Article Cite This: J. Phys. Chem. B XXXX, XXX, XXX−XXX
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Cluster Size and Quinary Structure Determine the Rheological Effects of Antibody Self-Association at High Concentrations Wenhua Wang, Wayne G. Lilyestrom, Zhi Yu Hu, and Thomas M. Scherer* Late Stage Pharmaceutical Development, Genentech (a Member of the Roche Group), 1 DNA Way, MS 56-1A, South San Francisco, California 94080, United States S Supporting Information *
ABSTRACT: The question of how nonspecific reversible intermolecular protein interactions affect solution rheology at high concentrations is fundamentally rooted in the translation of nanometer-scale interactions into macroscopic properties. Well-defined solutions of purified monoclonal antibodies (mAbs) provide a useful system with which to investigate the manifold intricacies of weak protein interactions at high concentrations. Recently, characterization of self-associating IgG1 antibody (mAb2) solutions has established the direct role of protein clusters on concentrated mAb rheology. Expanding on our earlier work with three additional mAbs (mAb1, mAb3, and mAb4), the observed concentration-dependent static light scattering and rheological data present a substantially more complex relationship between protein interactions and solution viscosity at high concentrations. The four mAb systems exhibited divergent correlations between cluster formation (size) and concentrated solution viscosities dependent on mAb primary sequence and solution conditions. To address this challenge, wellestablished features of colloidal cluster phenomena could be applied as a framework for interpreting our observations. The initial stages of mAb cluster formation were investigated with small-angle X-ray scattering (SAXS) and ensemble-optimized fit methods, to uncover shifts in the dimer structure populations which are produced by changes in mAb interaction modes and association valence under the different solution conditions. Analysis of mAb average cluster number and effective hydrodynamic radii at high concentrations revealed cluster architectures can have a wide range of fractal dimensions. Collectively, the static light scattering, SAXS, and rheological characterization demonstrate that nonspecific and anisotropic attractive intermolecular interactions produce antibody clusters with different quinary structures to regulate the rheological properties of concentrated mAb solutions.
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INTRODUCTION
the interstitial distances become smaller than the dimensions of the molecules themselves.6 Protein solution interactions are all essentially governed by protein chemical and structural features which affect solution thermodynamics through the sum of molecular forces across different lengths of scale. The weak attractive intermolecular interactions that lead to mAb self-association have also been definitively linked to elevated mAb solution viscosities at high concentrations.3,7,8 Several underlying molecular features that contribute to mAb solution viscosities and phase behaviors include primary structure, tertiary structure, localized electrostatic and hydrophobic surface features, solution conditions, solute−protein interactions, and the complex many-body interactions that occur in crowded conditions. Primary structure changes, including point mutations, can alter the molecular interactions that result in elevated viscosities.9 Antibody primary structures in the variable and hypervariable regions of the Fab complimentarity-determining region (CDR) were shown through sequence mutations of IgG1, IgG3, and IgG4 antibodies to modulate the solution
Establishing the relationship between the molecular and macroscopic properties is a central aim of soft-matter physical chemistry. Protein solutions or suspensions are ubiquitous forms of soft matter, which offer a profound variety of biological and technological functions, of which monoclonal antibodies (mAbs) are but one example. As mAbs have become an important class of therapeutic molecules to treat a wide variety of diseases and medical conditions, the requirement of high doses and high-concentration products to achieve therapeutic efficacy has challenged the development and manufacturing efforts.1,2 Some of the challenges observed as a result of the high protein concentrations during the manufacture and administration of protein therapeutics include high filtration back pressures, extended pool mixing times, altered fill/finish operation dynamics, and unmanageably high syringe injection forces for patients and caregivers. Furthermore, protein stability issues may manifest, such as concentration-dependent aggregation, opalescence, phase separation, and unexpectedly high solution viscosities2−5 Many of these issues have been linked to the nature of the weak intermolecular interactions between proteins that become prominent under the molecularly crowded conditions, where © XXXX American Chemical Society
Received: October 30, 2017 Revised: January 14, 2018 Published: January 23, 2018 A
DOI: 10.1021/acs.jpcb.7b10728 J. Phys. Chem. B XXXX, XXX, XXX−XXX
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The Journal of Physical Chemistry B viscosity at concentrations >100 mg/mL.10−12 Although secondary structures loss has been implicated in irreversible interactions, the native antibody secondary and tertiary structures contribute to attractive intermolecular interactions through the presentation of surface features.6,13,14 The bidentate tertiary structure of mAb CDRs enables both hetero (A−B) and homo (A−A) surface patch interactions.15 Electrostatic, oppositely charged patch interactions (A−B type) have been frequently identified as a primary source of mAb-attractive interactions,16,17 whereas hydrophobic patches can present A−A- or A−B-type interacting features if one or more hydrophobic surface patches exists on a molecule.8 Recent simulations and particle assembly models/experiments with localized colloidal interactions have elegantly confirmed that surface patches can produce an array of cluster architectures in attractive colloidal systems.18−21 Investigations of