Protein-protein interactions in dilute to concentrated solutions: α-chymotrypsinogen in acidic conditions

Human serum albumin as a potential drug delivery system for N-methylated hot spot insulin analogs inhibiting hormone aggregation

The purpose of this study was to investigate whether Human Serum Albumin (HSA) can bind N-methylated analogs of hot spots of native insulin. Three N-methylated derivatives of the A13-A19 fragment of native insulin were used: L(N-Me)YQLENY (1), LYQ(N-Me)LENY (2), and L(N-Me)YQ(N-Me)LENY (3). The studied N-methylated insulin fragments possess inhibiting potential against hormone aggregation. A variety of research techniques, including spectroscopic methods and microscopy assays, were used to study the interaction of HSA with the N-methylated insulin fragments. Based on spectroscopic measurements with Congo Red and Thioflavin T, all the analyzed N-methylated peptides were able to interact with the HSA surface. The CD spectrum registered for HSA in the presence of L(N-Me)YQLENY showed the smallest content of α-helix conformation, indicating the most compact HSA structure. Based on the results of MST, the dissociation constants (Kd) for complexes of HSA and peptides 1-3 were 19.2 nM (complex 1), 15.6 nM (complex 2), and 8.07 nM (complex 3). Microscopy assays, dynamic light scattering measurements as well as computer simulation of protein-ligand interaction also confirmed the possibility of docking the N-methylated inhibitors within HSA.

Combined Effects of Pressure and Ionic Strength on Protein-Protein Interactions: An Empirical Approach

Proteins are exposed to hydrostatic pressure (HP) in a variety of ecosystems as well as in processing steps such as freeze-thaw, cell disruption, sterilization, and homogenization, yet pressure effects on protein-protein interactions (PPIs) remain underexplored. With the goal of contributing toward the expanded use of HP as a fundamental control parameter in protein research, processing, and engineering, small-angle X-ray scattering was used to examine the effects of HP and ionic strength on ovalbumin, a model protein. Based on an extensive data set, we develop an empirical method for scaling PPIs to a master curve by combining HP and osmotic effects. We define an effective pressure parameter that has been shown to successfully apply to other model protein data available in the literature, with deviations evident for proteins that do not follow the apparent Hofmeister series. The limitations of the empirical scaling are discussed in the context of the hypothesized underlying mechanisms.

Antibody association in solution: cluster distributions and mechanisms

Understanding factors that affect the clustering and association of antibodies molecules in solution is critical to their development as therapeutics. For 19 different monoclonal antibody (mAb) solutions, we measured the viscosities, the second virial coefficients, the Kirkwood-Buff integrals, and the cluster distributions of the antibody molecules as functions of protein concentration. Solutions were modeled using the statistical-physics Wertheim liquid-solution theory, representing antibodies as Y-shaped molecular structures of seven beads each. We found that high-viscosity solutions result from more antibody molecules per cluster. Multi-body properties such as viscosity are well predicted experimentally by the 2-body Kirkwood-Buff quantity, G22, but not by the second virial coefficient, B22, and well-predicted theoretically from the Wertheim protein-protein sticking energy. Weakly interacting antibodies are rate-limited by nucleation; strongly interacting ones by propagation. This approach gives a way to relate micro to macro properties of solutions of associating proteins.

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.

Predicting Colloidal Stability of High-Concentration Monoclonal Antibody Formulations in Common Pharmaceutical Buffers Using Improved Polyethylene Glycol Induced Protein Precipitation Assay

Colloidal stability is an important consideration when developing high concentration mAb formulations. PEG-induced protein precipitation is a commonly used assay to assess the colloidal stability of protein solutions. However, the practical usefulness and the current theoretical model for this assay have yet to be verified over a large formulation space across multiple mAbs and mAb-based modalities. In the present study, we used PEG-induced protein precipitation assays to evaluate colloidal stability of 3 mAbs in 24 common formulation buffers at 20 and 5 °C. These prediction assays were conducted at low protein concentration (1 mg/mL). We also directly characterized high concentration (100 mg/mL) formulations for cold-induced phase separation, turbidity, and concentratibility by ultrafiltration. This systematic study allowed analysis of the correlation between the results of low concentration assays and the high concentration attributes. The key findings of this study include the following: (1) verification of the usefulness of three different parameters (Cmid, μB, and Tcloud) from PEG-induced protein precipitation assays for ranking colloidal stability of high concentration mAb formulations; (2) a new method to implement PEG-induced protein precipitation assay suitable for high throughput screening with low sample consumption; (3) improvement in the theoretical model for calculating robust thermodynamic parameters of colloidal stability (μB and εB) that are independent of specific experimental settings; (4) systematic evaluation of the effects of pH and buffer salts on colloidal stability of mAbs in common formulation buffers. These findings provide improved theoretical and practical tools for assessing the colloidal stability of mAbs and mAb-based modalities during formulation development.

