential to characterize, understand, and ultimately predict the properties of proteins relevant to their stability and function as therapeutics. Such methods would streamline the development pathway by minimizing the current experimental testing required for many protein variants and formulations. The molecular understanding of thermostability and aggregation propensity has advanced significantly along with predictive algorithms based on the sequence-level or structural-level information on a protein. However, these approaches focus largely on a comparison of protein sequence variations to correlate the properties of proteins to their stability, solubility, and aggregation propensity. For therapeutic protein development, it is of equal importance to take into account the impact of the formulation conditions to elucidate and predict the stability of the antibody drugs. At the macroscopic level, changing temperature, pH, ionic strength, and the addition of excipients can significantly alter the kinetics of protein aggregation. The mechanisms controlling aggregation kinetics have been traced back to a combination of molecular features, including conformational stability, partial unfolding to aggregation-prone states, and the colloidal stability governed by surface charges and hydrophobicity. However, very little has been done to evaluate these features in the context of protein dynamics in different formulations. In this work, we have combined a range of molecular features calculated from the Fab A33 protein sequence and molecular dynamics simulations. Using the power of advanced, yet interpretable, statistical tools, it has been possible to uncover greater insights into the mechanisms behind protein stability, validating previous findings, and also develop models that can predict the aggregation kinetics within a range of 49 different solution conditions.

Understanding and controlling the molecular mechanisms of protein aggregation in mAb therapeutics

In antibody development and manufacturing, protein aggregation is a common challenge that can lead to serious efficacy and safety issues. To mitigate this problem, it is important to investigate its molecular origins. This review discusses (1) our current molecular understanding and theoretical models of antibody aggregation, (2) how various stress conditions related to antibody upstream and downstream bioprocesses can trigger aggregation, and (3) current mitigation strategies employed towards inhibiting aggregation. We discuss the relevance of the aggregation phenomenon in the context of novel antibody modalities and highlight how in silico approaches can be exploited to mitigate it.

Enhanced Thermal Stability and Reduced Aggregation in an Antibody Fab Fragment at Elevated Concentrations

The aggregation of protein therapeutics such as antibodies remains a major challenge in the biopharmaceutical industry. The present study aimed to characterize the impact of the protein concentration on the mechanisms and potential pathways for aggregation, using the antibody Fab fragment A33 as the model protein. Aggregation kinetics were determined for 0.05 to 100 mg/mL Fab A33, at 65 °C. A surprising trend was observed whereby increasing the concentration decreased the relative aggregation rate, ln(v) (% day^-1), from 8.5 at 0.05 mg/mL to 4.4 at 100 mg/mL. The absolute aggregation rate (mol L^-1 h^-1) increased with the concentration following a rate order of approximately 1 up to a concentration of 25 mg/mL. Above this concentration, there was a transition to an apparently negative rate order of -1.1 up to 100 mg/mL. Several potential mechanisms were examined as possible explanations. A greater apparent conformational stability at 100 mg/mL was observed from an increase in the thermal transition midpoint (T_m) by 7-9 °C, relative to those at 1-4 mg/mL. The associated change in unfolding entropy (△S_vh) also increased by 14-18% at 25-100 mg/mL, relative to those at 1-4 mg/mL, indicating reduced conformational flexibility in the native ensemble. Addition of Tween or the crowding agents Ficoll and dextran, showed that neither surface adsorption, diffusion limitations nor simple volume crowding affected the aggregation rate. Fitting of kinetic data to a wide range of mechanistic models implied a reversible two-state conformational switch mechanism from aggregation-prone monomers (N*) into non-aggregating native forms (N) at higher concentrations. k_D measurements from DLS data also suggested a weak self-attraction while remaining colloidally stable, consistent with macromolecular self-crowding within weakly associated reversible oligomers. Such a model is also consistent with compaction of the native ensemble observed through changes in T_m and △S_vh.