colloidal systems have also established that particle shape and aggregate assembly processes (reaction-limited or diffusionlimited) are important determinants of particle suspension rheological properties.22,23 Solution conditions and solute− protein interactions can mitigate or augment electrostatic and hydrophobic patch interactions to affect the solution rheology of concentrated mAb solutions.8,24,25 As another source of protein interactions, molecular crowding is a well-understood consequence of the molecules’ volume occupancy and shape restricting the space available to other molecules. The use of hard-sphere models has enabled characterization of the excluded volume contributions to protein thermodynamic behavior, which becomes significant at concentrations exceeding 10−20 mg/mL mAb.13,26,27 These models have confirmed the large influence of excluded volume effects have on concentrated protein interactions. More subtle consequences of molecular crowding manifest as increasingly significant contributions of many-body interactions to behavior of the system, when the intermolecular distances become small.6 It is also known that the many-body interactions in concentrated systems cannot be reliably simulated using two particle interaction potentials.28,29 As a result, dilute solution interactions have only limited value for the prediction of concentrated protein solution behavior, even when mAb framework and protein solution conditions remain constant.7,30 A more comprehensive description of intermolecular interactions across concentrations would benefit the overall understanding of protein behavior in molecular crowding conditions, including their rheology. Not coincidentally, the concentration dependent rheology of proteins can also be interpreted with excluded volume and hard-particle models. Although simple colloid rheological models, such as the Krieger−Dougherty fail at high concentrations or volume fractions, others, such as the Mooney equation31 and modified versions,27 are more successful, in part because of factors included to adjust for the nonspherical shape of most proteins. Thus, in the limiting case of noninteracting hard-particle systems, the solution viscosity increases exponentially at high concentrations as demonstrated with colloids, mAbs, and globular proteins in general.32,33 Beyond the observation that attractive intermolecular interactions contribute to elevated protein solution viscosities, considerable disagreement remains regarding the underlying mechanisms that modify protein solution rheological behavior. Among the earliest and most widely accepted hypothesis for the macroscopic viscosity enhancement has been the formation of a “transient network” model or lattice of self-associated
mAbs.3,15,34,35 Similarly, others have proposed hypothesis based variously on molecular entanglements,36 hierarchical cluster formations,37 electroviscous rheological effects,38,39 or aggregated protein particles.40 Juxtaposed against the diverse hypotheses for how protein molecular interactions translate into macroscopic solution rheological behavior, several pieces of conflicting evidence have been provided but never integrated into a comprehensive, more fully inclusive model.41−44 Recently, Lilyestrom et al. have found correlation between mAb cluster number/oligomeric state, volume, and viscosity at high concentrations, demonstrating that linear-chain assemblies of reversible mAb clusters (mAb2 here) formed through anisotropic interactions cause profound hydrodynamic and rheological solution effects in this system.8 Such observations suggested the existence of other protein cluster geometries and that their formation could also have macroscopic consequences. Expanding on our earlier work, the solution interactions and rheological properties of three additional mAbs (1, 3, 4) were examined across a diverse set of solution conditions, protein concentrations, and viscosities utilizing light scattering (static light scattering (SLS), small-angle X-ray scattering (SAXS)), and rheological methods. These mAbs exhibited either similar (mAb3), contrasting (mAb4), or entirely divergent (mAb1) self-association, cluster size, and viscosity trends compared to the properties of mAb2 solutions reported previously. The newly obtained data demonstrate that a substantially more complex relationship exists between weakly attractive intermolecular protein interactions and the solution rheological properties than previously understood. A systematic analysis of the diverse mAb reversible self-association and concentrationdependent rheology reveals the important role of protein cluster quinary structural features and yields a more comprehensive understanding of protein interactions in concentrated mAb solutions.
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MATERIALS AND METHODS Monoclonal antibodies 1−4 were expressed in Chinese hamster ovarian cell lines and purified at Genentech (South San Francisco, CA). The protein mAb1 was referred to as mAb1 in the previous studies by Shire et al.,3 Kanai et al.,15 Yadav et al.,14,45 and Scherer et al.6,13 The mAb2 molecule was referred to as mAb1 in the previous study by Lilyestrom et al.8 mAb1 and mAb2 are based on the same IgG1 framework and κ-light chain, with 48 residues differing in their complementaritydetermining regions (CDRs). mAb3 is based on the same IgG1 framework with λ-light chains. mAb4 consists of an IgG4 framework with hinge region P226S mutation and κ-light chain. mAbs1−4 are thus structurally related to varying degrees; compared to mAb1, mAb2 has ∼92% sequence identity, mAb3 has 74% sequence identity, whereas mAb4 has 83% sequence identity. The theoretical isoelectric points (pI) of the mAbs1−4 are 7.8, 9.2, 8.9, and 6.3, respectively. Purified antibodies were obtained as semidilute or concentrated solutions and stored at 2−8 °C prior to use. mAbs were dialyzed to the desired buffer conditions by three cycles of buffer exchange at 5 °C with a 10 kDa cutoff of membrane tubing (Spectra/Por). The following buffers were prepared: 20 mM L-histidine hydrochloride (His-Cl), pH 4.5−7.0 by 0.5 increments; 20 mM imidazole hydrochloride (imidazole-Cl), pH 7.5 for mAb1; 20 mM His-Cl, pH 6.0; 20 mM sodium phosphate, pH 7.2 ± 150 mM NaCl for mAb3; 20 mM Lhistidine acetate (His-acetate), pHs 5.5, 5.7, 6.0, 6.5; and 20 mM sodium phosphate, pH 7.2 for mAb4. To compensate for B