Characterizing Protein-Protein Interactions and Viscosity of a Monoclonal Antibody from Low to High Concentration Using Small-Angle X-ray Scattering and Molecular Dynamics Simulations

Understanding protein-protein interactions and formation of reversible oligomers (clusters) in concentrated monoclonal antibody (mAb) solutions is necessary for designing stable, low viscosity (η) concentrated formulations for processing and subcutaneous injection. Here we characterize the strength (K) of short-range anisotropic attractions (SRA) for 75-200 mg/mL mAb2 solutions at different pH and cosolute conditions by analyzing structure factors (Seff(q)) from small-angle X-ray scattering (SAXS) using coarse-grained molecular dynamics simulations. Best fit simulations additionally provide cluster size distributions, fractal dimensions, cluster occluded volume, and mAb coordination numbers. These equilibrium properties are utilized in a model to account for increases in viscosity caused by occluded volume in the clusters (packing effects) and dissipation of stress across lubricated fractal clusters. Seff(q) is highly sensitive to K at 75 mg/mL where mAbs can mutually align to form SRA contacts but becomes less sensitive at 200 mg/mL as steric repulsion due to packing becomes dominant. In contrast, η at 200 mg/mL is highly sensitive to SRA and the average cluster size from SAXS/simulation, which is observed to track the cluster relaxation time from shear thinning. By analyzing the distribution of sub-bead hot spots on the 3D mAb surface, we identify a strongly attractive hydrophobic patch in the complementarity determining region (CDR) at pH 4.5 that contributes to the high K and consequently large cluster sizes and high η. Adding NaCl screens electrostatic interactions and increases the impact of hydrophobic attraction on cluster size and raises η, whereas nonspecific binding of Arg attenuates all SRA, reducing η. The hydrophobic patch is absent at higher pH values, leading to smaller K, smaller clusters, and lower η. This work constitutes a first attempt to use SAXS and CG modeling to link both structural and rheological properties of concentrated mAb solutions to the energetics of specific hydrophobic patches on mAb surfaces. As such, our work opens an avenue for future research, including the possibility of designing coarse-grained models with physically meaningful interacting hot spots.

Role of Domain-Domain Interactions on the Self-Association and Physical Stability of Monoclonal Antibodies: Effect of pH and Salt

Monoclonal antibodies (mAbs) make up a major class of biotherapeutics with a wide range of clinical applications. Their physical stability can be affected by various environmental factors. For instance, an acidic pH can be encountered during different stages of the mAb manufacturing process, including purification and storage. Therefore, understanding the behavior of flexible mAb molecules in acidic solution environments will benefit the development of stable mAb products. This study used small-angle X-ray scattering (SAXS) and complementary biophysical characterization techniques to investigate the conformational flexibility and protein-protein interactions (PPI) of a model mAb molecule under near-neutral and acidic conditions. The study also characterized the interactions between Fab and Fc fragments under the same buffer conditions to identify domain-domain interactions. The results suggest that solution pH significantly influences mAb flexibility and thus could help mAbs remain physically stable by maximizing local electrostatic repulsions when mAbs become crowded in solution. Under acidic buffer conditions, both Fab and Fc contribute to the repulsive PPI observed among the full mAb at a low ionic strength. However, as ionic strength increases, hydrophobic interactions lead to the self-association of Fc fragments and, subsequently, could affect the aggregation state of the mAb.

Effect of Protein–Protein Interactions on Translational Diffusion of Spheroidal Proteins

One of the commonly accepted approaches to estimate protein–protein interactions (PPI) in aqueous solutions is the analysis of their translational diffusion. The present review article observes a phenomenological approach to analyze PPI effects via concentration dependencies of self- and collective translational diffusion coefficient for several spheroidal proteins derived from the pulsed field gradient NMR (PFG NMR) and dynamic light scattering (DLS), respectively. These proteins are rigid globular α-chymotrypsin (ChTr) and human serum albumin (HSA), and partly disordered α-casein (α-CN) and β-lactoglobulin (β-Lg). The PPI analysis enabled us to reveal the dominance of intermolecular repulsion at low ionic strength of solution (0.003–0.01 M) for all studied proteins. The increase in the ionic strength to 0.1–1.0 M leads to the screening of protein charges, resulting in the decrease of the protein electrostatic potential. The increase of the van der Waals potential for ChTr and α-CN characterizes their propensity towards unstable weak attractive interactions. The decrease of van der Waals interactions for β-Lg is probably associated with the formation of stable oligomers by this protein. The PPI, estimated with the help of interaction potential and idealized spherical molecular geometry, are in good agreement with experimental data.

CENTAUR-The small- and wide-angle neutron scattering diffractometer/spectrometer for the Second Target Station of the Spallation Neutron Source

CENTAUR has been selected as one of the eight initial instruments to be built at the Second Target Station (STS) of the Spallation Neutron Source at Oak Ridge National Laboratory. It is a small-angle neutron scattering (SANS) and wide-angle neutron scattering (WANS) instrument with diffraction and spectroscopic capabilities. This instrument will maximally leverage the high brightness of the STS source, the state-of-the-art neutron optics, and a suite of detectors to deliver unprecedented capabilities that enable measurements over a wide range of length scales with excellent resolution, measurements on smaller samples, and time-resolved investigations of evolving structures. Notably, the simultaneous WANS and diffraction capability will be unique among neutron scattering instruments in the United States. This instrument will provide much needed capabilities for soft matter and polymer sciences, geology, biology, quantum condensed matter, and other materials sciences that need in situ and operando experiments for kinetic and/or out-of-equilibrium studies. Beam polarization and a high-resolution chopper will enable detailed structural and dynamical investigations of magnetic and quantum materials. CENTAUR's excellent resolution makes it ideal for low-angle diffraction studies of highly ordered large-scale structures, such as skyrmions, shear-induced ordering in colloids, and biomembranes. Additionally, the spectroscopic mode of this instrument extends to lower momentum transfers than are currently possible with existing spectrometers, thereby providing a unique capability for inelastic SANS studies.