NMR Reveals Functionally Relevant Thermally Induced Structural Changes within the Native Ensemble of G-CSF

Structure–function relationships in proteins refer to a trade-off between stability and bioactivity, molded by evolution of the molecule. Identifying which protein amino acid residues jeopardize global or local stability for the benefit of bioactivity would reveal residues pivotal to this structure–function trade-off. Here, we use ¹⁵N–¹H heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectroscopy to probe the microenvironment and dynamics of residues in granulocyte colony-stimulating factor (G-CSF) through thermal perturbation. From this analysis, we identified four residues (G4, A6, T133, and Q134) that we classed as significant to global stability, given that they all experienced large environmental and dynamic changes and were closely correlated to each other in their NMR characteristics. Additionally, we observe that roughly four structural clusters are subject to localized conformational changes or partial unfolding prior to global unfolding at higher temperature. Combining NMR observables with structure relaxation methods reveals that these structural clusters concentrate around loop AB (binding site III inclusive). This loop has been previously implicated in conformational changes that result in an aggregation prone state of G-CSF. Residues H43, V48, and S63 appear to be pivotal to an opening motion of loop AB, a change that is possibly also important for function. Hence, we present here an approach to profiling residues in order to highlight their potential roles in the two vital characteristics of proteins: stability and bioactivity.

A Conservative Point Mutation in a Dynamic Antigen-binding Loop of Human Immunoglobulin λ6 Light Chain Promotes Pathologic Amyloid Formation

Immunoglobulin light chain (LC) amyloidosis (AL) is a life-threatening human disease wherein free mono-clonal LCs deposit in vital organs. To determine what makes some LCs amyloidogenic, we explored patient-based amyloidogenic and non-amyloidogenic recombinant LCs from the λ6 subtype prevalent in AL. Hydrogen-deuterium exchange mass spectrometry, structural stability, proteolysis, and amyloid growth studies revealed that the antigen-binding CDR1 loop is the least protected part in the variable domain of λ6 LC, particularly in the AL variant. N32T substitution in CRD1 is identified as a driver of amyloid formation. Substitution N32T increased the amyloidogenic propensity of CDR1 loop, decreased its protection in the native structure, and accelerated amyloid growth in the context of other AL substitutions. The destabilizing effects of N32T propagated across the molecule increasing its dynamics in regions ∼30 Å away from the substitution site. Such striking long-range effects of a conservative point substitution in a dynamic surface loop may be relevant to Ig function. Comparison of patient-derived and engineered proteins showed that N32T interactions with other substitution sites must contribute to amyloidosis. The results suggest that CDR1 is critical in amyloid formation by other λ6 LCs.

Communication pathways bridge local and global conformations in an IgG4 antibody

The affinity of an antibody for its antigen is primarily determined by the specific sequence and structural arrangement of the complementarity-determining regions (CDRs). Recent evidence, however, points toward a nontrivial relation between the CDR and distal sites: variations in the binding strengths have been observed upon mutating residues separated from the paratope by several nanometers, thus suggesting the existence of a communication network within antibodies, whose extension and relevance might be deeper than insofar expected. In this work, we test this hypothesis by means of molecular dynamics (MD) simulations of the IgG4 monoclonal antibody pembrolizumab, an approved drug that targets the programmed cell death protein 1 (PD-1). The molecule is simulated in both the apo and holo states, totalling 4 μs of MD trajectory. The analysis of these simulations shows that the bound antibody explores a restricted range of conformations with respect to the apo one, and that the global conformation of the molecule correlates with that of the CDR. These results support the hypothesis that pembrolizumab featues a multi-scale hierarchy of intertwined global and local conformational changes. The analysis pipeline developed in this work is general, and it can help shed further light on the mechanistic aspects of antibody function.

Protein-protein interactions and reduced excluded volume increase dynamic binding capacity of dual salt systems in hydrophobic interaction chromatography