DOI: 10.1021/acs.jpcb.7b10728 J. Phys. Chem. B XXXX, XXX, XXX−XXX
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The Journal of Physical Chemistry B
⎡ ⎤ R(θ = 0, c) 1 ⎥ = M w app = M ⎢ 2 Kc ⎣ [1 + 2B2 Mc + 3B3Mc ···] ⎦
Donnan effects during dialysis, dialysis buffers were adjusted with offsets to achieve the intended pH of protein solutions. mAb solutions were then concentrated to ∼220 mg/mL using EMD Millipore stirred cells with 10 kDa cutoff of membrane and filtered with 0.22 μm sterile vacuum filtration system (Millipore Corp., MA). The concentrations of the samples were determined using gravimetric dilutions and absorptivities at 280 nm (A280) of 1.58, 1.58, 1.63, and 1.45 (mg/mL) cm−1for mAbs1−4, respectively. Deionized water from a PURELAB Ultrapurification system (ELGA LabWater) was used to prepare all solutions. All buffer components and reagents used were of analytical grade or higher purity. Static Light Scattering Data Collection and Analysis. All mAb solutions for static light scattering (SLS) were prepared in 20 mL scintillation vials by gravimetric dilution (1.0 to ∼220 mg/mL) from stock solutions with known concentrations in a laminar flow hood. The stock materials consisted of >98% mAb monomers, characterized by size exclusion chromatography (data not shown). After preparation of the samples, mAb solutions were gently mixed and left at room temperature ≥2 h to reach equilibrium. Protein samples were centrifuged at room temperature for 20 min at 3750 rpm prior to light scattering analysis. The methods used for light scattering measurements and data analysis have been previously described in detail.8 Briefly, SLS experiments were conducted using an 18-angle DAWN EOS light scattering detector with a 30 mW solid-state laser (λ = 690 nm) (Wyatt Technology Corp., CA) at 25 °C. Astra 4.90 software (Wyatt Technology Corp., CA) was used to acquire data, and Astra 6.0 was used for data processing. For a single scattering species at arbitrary concentration, the generalized equation for Rayleigh scattering intensity (R(θ,c)) can be written as eq 1.46 Within this restricted case, applicable to systems of purified monodisperse proteins, R(θ,c) is a function of the scattering angle θ and w/v concentration c, and is directly related to the mass of the scattering species (M), the molecular size through the radius of gyration, Rg, and solute interactions described by the virial coefficients B2, B3, etc., as below Kc 1 = [1 + 2B2 Mc + 3B3Mc 2 + ···] R (θ , c ) M ⎡ ⎤ q2R g2 ⎢1 + + ···⎥ ⎢⎣ ⎥⎦ 3
(2)
Mw app is the apparent protein molecular weight obtained that include complex contributions from solution nonideality, particularly at high protein concentrations. Second osmotic virial coefficients (B2) were determined from linear fit analysis of 1/Mw app versus c for sample concentrations ≤10 mg/mL. Contributions to the light scattering data from higher-order virial expansion terms for concentrations above 10 mg/mL were analytically interpreted by fitting of data with models of self-associating hard particles. Interacting Hard-Sphere (IHS) Model Analysis. MATLAB (R2011b, Mathworks, Natick, MA) scripts of modeling multicomponent equilibrium interacting hard-sphere (IHS)47 models were used to obtain the equilibrium mAb cluster association states and constants as a function of concentration, as previously described.8 Briefly, we consider that an mAb solution contains three species: mAb monomer, m-mer, and nmer oligomers or “clusters”. The self-association constants to form m-mer and n-mer cluster species are Km and Kn, respectively. Model fitting analysis of the experimental scattering intensity as a function of concentration for each mAb and solution condition provided optimized results for mmer and n-mer cluster size or association state and their respective association constants. The distribution of cluster sizes as a function of protein concentration (0−250 mg/mL) was obtained from the n and m-mer association constants and effective volume contributions to nonideality to calculate mass fractions of each species (monomer, m-mer, n-mer) (MATLAB script, written and kindly provided by A.P. Minton). An average cluster size (⟨Nc⟩) representing the average number of mAb monomer units per protein cluster could be readily obtained as a function of concentration from the mass fraction distributions. Rheological Measurements and Analysis. Samples prepared for static light scattering experiments were stored at 2−8 °C (for less than 2 weeks) until subsequent use for the viscosity measurements. Solution viscosities were measured using Physica MCR 501 rheometer (Anton Paar, Graz, Austria) with a 50 mm cone (CP 50−0.5) with a constant shear rate of 1000 s−1 and a temperature-controlled plate at 25 °C. Viscosity data of each sample were averaged from 12 data points with 10 s of each measurement. Viscosities at 175 mg/mL were obtained from nonlinear fitting of the viscosity versus mAb concentration profiles. The apparent effective volumes of mAb clusters were calculated using the modified Mooney equation by Ross and Minton8,27
(1)
where K=
2 4πno(sin θ /2) 4π 2n2 ⎛⎜ dn ⎞⎟ , q= 4⎝ λo NAλo dc ⎠
The system constant K includes the solution refractive index (n), the wavelength of incident light (λo), the refractive index increment of scattering solute (dn/dc), the scattering vector q at scattering angle (θ), and the Avogadro constant (NA). In the limit of infinite dilution (c → 0) and the scattering angle θ approaching 0, eq 1 yields the value of 1/M, the absolute molecular mass of the scattering species. In practice, light scattering measurements are made at both finite concentrations and angles, extrapolating to one or both limiting conditions to obtain M. To simplify interpretation of data obtained from the light scattering measurements over a wide range of protein concentrations, the value of apparent molecular mass (Mapp) is introduced and is defined at concentration c as R(0,c)/Kc in the limit of θ → 0 reduces to eq 2.