NMR and dynamic light scattering give different diffusion information for short-living protein oligomers. Human serum albumin in water solutions of metal ions

Diffusive behavior of human serum albumin (HSA) in the presence of Mg²⁺ and Cu²⁺ ions was studied by pulsed field gradient nuclear magnetic resonance (PFG NMR) and dynamic light scattering (DLS). According to NMR data yielding measurements of HSA self-diffusion coefficient, a weighted average of the protein monomers and oligomers diffusion mobility in the presence of metal ions was observed. While the short-time collective diffusion measured by DLS showed one type of diffusing species in ion-free HSA solution and two molecular forms of HSA in the presence of metal ions. The light intensity correlation function analysis showed that HSA oligomers have a limited lifetime (lower limit is about 0.4 ms) intermediate between characteristic time scales of PFG NMR and DLS experiments. For a theoretical description of concentration dependence of HSA self- and collective diffusion coefficients, the phenomenological approach based on the frictional formalism of non-equilibrium thermodynamics was used (Vink theory), allowing analysis of the solvent-solute and solute-solute interactions in protein solutions. In the presence of metal ions, a significant increase of HSA protein-protein friction coefficient was shown. Based on theoretical analysis of collective diffusion data, the positive values of second virial coefficients A₂ for HSA monomers were obtained. The A₂ values were found to be higher for the HSA with metal ions compared with the ion-free HSA solution. This is due to the more pronounced contribution of repulsion in protein-protein interactions of HSA monomers in the presence of Mg²⁺ and Cu²⁺ ions.

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.

Computational models for studying physical instabilities in high concentration biotherapeutic formulations

Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

Revisit PEG-Induced Precipitation Assay for Protein Solubility Assessment of Monoclonal Antibody Formulations

PURPOSE

Protein solubility is an important attribute of pharmaceutical monoclonal antibody (MAb) formulations, particularly at high MAb concentrations. PEG-induced protein precipitation has been routinely used to assess protein solubility. To provide insights for better understanding and implementation of PEG-induced protein precipitation assay, this work compares different solubility measures and examines their relevance to loss of protein solubility in concentrated formulations.

METHODS

Solubility of a MAb in 15 formulations was evaluated using PEG-induced precipitation assay. Three apparent protein solubility measures, the middle-point and onset PEG concentrations (c_mid and c_onset) as well as the binding free energy (μ_B), were obtained from the PEG-induced protein precipitation assay and compared to the DLS protein interaction parameter (k_D). Visual inspection of loss of protein solubility in concentrated formulations during storage was used to further examine the discrepancy of protein solubility ranking by these measures.

RESULTS

PEG-induced precipitation assay predicted overall protein solubility ranking similar to that by DLS k_D. However, for three formulations with ionic excipients NaCl, Arg·Cl, and Arg·Glu·Cl, PEG-induced precipitation assay yielded more accurate predictions compared to DLS k_D measurements. Furthermore, μ_B showed superior ability in distinguishing protein solubility for these formulations.

CONCLUSIONS

This study demonstrated good correlations between the protein solubility measures obtained from PEG-induced precipitation experiments and DLS k_D measurement. It also provides one example in which protein solubility ranking by binding free energy is more accurate than the other measures. The results support the theoretical proposition that μ_B has a potential to serve as standard protein solubility measure.

The Role of pH and Ionic Strength in the Attraction-Repulsion Balance of Fibrinogen Interactions

Fibrinogen (Fg) self-assembly is sensitive to the physicochemical properties of an environment like pH and ionic strength. These parameters tune the direction and strength of noncovalent physical driving forces determining protein intermolecular interactions. The attraction-repulsion balance in intermolecular interactions of the multidomain protein Fg at pH values 3.5, 7.4, and 9.5 and varying ionic strengths of the water medium has been analyzed by the complex diffusive approach, proposed by us previously. The concentration dependence of protein collective diffusion was analyzed within the phenomenological approach, based on the frictional formalism of nonequilibrium thermodynamics proposed by H. Vink. The analysis of protein diffusion data has shown the fundamental difference in the physical nature and direction of interaction forces between protein molecules at different conditions. The paired interaction potential of protein molecules was characterized in terms of second virial coefficients and Hamaker constants within the Deryaguin-Landau-Verwey-Overbeek theory and the "porous" colloid particle model. Our results indicated the maximum Hamaker constant and dominance of the van der Waals attraction between Fg molecules at pH 7.4. The increase in pH up to 9.5 results in the zero values of the second virial coefficient and Hamaker constant, corresponding to the full reciprocal compensation for electrostatic repulsion and van der Waals attraction. In the acidic medium (pH 3.5), the strong electrostatic repulsion substantially exceeds the van der Waals attraction. A high ionic strength is characterized by a significant decrease of all intermolecular interactions, which is expressed in almost zero values of virial coefficients and the Hamaker constant. Thus, it is experimentally shown that the physiological conditions of the Fg environment (pH 7.4 and slight ionic strength) provide a high probability for peak physical attraction between fibrinogen molecules, which is used in nature to facilitate blood clotting.