Deploying two salts in hydrophobic interaction chromatography can significantly increase dynamic binding capacities. Nevertheless, the mechanistic understanding of this phenomenon is lacking. Here, we investigate whether surface tension or ionic strength govern dynamic binding capacities of the chromatographic resin Toyopearl Butyl-650 M in dual salt systems. Small-angle X-ray scattering was employed to analyze the model proteins and the protein-resin adduct in the respective dual salt systems. The dual salt systems incorporate sodium citrate and a secondary sodium salt (acetate, sulfate, or phosphate). As model proteins, we used lysozyme, GFP, and a monoclonal antibody (adalimumab). Moreover, for the protein-resin adduct, we determined the model parameters of a self-avoiding random walk model fitted into the pair density distribution function of the SAXS data. Ionic strength is more predictive for dynamic binding capacities in HIC dual salt systems than surface tension. However, dynamic binding capacities still differ by up to 30 % between the investigated dual salt systems. The proteins exhibit extensive protein-protein interactions in the studied dual salt HIC buffers. We found a correlation of protein-protein interactions with the well-known Hofmeister series. For systems with elevated protein-protein interactions, adsorption isotherms deviate from Langmuirian behavior. This highlights the importance of lateral protein-protein interactions in protein adsorption, where monomolecular protein layers are usually assumed. SAXS analysis of the protein-resin adduct indicates an inverse correlation of the binding capacity and the excluded volume parameter. This is indicative of the deposition of proteins in the cavities of the stationary phase. We hypothesize that increasing protein-protein interactions allow the formation of attractive clusters and multilayers in the cavities, respectively.

Comparison of the pH- and thermally-induced fluctuations of a therapeutic antibody Fab fragment by molecular dynamics simulation

Successful development of protein therapeutics depends critically on achieving stability under a range of conditions. A deeper understanding of the drivers of instability across different stress conditions, will enable the engineering of more robust protein scaffolds. We compared the impacts of low pH and high temperature stresses on the structure of a humanized antibody fragment (Fab) A33, using atomistic molecular dynamics simulations, using a recent 2.5 Å crystal structure. This revealed that low-pH induced the loss of native contacts in the domain C_L. By contrast, thermal stress led to 5-7% loss of native contacts in all four domains, and simultaneous loss of >30% of native contacts in the V_L-V_H and C_L-C_H interfaces. This revealed divergent destabilising pathways under the two different stresses. The underlying cause of instability was probed using FoldX and Rosetta mutation analysis, and packing density calculations. These agreed that mutations in the C_L domain, and C_L-C_H1 interface have the greatest potential for stabilisation of Fab A33. Several key salt bridge losses underpinned the conformational change in C_L at low pH, whereas at high temperature, salt bridges became more dynamic, thus contributing to an overall destabilization. Lastly, the unfolding events at the two stress conditions exposed different predicted aggregation-prone regions (APR) to solvent, which would potentially lead to different aggregation mechanisms. Overall, our results identified the early stages of unfolding and stability-limiting regions of Fab A33, and the V_H and C_L domains as interesting future targets for engineering stability to both pH- and thermal-stresses simultaneously.

Conformational Ensembles of Antibodies Determine Their Hydrophobicity

A major challenge in the development of antibody biotherapeutics is their tendency to aggregate. One root cause for aggregation is exposure of hydrophobic surface regions to the solvent. Many current techniques predict the relative aggregation propensity of antibodies via precalculated scales for the hydrophobicity or aggregation propensity of single amino acids. However, those scales cannot describe the nonadditive effects of a residue’s surrounding on its hydrophobicity. Therefore, they are inherently limited in their ability to describe the impact of subtle differences in molecular structure on the overall hydrophobicity. Here, we introduce a physics-based approach to describe hydrophobicity in terms of the hydration free energy using grid inhomogeneous solvation theory (GIST). We apply this method to assess the effects of starting structures, conformational sampling, and protonation states on the hydrophobicity of antibodies. Our results reveal that high-quality starting structures, i.e., crystal structures, are crucial for the prediction of hydrophobicity and that conformational sampling can compensate errors introduced by the starting structure. On the other hand, sampling of protonation states only leads to good results when combined with high-quality structures, whereas it can even be detrimental otherwise. We conclude by pointing out that a single static homology model may not be adequate for predicting hydrophobicity.

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.