ηinh =
ln(ηr ) c
=
κ [η] ln(ηr ) + [η] v
(3)
where ηinh is the inherent viscosity, meaning the buffer and protein concentration-normalized viscosity, η is the measured viscosity, η0 is the buffer viscosity, ηrel is defined as η/η0, ν is the Simha shape parameter, κ is the self-crowding factor, c is the protein concentration in mg/mL, and [η] is the solute intrinsic viscosity. Graphical analysis of ηinh versus ln(η/η0) permits identification of both linear (constant) and nonlinear (dynamic) contributions of the rheological behavior of the protein solutions. For data sets with significant nonlinearity, a linear analysis of the highest 3−4 concentration data ηinh versus C
DOI: 10.1021/acs.jpcb.7b10728 J. Phys. Chem. B XXXX, XXX, XXX−XXX
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solvent system. Interpretation of the experimental solution structure factors obtained from SAXS or SANS is qualitatively based on the intermolecular correlations of scattering species, and more quantitatively in terms of radial distribution functions. In the limit of very dilute solution and the absence of intermolecular interactions, S(q) is equal to 1. The contributions of attractive interactions to solution nonideality between protein molecules lead to time-averaged species, which appear as clusters or aggregates that scatter light proportionally to their mass and concentration with the result that S(q) > 1. Protein molecules distributed in solution by repulsive interactions have reduced time-averaged molecular proximities relative to that of noninteracting species, leading to S(q) values 98% mAb monomers before scattering data collection at the Advanced Light Source (ALS, Lawrence Berkeley National Laboratory). SAXS data were collected at the SIBYLS beamline 12.3.1 of the ALS using a Mar CCD area detector (diameter, 165 mm) located 1.6 m from the sample chamber in the q-spacing 0.01−0.32 Å−1, where q = 4π sin θ/λ (2θ is the scattering angle and wavelength λ = 1.03 Å) at room temperature. Scattering intensity images were subjected to circular integration, normalization, and subtraction of buffer image files from the actual sample files. The radii of gyration (Rg) were analyzed using the Guinier approximation with low-angle data (Rg × q < 1.3) using PRIMUS49 to evaluate possible intermolecular interaction effects. The Rg values and maximum dimensions (Dmax) were also determined from the entire scattering profiles using the program GNOM,50 summarized in Table S1. The structure factor S(q) obtained from SAXS provides information about protein intermolecular interactions and radial distribution functions in aqueous solution based on the following equation51,52 I(q) = A pP(q)S(q)
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RESULTS AND DISCUSSION The investigation of mAb self-association and viscosity was conducted across protein concentrations (0−225 mg/mL) and viscosities (1 to >800 cP) with mAbs1−4 under diverse solution conditions. Complimentary data sets were developed from static light scattering characterization of protein−protein interactions, rheological measurements of solution viscosities at constant shear, and SAXS to provide solution structure factors and molecular assembly information where feasible. The mAbs studied here were not selected based on their uniform features, but rather because each presented high-concentration behavior challenging the current understanding of protein interactions and rheology. Conditions used to evaluate the relationship between intermolecular interactions and solution viscosities span the range of pH, buffer, and ionic strength conditions, illustrating the range of complex behaviors possible in concentrated mAb solutions. The solution phenomena of interest occurred under different conditions for each mAb: antibodies mAb1 and mAb4 were studied under low ionic strength conditions as a function of solution pH, mAb1 across the pH range 4.5−7.5 in 20 mM buffer histidine-HCl and imidazole-HCl buffers, and mAb4 at pH 5.5−7.2 in 20 mM buffer histidine acetate or sodium
(7)
where I(q) is the SAXS scattering intensity, Ap is an amplitude factor, and P(q) is the form factor, the average particle scattering component related to the molecular structure/shape of the scattering unit in solution. S(q) may be readily obtained from the scattering intensity, I(q), dividing by the term of ApP(q) obtained from dilute solution scattering in the same D
DOI: 10.1021/acs.jpcb.7b10728 J. Phys. Chem. B XXXX, XXX, XXX−XXX
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Figure 1. A comparison of dilute solution mAb interaction parameters to solution viscosities at high concentrations. (A) Osmotic second virial coefficient B2 as a function of solution conditions for mAbs1−4. (B) Viscosity of 175 mg/mL solutions measured at 20 °C and constant shear rate (103 s−1) as a function of solution conditions for mAbs1−4. (C) Correlation of viscosity with B2 for mAbs1−4 and all solution conditions.