Probing interactions of therapeutic antibodies with serum via second virial coefficient measurements

Antibody-based therapeutics are the fastest-growing drug class on the market, used to treat aggressive forms of cancer, chronic autoimmune conditions, and numerous other disease states. Although the specificity, affinity, and versatility of therapeutic antibodies can provide an advantage over traditional small-molecule drugs, their development and optimization can be much more challenging and time-consuming. This is, in part, because the ideal formulation buffer systems used for in vitro characterization inadequately reflect the crowded biological environments (serum, endosomal lumen, etc.) that these drugs experience once administered to a patient. Such environments can perturb the binding of antibodies to their antigens and receptors, as well as homo- and hetero-aggregation, thereby altering therapeutic effect and disposition in ways that are incompletely understood. Although excluded volume effects are classically thought to favor binding, weak interactions with co-solutes in crowded conditions can inhibit binding. The second virial coefficient (B₂) parameter quantifies such weak interactions and can be determined by a variety of techniques in dilute solution, but analogous methods in complex biological fluids are not well established. Here, we demonstrate that fluorescence correlation spectroscopy is able to measure diffusive B₂-values directly in undiluted serum. Apparent second virial coefficient (B_2,app) measurements of antibodies in serum reveal that changes in the balance between attractive and repulsive interactions can dramatically impact global nonideality. Furthermore, our findings suggest that the approach of isolating specific components and completing independent cross-term virial coefficient measurements may not be an effective approach to characterizing nonideality in serum. The approach presented here could enrich our understanding of the effects of biological environments on proteins in general and advance the development of therapeutic antibodies and other protein-based therapeutics.

SANS quantification of bound water in water-soluble polymers across multiple concentration regimes

Contrast-variation small-angle neutron scattering (CV-SANS) is a widely used technique for quantifying hydration water in soft matter systems, but it is predominantly applied in the dilute regime or for systems with a well-defined structure factor. Here, CV-SANS was used to quantify the number of hydration water molecules associating with three water-soluble polymers with different critical solution temperatures and types of water-solute interactions in dilute, semidilute, and concentrated solution through the exploration of novel methods of data fitting and analysis. Multiple SANS fitting workflows with varying levels of model assumptions were evaluated and compared to give insight into SANS model selection. These fitting pathways ranged from general, model-free algorithms to more standard form and structure factor fitting. In addition, Monte Carlo bootstrapping was evaluated as a method to estimate parameter uncertainty through simulation of technical replicates. The most robust fitting workflow for dilute solutions was found to be form factor fitting without CV-SANS (i.e. polymer in 100% D2O). For semidilute and concentrated solutions, while the model-free approach can be mathematically defined for CV-SANS data, the addition of a structure factor imposes physical constraints on the optimization problem, suggesting that the optimal fitting pathway should include appropriate form and structure factor models. The measured hydration numbers were consistent with the number of tightly bound water molecules associated with each monomer unit, and the concentration dependence of the hydration number was largely governed by the chemistry-specific interactions between water and polymer. Polymers with weaker water-polymer interactions (i.e. those with fewer hydration water molecules) were found to have more bound water at higher concentrations than those with stronger water-polymer interactions due to the increase in the number of forced water-polymer contacts in the concentrated system. This SANS-based method to count hydration water molecules can be applied to polymers in any concentration regime, which will lead to improved understanding of water-polymer interactions and their impact on materials design.

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.

Product-Specific Impact of Viscosity Modulating Formulation Excipients During Ultra-High Concentration Biotherapeutics Drug Product Development

Developing ultra-high concentration biotherapeutics drug products can be challenging due to increased viscosity, processing, and stability issues. Excipients used to alleviate these concerns are traditionally evaluated at lower protein concentrations. This study investigates whether classically known modulators of stability and viscosity at low (<50 mg/mL) to high (>50 - 150 mg/mL) protein concentrations are beneficial in ultra-high (>150 mg/mL) concentration protein formulations and drug products. This study evaluates the effect of arginine monohydrochloride, proline, and lysine monohydrochloride on viscosity and concentratability at different high and ultra-high protein concentrations using a monoclonal antibody, mAbN, formulation as a candidate protein system. The effect of excipients on the viscosity and concentratability (rate and extent) was different at high versus ultra-high protein concentrations. These results highlight that classical excipients in literature known to modulate protein interactions at low protein concentrations and reduce viscosity at high protein concentrations may need to be evaluated at target protein concentrations in a product-specific manner while developing ultra-high concentration biologics drug products.

Temperature Dependence of Protein Solution Viscosity and Protein-Protein Interactions: Insights into the Origins of High-Viscosity Protein Solutions

Protein solution viscosity (η) as a function of temperature was measured at a series of protein concentrations under a range of formulation conditions for two monoclonal antibodies (MAbs) and a globular protein (aCgn). Based on theoretical arguments, a strong temperature dependence for protein-protein interactions (PPI) indicates highly anisotropic, short-ranged attractions that could lead to higher solution viscosities. The semi-empirical Ross-Minton model was used to determine the apparent intrinsic viscosity, shape, and "crowding" factors for each protein as a function of temperature and formulation conditions. The apparent intrinsic viscosity was independent of temperature for aCgn, while a slight decrease with increasing temperature was observed for the MAbs. The temperature dependence of solution viscosity was analyzed using the Andrade-Eyring equation to determine the effective activation energy of viscous flow (E_a,η). While E_a,η values were different for each protein, they were independent of formulation conditions for a given protein. PPI were quantified via the osmotic second virial coefficient (B₂₂) and the protein diffusion interaction parameter (k_D) as a function of temperature under the same formulation conditions as the viscosity measurements. Net interactions ranged from strongly attractive to repulsive by changing formulation pH and ionic strength for each protein. Overall, larger activation energies for PPI corresponded to larger activation energies for η, and those were predictive of the highest η values at higher protein concentrations.