In situ neutron scattering of antibody adsorption during protein A chromatography

A deeper understanding of the nanoscale and mesoscale structure of chromatographic adsorbents and the distribution of proteins within the media, is critical to a mechanistic understanding of separation processes using these materials. Characterisation of the media's architecture at this scale and protein adsorption within, is challenging using conventional techniques. In this study, we propose a novel resin characterisation technique that enables in-situ measurement of the structure of the adsorbed protein layer within the resin, under typical chromatographic conditions. A quartz flow-through cell was designed and fabricated for use with Small Angle Neutron Scattering (SANS), in order to measure the nanoscale to mesoscale structures of a silica based protein A chromatography resin during the monoclonal antibody sorption process. We were able to examine the pore-to-pore (˜133 nm) and pore size (˜63 nm) correlations of the resin and the in-plane adsorbed antibody molecules (˜ 4.2 nm) correlation at different protein loadings and washing buffers, in real time using a contrast matching approach. When 0.03 M sodium phosphate with 1 M urea and 10 % isopropanol buffer, pH 8, was introduced into the system as a wash buffer, it disrupted the system's order by causing partial unfolding of the adsorbed antibody, as evidenced by a loss of the in-plane protein correlation. This method offers new ways to investigate the nanoscale structure and ligand immobilisation within chromatography resins; and perhaps most importantly understand the in-situ behaviour of adsorbed proteins within the media under different mobile phase conditions within a sample environment replicating that of a chromatography column.

An in vivo platform to select and evolve aggregation-resistant proteins

Protein biopharmaceuticals are highly successful, but their utility is compromised by their propensity to aggregate during manufacture and storage. As aggregation can be triggered by non-native states, whose population is not necessarily related to thermodynamic stability, prediction of poorly-behaving biologics is difficult, and searching for sequences with desired properties is labour-intensive and time-consuming. Here we show that an assay in the periplasm of E. coli linking aggregation directly to antibiotic resistance acts as a sensor for the innate (un-accelerated) aggregation of antibody fragments. Using this assay as a directed evolution screen, we demonstrate the generation of aggregation resistant scFv sequences when reformatted as IgGs. This powerful tool can thus screen and evolve ‘manufacturable’ biopharmaceuticals early in industrial development. By comparing the mutational profiles of three different immunoglobulin scaffolds, we show the applicability of this method to investigate protein aggregation mechanisms important to both industrial manufacture and amyloid disease.

Protein aggregation remains a significant challenge for manufacturing of protein biopharmaceuticals. Here, the authors demonstrate the use of directed evolution and an assay for in vivo innate protein aggregation-propensity to generate aggregation-resistant scFv fragments.

Atomistic Modeling of Scattering Curves for Human IgG1/4 Reveals New Structure-Function Insights

Small angle x-ray and neutron scattering are techniques that give solution structures for large macromolecules. The creation of physically realistic atomistic models from known high-resolution structures to determine joint x-ray and neutron scattering best-fit structures offers a, to our knowledge, new method that significantly enhances the utility of scattering. To validate this approach, we determined scattering curves for two human antibody subclasses, immunoglobulin G (IgG) 1 and IgG4, on five different x-ray and neutron instruments to show that these were reproducible, then we modeled these by Monte Carlo simulations. The two antibodies have different hinge lengths that connect their antigen-binding Fab and effector-binding Fc regions. Starting from 231,492 and 190,437 acceptable conformations for IgG1 and IgG4, respectively, joint x-ray and neutron scattering curve fits gave low goodness-of-fit R factors for 28 IgG1 and 2748 IgG4 structures that satisfied the disulphide connectivity in their hinges. These joint best-fit structures showed that the best-fit IgG1 models had a greater separation between the centers of their Fab regions than those for IgG4, in agreement with their hinge lengths of 15 and 12 residues, respectively. The resulting asymmetric IgG1 solution structures resembled its crystal structure. Both symmetric and asymmetric solution structures were determined for IgG4. Docking simulations with our best-fit IgG4 structures showed greater steric clashes with its receptor to explain its weaker FcγRI receptor binding compared to our best-fit IgG1 structures with fewer clashes and stronger receptor binding. Compared to earlier approaches for fitting molecular antibody structures by solution scattering, we conclude that this joint fit approach based on x-ray and neutron scattering data, combined with Monte Carlo simulations, significantly improved our understanding of antibody solution structures. The atomistic nature of the output extended our understanding of known functional differences in Fc receptor binding between IgG1 and IgG4.