tigations of protein interactions and concentrated solution viscosities. B2 values for mAbs1−4 obtained from protein concentrations 2 occur in systems of associating proteins, the magnitudes of two-molecule interaction parameters (Kd, B2) cease to correlate with the high-concentration solution viscosities (see Figure 1C); due to equilibrium thermodynamics, larger association valences (V > 2) are expected to dominate at high concentrations, where many-body interactions and volume exclusion (molecular crowding) effects become consequential. The diverse rheology of mAbs1−4 may be resolved by considering the strength and valency of protein interactions, as well as the resulting quinary structural features of clusters that exist at high concentrations. Self-associated mAb clusters with V = 2 and linear assembly structures, as illustrated in Figure 7A,C−E, establish stress-bearing chains to increase solution viscosity dramatically. However, when interaction valences are >2, mAbs form increasingly branched (Figure 7F, mAb3) and condensed/compact clusters, as represented in Figure 7B (mAb1, pH ≥ 7.0) and Figure 7G−H (mAb4), which create less hydrodynamic resistance to flow so that the protein cluster effects on the solution viscosity are greatly diminished. Similarly, soluble aggregates of antibodies and proteins, which accrete irreversibly as dense masses of partially unfolded species, would be expected to have no significant effect on the concentration-dependent viscosities of solutions. Fractal dimension analysis of the clustering mAb systems in Figures 8A, and S7, Supporting Information, provide clear evidence that mAb solution rheology is a function of both the number of monomer units in a cluster and quinary structural arrangement as scaled cluster size ξ to modulate the hydrodynamic and frictional effects of clusters during solution flow. Colloidal suspensions or dispersions are defined as complex fluids, differentiated from simple fluids by the microstructure that results from the relative arrangement of constituents. The rheology of colloidal suspensions is determined by the interplay of mesoscopic forces with the translational motion induced by macroscopic flow. Our characterization of the structural features of mAb clusters using SAXS/EOM, static light scattering, and rheology underscores that mAbs, like many proteins in solution, share numerous attributes in common with colloidal suspensions. The analysis of cluster structural features supplies evidence of the diverse interactions and rheological consequences mAb solutions may exhibit. The molecular details of mAb assembly and average cluster number states provide significant new insights into the mechanisms, by which protein interactions control concentrated solution viscosities. Protein surface patches provide the anisotropic attractive molecular features, which regulate interaction valence. They work in combination with excluded volume/molecular crowding effects to determine cluster assembly size and quinary structures for the diverse structural topologies that are shown to form at high
framework or solution condition, a wider range of systems were investigated, pursuing more broadly applicable conclusions. An evaluation of the correlation between the solution viscosity at 175 mg/mL (η 175 ) and various molecular interaction parameters (B2, Nc, Veff, Df) for the four antibody systems with diverse solution conditions is provided in Figure S6, Supporting Information. The good correlation (R = 0.8) found in Figure S6B indicates that solution viscosities are clearly related to the features of cluster size (Nc) of self-association at high concentrations to a much greater extent than the dilute solution interactions (Figure S6A). However, the IgG molecule-dependent trends in Figure 4 also clearly illustrate that a complex inter-relationship between association state Nc and rheological behavior exists: mAbs can have different cluster-forming patterns. Even for a single mAb, valency and cluster topology may vary across the spectrum depending on solution conditions, as in the case of mAb1. The linear cluster assembly of mAb2 and mAb3 is defined by the strong correlation of Nc, with η175 contrasts with the relationship observed for mAb4. The absence of a relationship, with the attractive interactions and cluster species having minimal/no effect on the viscosity of mAb4 solutions, appears to represent the other extreme on the viscosity/cluster formation behavior continuum. An improved understanding of the divergent phenomena exhibited by mAbs1−4 in Figure 4 may be derived by relating the nanoscale features of the intermolecular interactions to the macroscopic rheological behavior. Characterization of dilute solution mAb systems with SAXS/ EOM identified dimer structures and their population distributions, to provide new details about the precursors to mAb cluster assembly at higher concentrations. In contrast to the extended end−end assembly of a single population of dimers (Dmax ∼ 300 Å) found with mAb2 as a function of increasing Na2SO4 salt concentrations,8 mAb1 showed pHdependent dimerization with at least two populations of dimers, centered about Dmax ∼260 and ∼315 Å. At a pH of 6.0, the population of mAb1 dimers was composed of more extended dimer structures, such as mAb dimer structure *4, whereas at pH 7.5, the population of dimers was found to consist of smaller structures Dmax = ca. 230−275 Å derived from several different interaction loci, as represented by structures *1−*3 (Figure 5). The dilute solution mAb1 dimer structures from SAXS/EOM in Figure 5 show structural shifts and valence changes as a function of solution pH that correspond to the cluster structure changes at high concentrations (Figure 7A,B) as remarkably coincident. Examined together, these data provide evidence that different molecular assembly mechanisms enable diverse types of protein/colloidal cluster structures as a function of solution conditions. End-on-end association between two interaction sites with valence (V) = 2 constitutes the most basic assembly pattern and results in linear “chain” oligomer formations. Previous investigations have shown that the extended end-to-end dimer structures of mAb28 and those also observed for mAb1 at pH 6.0 can continue to self-assemble into larger linear protein clusters at high concentrations, leading to dramatically elevated solution viscosities. However, when multiple sites of interaction are simultaneously present, (V > 2) more complex mechanisms and configurations of protein association should be anticipated. A direct consequence of valence >2 is that the mAb monomer units can form branched clusters so that with increasing V progressively denser cluster structures result. Dimer species observed for mAb1 at pH 7.5 (Figure 5C: N
DOI: 10.1021/acs.jpcb.7b10728 J. Phys. Chem. B XXXX, XXX, XXX−XXX
The Journal of Physical Chemistry B concentrations. We found that not only the number of mAb units assembled (cluster formation size) but also the resulting cluster topology determine the viscosity of concentrated mAb solutions in a multiparametric manner. With this more nuanced understanding, the diverse rheological and self-association properties exhibited by mAbs1−4 and others43,71 can be reconciled as part of a continuum of the colloidal proteinclustering phenomenon.