A Rapid, Small-Volume Approach to Evaluate Protein Aggregation at Air-Water Interfaces

Non-native protein aggregation is a common concern for biopharmaceuticals. A given protein may aggregate through a variety of mechanisms that depend on solution and physico-chemical stress conditions. A thorough evaluation of aggregation behavior for a protein under all conditions of interest is necessary to ensure drug safety and efficacy. This work introduces a rapid, small-volume approach to evaluate protein aggregation propensity upon exposure to air-water interfaces (AWI). A microtensiometer apparatus is used to aerate a small volume of a protein solution with microbubbles for short periods of time (≤10 s). Sub-visible particles that form are captured and analyzed using backgrounded membrane imaging. This allows one to capture all particles in the solution while being sample sparing. The surface-mediated aggregation of two model monoclonal antibodies (MAbs) and a globular protein (aCgn) was tested as a function of pH and temperature. Temperature had a negligible effect under the rapid interface turnover time scales with this technique. Electrostatic protein-protein interactions, mediated by pH changes, were more influential for particle formation via AWI. Nonionic surfactants substantially reduced particle formation for all MAb solutions, but not aCgn. The results are contrasted with expectations when exposing samples to much larger air-water interfacial stress.

Toward Biotherapeutics Formulation Composition Engineering using Site-Identification by Ligand Competitive Saturation (SILCS)

Formulation of protein-based therapeutics employ advanced formulation and analytical technologies for screening various parameters such as buffer, pH, and excipients. At a molecular level, physico-chemical properties of a protein formulation depend on self-interaction between protein molecules, protein-solvent and protein-excipient interactions. This work describes a novel in silico approach, SILCS-Biologics, for structure-based modeling of protein formulations. SILCS Biologics is based on the Site-Identification by Ligand Competitive Saturation (SILCS) technology and enables modeling of interactions among different components of a formulation at an atomistic level while accounting for protein flexibility. It predicts potential hotspot regions on the protein surface for protein-protein and protein-excipient interactions. Here we apply SILCS-Biologics on a Fab domain of a monoclonal antibody (mAbN) to model Fab-Fab interactions and interactions with three amino acid excipients, namely, arginine HCl, proline and lysine HCl. Experiments on 100 mg/ml formulations of mAbN showed that arginine increased, lysine reduced, and proline did not impact viscosity. We use SILCS-Biologics modeling to explore a structure-based hypothesis for the viscosity modulating effect of these excipients. Current efforts are aimed at further validation of this novel computational framework and expanding the scope to model full mAb and other protein therapeutics.

On the Aggregation and Nucleation Mechanism of the Monoclonal Antibody Anti-CD20 Near Liquid-Liquid Phase Separation (LLPS)

The crystallization of Anti-CD20, a full-length monoclonal antibody, has been studied in the PEG400/Na2SO4/Water system near Liquid-Liquid Phase Separation (LLPS) conditions by both sitting-drop vapour diffusion and batch methods. In order to understand the Anti-CD20 crystallization propensity in the solvent system of different compositions, we investigated some measurable parameters, normally used to assess protein conformational and colloidal stability in solution, with the aim to understand the aggregation mechanism of this complex biomacromolecule. We propose that under crystallization conditions a minor population of specifically aggregated protein molecules are present. While this minor species hardly contributes to the measured average solution behaviour, it induces and promotes crystal formation. The existence of this minor species is the result of the LLPS occurring concomitantly under crystallization conditions.

Understanding mAb aggregation during low pH viral inactivation and subsequent neutralization

Monoclonal antibodies (mAbs) and related recombinant proteins continue to gain importance in the treatment of a great variety of diseases. Despite significant advances, their manufacturing can still present challenges owing to their molecular complexity and stringent regulations with respect to product purity, stability, safety, and so forth. In this context, protein aggregates are of particular concern due to their immunogenic potential. During manufacturing, mAbs routinely undergo acidic treatment to inactivate viral contamination, which can lead to their aggregation and thereby to product loss. To better understand the underlying mechanism so as to propose strategies to mitigate the issue, we systematically investigated the denaturation and aggregation of two mAbs at low pH as well as after neutralization. We observed that at low pH and low ionic strength, mAb surface hydrophobicity increased whereas molecular size remained constant. After neutralization of acidic mAb solutions, the fraction of monomeric mAb started to decrease accompanied by an increase on average mAb size. This indicates that electrostatic repulsion prevents denatured mAb molecules from aggregation under acidic pH and low ionic strength, whereas neutralization reduces this repulsion and coagulation initiates. Limiting denaturation at low pH by d-sorbitol addition or temperature reduction effectively improved monomer recovery after neutralization. Our findings might be used to develop innovative viral inactivation procedures during mAb manufacturing that result in higher product yields.