CONCLUSIONS Our observations challenged the current models for the increased viscosities in concentrated protein solutions that are based primarily on the strength of protein self-association in dilute solutions. SAXS/EOM analysis of dilute solutions revealed new features of dimer assembly structures and population diversity. Molecular-level investigations of mAb1 and mAb2 oligomerization suggests that the number of attractive patches (interaction valence) as well as their relative orientations drive dimer formation and ultimately affect the sizes and structures of assembling clusters. Average cluster sizes and volumes found at high concentrations (40−175 mg/mL) provided illustrative computational structural models and enabled semiquantitative shape and unit density determination of cluster fractal dimensions Df as a measure of the structural features present. These data highlight the diversity of cluster fractal dimensions and cluster topologies that can assemble from essentially similar mAb units to affect the divergent rheological behavior of concentrated solutions. The formation of linear, extended cluster quinary structures was shown to consistently produce the greatest increases in mAb solution viscosity at high concentrations (for a given number of mAb units per cluster). Conversely, increasingly multi-valent mAb assembly produces clusters with branched or even dense collapsed topologies to progressively reduce their hydrodynamic effects on solution viscosity. The results collectively demonstrate that protein interaction valence, cluster size, and quinary structure govern the resistance to flow by reversibly assembled clusters in concentrated mAb solutions.
ACKNOWLEDGMENTS
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REFERENCES
(1) Shire, S. J. Formulation and manufacturability of biologics. Curr. Opin. Biotechnol. 2009, 20, 708−714. (2) Shire, S. J.; Shahrokh, Z.; Liu, J. Challenges in the development of high protein concentration formulations. J. Pharm. Sci. 2004, 93, 1390−1402. (3) Liu, J.; Nguyen, M. D. H.; Andya, J. D.; Shire, S. J. Reversible selfassociation increases the viscosity of a concentrated monoclonal antibody in aqueous solution. J. Pharm. Sci. 2005, 94, 1928−1940. (4) Nishi, H.; Miyajima, M.; Nakagami, H.; Noda, M.; Uchiyama, S.; Fukui, K. Phase separation of an IgG1 antibody solution under a low ionic strength condition. Pharm. Res. 2010, 27, 1348−1360. (5) Sukumar, M.; Doyle, B. L.; Combs, J. L.; Pekar, A. H. Opalescent appearance of an IgG1 antibody at high concentrations and its relationship to noncovalent association. Pharm. Res. 2004, 21, 1087− 1093. (6) Scherer, T. M. Cosolute effects on the chemical potential and interactions of an IgG1 monoclonal antibody at high concentrations. J. Phys. Chem. B 2013, 117, 2254−2266. (7) Connolly, B. D.; Petry, C.; Yadav, S.; Demeule, B.; Ciaccio, N.; Moore, J. M. R.; Shire, S. J.; Gokarn, Y. R. Weak interactions govern the viscosity of concentrated antibody solutions: high-throughput analysis using the diffusion interaction parameter. Biophys. J. 2012, 103, 69−78. (8) Lilyestrom, W. G.; Yadav, S.; Shire, S. J.; Scherer, T. M. Monoclonal antibody self-association, cluster formation, and rheology at high concentrations. J. Phys. Chem. B 2013, 117, 6373−6384. (9) Bethea, D.; Wu, S.-J.; Luo, J.; Hyun, L.; Lacy, E. R.; Teplyakov, A.; Jacobs, S. A.; O’Neil, K. T.; Gilliland, G. L.; Feng, Y. Mechanisms of self-association of a human monoclonal antibody CNTO607. Protein Eng., Des. Sel. 2012, 25, 531−537. (10) Geoghegan, J. C.; Fleming, R.; Damschroder, M.; Bishop, S. M.; Sathish, H. A.; Esfandiary, R. Mitigation of reversible self-association and viscosity in a human IgG1 monoclonal antibody by rational, structure-guided Fv engineering. mAbs 2016, 8, 941−950. (11) Nichols, P.; Li, L.; Kumar, S.; Buck, P. M.; Singh, S. K.; Goswami, S.; Balthazor, B.; Conley, T. R.; Sek, D.; Allen, M. J. Rational design of viscosity reducing mutants of a monoclonal antibody: hydrophobic versus electrostatic inter-molecular interactions. mAbs 2015, 7, 212−230. (12) Yadav, S.; Shire, S. J.; Kalonia, D. S. Viscosity analysis of high concentration bovine serum albumin aqueous solutions. Pharm. Res. 2011, 28, 1973−1983. (13) Scherer, T. M.; Liu, J.; Shire, S. J.; Minton, A. P. Intermolecular interactions of IgG1 monoclonal antibodies at high concentrations characterized by light scattering. J. Phys. Chem. B 2010, 114, 12948− 12957. (14) Yadav, S.; Laue, T. M.; Kalonia, D. S.; Singh, S. N.; Shire, S. J. The influence of charge distribution on self-association and viscosity behavior of monoclonal antibody solutions. Mol. Pharm. 2012, 9, 791− 802. (15) Kanai, S.; Liu, J.; Patapoff, T. W.; Shire, S. J. Reversible selfassociation of a concentrated monoclonal antibody solution mediated by Fab−Fab interaction that impacts solution viscosity. J. Pharm. Sci. 2008, 97, 4219−4227. (16) Zhang, L.; Lilyestrom, W.; Li, C.; Scherer, T.; van Reis, R.; Zhang, B. Revealing a positive charge patch on a recombinant
ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcb.7b10728. SAXS structure factor analysis and additional OEM characterization for mAb1 as a function of pH, light scattering data analysis illustrating ⟨Nc⟩ as a function of concentration, shear rate dependence of concentrated mAb1 solution rheology, cluster fractal dimensions as a function of mAb concentration, correlation of various protein interaction parameters with relative viscosity for mAbs1−4, and a viscosity model incorporating cluster ⟨Nc⟩ and fractal dimensions as scaled cluster size (PDF)
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This manuscript is dedicated to the memory of Dr. Steven J. Shire, whose work and collaboration provided the authors a decade of thought provoking conversations, research subject matter, and inspiration. L. Owyang is gratefully thanked for light scattering and rheological measurements of mAb4 solutions. W.G.L. and W.W. acknowledge Genentech support as part of the Postdoctoral Research Fellowship Program from 2010−2012 and 2013−2015, respectively.
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. ORCID
Thomas M. Scherer: 0000-0002-9309-6085 Notes
The authors declare no competing financial interest. O
DOI: 10.1021/acs.jpcb.7b10728 J. Phys. Chem. B XXXX, XXX, XXX−XXX
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The Journal of Physical Chemistry B monoclonal antibody by chemical labeling and mass spectrometry. Anal. Chem. 2011, 83, 8501−8508. (17) Li, W.; Persson, B. A.; Morin, M.; Behrens, M. A.; Lund, M.; Oskolkova, M. Z. Charge-induced patchy attractions between proteins. J. Phys. Chem. B 2015, 119, 503−508. (18) Audus, D. J.; Starr, F. W.; Douglas, J. F. Coupling of isotropic and directional interactions and its effect on phase separation and selfassembly. J. Chem. Phys. 2016, 144, No. 074901. (19) Chaudhri, A.; Zarraga, I. E.; Yadav, S.; Patapoff, T. W.; Shire, S. J.; Voth, G. A. The role of amino acid sequence in the self-association of therapeutic monoclonal antibodies: insights from coarse-grained modeling. J. Phys. Chem. B 2013, 117, 1269−1279. (20) Jacobs, W. M.; Oxtoby, D. W.; Frenkel, D. Phase separation in solutions with specific and nonspecific interactions. J. Chem. Phys. 2014, 140, No. 204109. (21) Lu, P. J.; Zaccarelli, E.; Ciulla, F.; Schofield, A. B.; Sciortino, F.; Weitz, D. A. Gelation of particles with short-range attraction. Nature 2008, 453, 499−503. (22) Genovese, D. B. Shear rheology of hard-sphere, dispersed, and aggregated suspensions, and filler-matrix composites. Adv. Colloid Interface Sci. 2012, 171−172, 1−16. (23) Mueller, S.; Llewellin, E. W.; Mader, H. M. The effect of particle shape on suspension viscosity and implications for magmatic flows. Geophys. Res. Lett. 2011, 38, L13316. 10.1029/2011GL047167. (24) Scherer, T. M. Role of cosolute−protein interactions in the dissociation of monoclonal antibody clusters. J. Phys. Chem. B 2015, 119, 13027−13038. (25) Guo, Z.; Chen, A.; Nassar, R. A.; Helk, B.; Mueller, C.; Tang, Y.; Gupta, K.; Klibanov, A. M. Structure−activity relationship for hydrophobic salts as viscosity-lowering excipients for concentrated solutions of monoclonal antibodies. Pharm. Res. 2012, 29, 3102−3109. (26) Minton, A. P.; Edelhoch, H. Light-scattering of bovine serumalbumin solutions: extension of the hard particle model to allow for electrostatic repulsion. Biopolymers 1982, 21, 451−458. (27) Ross, P. D.; Minton, A. P. Hard quasi-spherical model for viscosity of hemoglobin solutions. Biochem. Biophys. Res. Commun. 1977, 76, 971−976. (28) Brunner, M.; Dobnikar, J.; von Grünberg, H.-H.; Bechinger, C. Direct measurement of three-body interactions amongst charged colloids. Phys. Rev. Lett. 2004, 92, No. 078301. (29) Allahyarov, E.; Löwen, H. Nonadditivity in the effective interactions of binary charged colloidal suspensions. J. Phys.: Condens. Matter 2009, 21, No. 424117. (30) Li, L.; Kumar, S.; Buck, P. M.; Burns, C.; Lavoie, J.; Singh, S. K.; Warne, N. W.; Nichols, P.; Luksha, N.; Boardman, D. Concentration dependent viscosity of monoclonal antibody solutions: explaining experimental behavior in terms of molecular properties. Pharm. Res. 2014, 31, 3161−3178. (31) Mooney, M. The viscosity of a concentrated suspension of spherical particles. J. Colloid Sci. 1951, 6, 162−170. (32) Minton, A. P.; Ross, P. D. Analysis of nonideal behavior in concentrated-solutions of normal and sickle hemoglobin. Fed. Proc. 1977, 36, 755. (33) Shewan, H. M.; Stokes, J. R. Viscosity of soft spherical microhydrogel suspensions. J. Colloid Interface Sci. 2015, 442, 75−81. (34) Pan, W.; Filobelo, L.; Pham, N. D. Q.; Galkin, O.; Uzunova, V. V.; Vekilov, P. G. Viscoelasticity in homogeneous protein solutions. Phys. Rev. Lett. 2009, 102, No. 058101. (35) Buck, P. M.; Chaudhri, A.; Kumar, S.; Singh, S. K. Highly viscous antibody solutions are a consequence of network formation caused by domain−domain electrostatic complementarities: insights from coarse-grained simulations. Mol. Pharm. 2015, 12, 127−139. (36) Schmit, J. D.; He, F.; Mishra, S.; Ketchem, R. R.; Woods, C. E.; Kerwin, B. A. Entanglement model of antibody viscosity. J. Phys. Chem. B 2014, 118, 5044−5049. (37) Godfrin, P. D.; Zarraga, I. E.; Zarzar, J.; Porcar, L.; Falus, P.; Wagner, N. J.; Liu, Y. Effect of hierarchical cluster formation on the viscosity of concentrated monoclonal antibody formulations studied by neutron scattering. J. Phys. Chem. B 2016, 120, 278−291.