Protein-protein interactions and water activity coefficients can be used to aid a first excipient choice in protein formulations

With respect to all biopharmaceuticals marketed to date, monoclonal antibodies represent the largest fraction with more than 48% market share (2012). However, the development of biopharmaceutical formulations is a challenging task, and time-consuming and cost-intensive high-throughput screenings are still state-of-the-art in formulation design. These screening techniques are almost exclusively based on heuristic decisions thus the benefit in terms of mechanistic understanding is often unclear. It requires novel, physical-sound methods to enhance/optimize future formulation development, ideally by understanding molecular interactions in these complex solutions. A suitable and evaluated measure-of-choice to characterize protein-protein interactions in aqueous protein solutions is the second osmotic virial coefficient B₂₂ which can be measured using static light scattering techniques. Furthermore B₂₂ can be modeled/predicted via the extended mxDLVO model for protein-protein interactions in the presence of single excipients and excipient-mixtures. Building up on this approach, giving an additional insight into water-water and water-excipient interactions, the thermodynamic equation-of-state ePC-SAFT is used to calculate water activity coefficients in the presence of excipient-mixtures. Immunoglobulin G (IgG) was chosen as a model protein to predict B₂₂-values for IgG in the presence of model excipient-mixtures (trehalose-NaCl, l-histidine-trehalose, l-histidine-NaCl). The combination of water activity coefficients and B₂₂ allows to quickly identify a first guess on suitable formulation conditions that then can be further evaluated with existing methods/knowledge.

Measuring the effects of macromolecular crowding on antibody function with biolayer interferometry

Biotherapeutic proteins are commonly dosed at high concentrations into the blood, which is an inherently complex, crowded solution with substantial protein content. The effects of macromolecular crowding may lead to an appreciable level of non-specific hetero-association in this physiological environment. Therefore, developing a method to characterize the diverse consequences of non-specific interactions between proteins under such non-ideal, crowded conditions, which deviate substantially from those commonly employed for in vitro characterization, is vital to achieving a more complete picture of antibody function in a biological context. In this study, we investigated non-specific interactions between human serum albumin (HSA) and two monoclonal antibodies (mAbs) by static light scattering and determined these interactions are both ionic strength-dependent and mAb-dependent. Using biolayer interferometry (BLI), we assessed the effect of HSA on antigen binding by mAbs, demonstrating that these non-specific interactions have a functional impact on mAb:antigen interactions, particularly at low ionic strength. While this effect is mitigated at physiological ionic strength, our in vitro data support the notion that HSA in the blood may lead to non-specific interactions with mAbs in vivo, with a potential impact on their interactions with antigen. Furthermore, the BLI method offers a high-throughput advantage compared to orthogonal techniques such as analytical ultracentrifugation and is amenable to a greater variety of solution conditions compared to nuclear magnetic resonance spectroscopy. Our study demonstrates that BLI is a viable technology for examining the impact of non-specific interactions on specific biologically relevant interactions, providing a direct method to assess binding events in crowded conditions.

Light Scattering to Quantify Protein-Protein Interactions at High Protein Concentrations

Static and dynamic (laser) light scattering (SLS and DLS, respectively) can be used to measure the so-called weak or colloidal protein-protein interactions in solution from low to high protein concentrations (c₂). This chapter describes a methodology to measure protein-protein self-interactions using SLS and DLS, with illustrative examples for monoclonal antibody solutions from low to high protein concentrations (c₂ ~ 1-10² g/L).

Science and art of protein formulation development

Protein pharmaceuticals have become a significant class of marketed drug products and are expected to grow steadily over the next decade. Development of a commercial protein product is, however, a rather complex process. A critical step in this process is formulation development, enabling the final product configuration. A number of challenges still exist in the formulation development process. This review is intended to discuss these challenges, to illustrate the basic formulation development processes, and to compare the options and strategies in practical formulation development.

Predicting High-Concentration Interactions of Monoclonal Antibody Solutions: Comparison of Theoretical Approaches for Strongly Attractive Versus Repulsive Conditions

Nonspecific protein-protein interactions of a monoclonal antibody were quantified experimentally using light scattering from low to high protein concentrations (c₂) and compared with prior work for a different antibody that yielded qualitatively different behavior. The c₂ dependence of the excess Rayleigh ratio (R^ex) provided the osmotic second virial coefficient (B₂₂) at low c₂ and the static structure factor (S_q=0) at high c₂, as a function of solution pH, total ionic strength (TIS), and sucrose concentration. Net repulsive interactions were observed at pH 5, with weaker repulsions at higher TIS. Conversely, attractive electrostatic interactions were observed at pH 6.5, with weaker attractions at higher TIS. Refined coarse-grained models were used to fit model parameters using experimental B₂₂ versus TIS data. The parameters were used to predict high-c₂ R^ex values via Monte Carlo simulations and separately with Mayer-sampling calculations of higher-order virial coefficients. For both methods, predictions for repulsive to mildly attractive conditions were quantitatively accurate. However, only qualitatively accurate predictions were practical for strongly attractive conditions. An alternative, higher resolution model was used to show semiquantitatively and quantitatively accurate predictions of strong electrostatic attractions at low c₂ and low ionic strength.

Dynamic cluster formation determines viscosity and diffusion in dense protein solutions

We develop a detailed description of protein translational and rotational diffusion in concentrated solution on the basis of all-atom molecular dynamics simulations in explicit solvent. Our systems contain up to 540 fully flexible proteins with 3.6 million atoms. In concentrated protein solutions (100 mg/mL and higher), the proteins ubiquitin and lysozyme, as well as the protein domains third IgG-binding domain of protein G and villin headpiece, diffuse not as isolated particles, but as members of transient clusters between which they constantly exchange. A dynamic cluster model nearly quantitatively explains the increase in viscosity and the decrease in protein diffusivity with protein volume fraction, which both exceed the predictions from widely used colloid models. The Stokes-Einstein relations for translational and rotational diffusion remain valid, but the effective hydrodynamic radius grows linearly with protein volume fraction. This increase follows the observed increase in cluster size and explains the more dramatic slowdown of protein rotation compared with translation. Baxter's sticky-sphere model of colloidal suspensions captures the concentration dependence of cluster size, viscosity, and rotational and translational diffusion. The consistency between simulations and experiments for a diverse set of soluble globular proteins indicates that the cluster model applies broadly to concentrated protein solutions, with equilibrium dissociation constants for nonspecific protein-protein binding in the Kd ≈ 10-mM regime.

Study of the complex coacervation mechanism between the lysing enzyme from T. harzianum and polyallylamine hydrochloride

Complex coacervation was achieved by mixing the lysing enzyme from T. harzianum (LYS) with polyallylamine hydrochloride (PAH). We show in this work that the study electrostatic complexes conformation can lead to the formation of dense complexes. We systematically investigated the effects of pH and the mass ratio on the structure and properties of the complex. The different transition phases (pHc, pHφ1, and pHφ2) have been determined using dynamic light scattering, zeta potential and turbidimetric measurements. The interpolymeric bonds may be ionic or physical, depending on the pH of the system. For a pH value of 4.9, the mixture system [LYS]/[PAH] gives raise the formation of coacervate droplets. The effects of temperature on the structure of coacervate droplets are studied by small angle light scattering (SALS).

Protein-Protein Interactions of Highly Concentrated Monoclonal Antibody Solutions via Static Light Scattering and Influence on the Viscosity

The ability to design and formulate mAbs to minimize attractive interactions at high concentrations is important for protein processing, stability, and administration, particularly in subcutaneous delivery, where high viscosities are often challenging. The strength of protein-protein interactions (PPIs) of an IgG1 and IgG4 monoclonal antibody (mAb) from low to high concentration was determined by static light scattering (SLS) and used to understand viscosity data. The PPI were tuned using NaCl and five organic ionic co-solutes. The PPI strength was quantified by the normalized structure factor S(0)/ S(0)_HS and Kirkwood-Buff integral G₂₂/ G_22,HS (HS = hard sphere) determined from the SLS data and also by fits with (1) a spherical Yukawa potential and (2) an interacting hard sphere (IHS) model, which describes attraction in terms of hypothetical oligomers. The IHS model was better able to capture the scattering behavior of the more strongly interacting systems (mAb and/or co-solute) than the spherical Yukawa potential. For each descriptor of PPI, linear correlations were obtained between the viscosity at high concentration (200 mg/mL) and the interaction strengths evaluated both at low (20 mg/mL) and high concentrations (200 mg/mL) for a given mAb. However, the only parameter that provided a correlation across both mAbs was the oligomer mass ratio ( m_oligomer/ m_{monomer+dimer}) from the IHS model, indicating the importance of self-association (in addition to the direct influence of the attractive PPI) on the viscosity.

Evaluating the Effects of Hinge Flexibility on the Solution Structure of Antibodies at Concentrated Conditions

Employing 2 different coarse-grained models, we evaluated the effect of intramolecular domain-domain distances and hinge flexibility on the general solution structure of monoclonal antibodies (mAbs), within the context of protein-protein steric repulsion. These models explicitly account for the hinge region, and represent antibodies at either domain or subdomain levels (i.e., 4-bead and 7-bead representations, respectively). Additionally, different levels of mAb flexibility are also considered. When evaluating mAbs as rigid structures, analysis of small-angle scattering profiles showed that changes in the relative internal distances between Fc and Fab domains significantly alter the local arrangement of neighboring molecules, as well as the molecular packing of the concentrated mAb solutions. Likewise, enabling hinge flexibility in either of the mAb models led to qualitatively similar results, where flexibility increases the spatial molecular arrangement at elevated concentrations. This occurs because fluctuations in mAb quaternary structure are modulated by the close proximity between molecules at elevated concentrations (>50 mg mL^-1), yielding an increased molecular packing and osmotic compressibility. However, our results also showed that the mechanism behind this synergy between flexibility and packing strongly depends on both the level of structural detail and the number of degrees-of-freedom considered in the coarse-grained model.

A methodology to calculate small-angle scattering profiles of macromolecular solutions from molecular simulations in the grand-canonical ensemble

The theoretical framework to evaluate small-angle scattering (SAS) profiles for multi-component macromolecular solutions is re-examined from the standpoint of molecular simulations in the grand-canonical ensemble, where the chemical potentials of all species in solution are fixed. This statistical mechanical ensemble resembles more closely scattering experiments, capturing concentration fluctuations that arise from the exchange of molecules between the scattering volume and the bulk solution. The resulting grand-canonical expression relates scattering intensities to the different intra- and intermolecular pair distribution functions, as well as to the distribution of molecular concentrations on the scattering volume. This formulation represents a generalized expression that encompasses most of the existing methods to evaluate SAS profiles from molecular simulations. The grand-canonical SAS methodology is probed for a series of different implicit-solvent, homogeneous systems at conditions ranging from dilute to concentrated. These systems consist of spherical colloids, dumbbell particles, and highly flexible polymer chains. Comparison of the resulting SAS curves against classical methodologies based on either theoretical approaches or canonical simulations (i.e., at a fixed number of molecules) shows equivalence between the different scattering intensities so long as interactions between molecules are net repulsive or weakly attractive. On the other hand, for strongly attractive interactions, grand-canonical SAS profiles deviate in the low- and intermediate-q range from those calculated in a canonical ensemble. Such differences are due to the distribution of molecules becoming asymmetric, which yields a higher contribution from configurations with molecular concentrations larger than the nominal value. Additionally, for flexible systems, explicit discrimination between intra- and inter-molecular SAS contributions permits the implementation of model-free, structural analysis such as Guinier's plots at high molecular concentrations, beyond what the traditional limits are for such analysis.

Determination of Interaction Parameters for Reversibly Self-Associating Antibodies: A Comparative Analysis

Monoclonal antibodies (mAbs) represent a major class of biotherapeutics and are the fastest growing category of biologic drugs on the market. However, mAb development and formulation are often impeded by reversible self-association (RSA), defined as the dynamic exchange of monomers with native-state oligomers. Here, we present a comparative analysis of the self-association properties for 5 IgG mAbs, under matched conditions and using orthogonal methods. Concentration-dependent dynamic light scattering and sedimentation velocity studies revealed that the majority of mAbs examined exhibited weak to moderate RSA. However, because these studies were carried out at mAb concentrations in the mg/mL range, we also observed significant nonideality. Noting that nonideality frequently masks RSA and vice versa, we conducted direct boundary fitting of the sedimentation velocity data to determine stoichiometric binding models, interaction affinities, and nonideality terms for each mAb. These analyses revealed equilibrium constants from micromolar to millimolar and stoichiometric models from monomer-dimer to isodesmic. Moreover, even for those mAbs described by identical models, we observed distinct kinetics of self-association. The accuracy of the models and their corresponding equilibrium constants were addressed using sedimentation equilibrium and simulations. Overall, these results serve as the starting point for the comparative dissection of RSA mechanisms in therapeutic mAbs.

Predicting Protein-Protein Interactions of Concentrated Antibody Solutions Using Dilute Solution Data and Coarse-Grained Molecular Models

Protein-protein interactions for solutions of an IgG1 molecule were quantified using static light scattering (SLS) measurements from low to high protein concentrations (c₂). SLS was used to determine second osmotic virial coefficients (B₂₂) at low c₂, and excess Rayleigh profiles (R^ex/K vs. c₂) and zero-q structure factors (S_q=0) as a function of c₂ at higher c₂ for a series of conditions (pH, sucrose concentration, and total ionic strength [TIS]). Repulsive (attractive) interactions were observed at low TIS (high TIS) for pH 5 and 6.5, with increasing repulsions when 5% w/w sucrose was also present. Previously developed and refined coarse-grained antibody models were used to fit model parameters from B₂₂ versus TIS data. The resulting parameters from low-c₂ conditions were used as the sole input to multiprotein Monte Carlo simulations to predict high-c₂R^ex/K and S_q=0 behavior up to 150 g/L. Experimental results at high-c₂ conditions were quantitatively predicted by the simulations for the coarse-grained models that treated antibody molecules as either 6 or 12 (sub) domains, which preserved the basic shape of a monoclonal antibody. Finally, preferential accumulation of sucrose around the protein surface was identified via high-precision density measurements, which self-consistently explained the simulation and experimental SLS results.

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.

Protein Partial Molar Volumes in Multicomponent Solutions from the Perspective of Inverse Kirkwood-Buff Theory

Inverse Kirkwood-Buff (KB) solution theory can be used to relate macroscopic quantities with molecular scale interactions and correlation functions, in the form of KB integrals. Protein partial specific volumes ([Formula: see text]) from high-precision density measurements can be used to quantify solvent-solute and solute-solute KB integrals. Currently, general expressions for [Formula: see text] as a function of cosolute concentration (c₃) have been provided for only binary and ternary solutions. We derive a general multicomponent expression for [Formula: see text] in terms of the relevant KB integrals for the case of low (infinite dilution) protein concentration but arbitrary cosolute concentrations. To test the utility of treating a quaternary system with a pseudoternary approximation, α-Chymotrypsinogen (aCgn) solutions with a series of solutes (NaCl, sucrose, and trehalose) were compared as a function of solute concentration with and without buffer present. Comparison between those ternary and quaternary solutions shows equivalent results within experimental uncertainty and suggests the pseudoternary approximation may be reasonable. In the case of aCgn, doing so also revealed that the preferential interactions can depend on pH. Analysis of steric contributions also provides an example that illustrates how KB integrals allow one to interpret [Formula: see text] in terms of contributions from molecular volume, excluded volume, and hydration/solvation effects.