(38) Raut, A. S.; Kalonia, D. S. Viscosity analysis of dual variable domain immunoglobulin protein solutions: role of size, electroviscous effect and protein−protein interactions. Pharm. Res. 2016, 33, 155− 166. (39) Saluja, A.; Kalonia, D. S. Measurement of fluid viscosity at microliter volumes using quartz impedance analysis. AAPS PharmSciTech 2004, 5, 68. (40) Pathak, J. A.; Sologuren, R. R.; Narwal, R. Do clustering monoclonal antibody solutions really have a concentration dependence of viscosity? Biophys. J. 2013, 104, 913−923. (41) Yadav, S.; Sreedhara, A.; Kanai, S.; Liu, J.; Lien, S.; Lowman, H.; Kalonia, D. S.; Shire, S. J. Establishing a link between amino acid sequences and self-associating and viscoelastic behavior of two closely related monoclonal antibodies. Pharm. Res. 2011, 28, 1750−1764. (42) Tiffany, J. M.; Koretz, J. F. Viscosity of alpha-crystallin solutions. Int. J. Biol. Macromol. 2002, 30, 179−185. (43) Salinas, B. A.; Sathish, H. A.; Bishop, S. M.; Harn, N.; Carpenter, J. F.; Randolph, T. W. Understanding and modulating opalescence and viscosity in a monoclonal antibody formulation. J. Pharm. Sci. 2010, 99, 82−93. (44) Sarangapani, P. S.; Hudson, S. D.; Migler, K. B.; Pathak, J. A. The limitations of an exclusively colloidal view of protein solution hydrodynamics and rheology. Biophys. J. 2013, 105, 2418−2426. (45) Yadav, S.; Liu, J.; Shire, S. J.; Kalonia, D. S. Specific interactions in high concentration antibody solutions resulting in high viscosity. J. Pharm. Sci. 2010, 99, 1152−1168. (46) Wyatt, P. J. Light scattering and the absolute characterization of macromolecules. Anal. Chim. Acta 1993, 272, 1−40. (47) Minton, A. P. Static light scattering from concentrated protein solutions, I: General theory for protein mixtures and application to self-associating proteins. Biophys. J. 2007, 93, 1321−1328. (48) Harshe, Y. M.; Ehrl, L.; Lattuada, M. Hydrodynamic properties of rigid fractal aggregates of arbitrary morphology. J. Colloid Interface Sci. 2010, 352, 87−98. (49) Konarev, P. V.; Volkov, V. V.; Sokolova, A. V.; Koch, M. H. J.; Svergun, D. I. PRIMUS: a Windows PC-based system for small-angle scattering data analysis. J. Appl. Crystallogr. 2003, 36, 1277−1282. (50) Svergun, D. I. Determination of the regularization parameter in indirect-transform methods using perceptual criteria. J. Appl. Crystallogr. 1992, 25, 495−503. (51) Kotlarchyk, M.; Chen, S.-H. Analysis of small-angle neutronscattering spectra from polydisperse interacting colloids. J. Chem. Phys. 1983, 79, 2461−2469. (52) Liu, Y.; Chen, W.-R.; Chen, S.-H. Cluster formation in twoYukawa fluids. J. Chem. Phys. 2005, 122, No. 044507. (53) Zhang, F.; Skoda, M. W. A.; Jacobs, R. M. J.; Martin, R. A.; Martin, C. M.; Schreiber, F. Protein interactions studied by SAXS: effect of ionic strength and protein concentration for BSA in aqueous solutions. J. Phys. Chem. B 2007, 111, 251−259. (54) Bernadó, P.; Mylonas, E.; Petoukhov, M. V.; Blackledge, M.; Svergun, D. I. Structural characterization of flexible proteins using small-angle X-ray scattering. J. Am. Chem. Soc. 2007, 129, 5656−5664. (55) Tria, G.; Mertens, H. D. T.; Kachala, M.; Svergun, D. I. Advanced ensemble modelling of flexible macromolecules using X-ray solution scattering. IUCrJ 2015, 2, 207−217. (56) Lilyestrom, W. G.; Shire, S. J.; Scherer, T. M. Influence of the cosolute environment on IgG solution structure analyzed by smallangle x-ray scattering. J. Phys. Chem. B 2012, 9611. (57) Sandin, S.; Ö fverstedt, L.-G.; Wikström, A.-C.; Wrange, O.; Skoglund, U. Structure and flexibility of individual immunoglobulin G molecules in solution. Structure 2004, 12, 409−415. (58) Saphire, E. O.; Parren, P. W. H. I.; Pantophlet, R.; Zwick, M. B.; Morris, G. M.; Rudd, P. M.; Dwek, R. A.; Stanfield, R. L.; Burton, D. R.; Wilson, I. A. Crystal structure of a neutralizing human IgG against HIV-1: a template for vaccine design. Science 2001, 293, 1155−1159. (59) Tama, F.; Wriggers, W.; Brooks, C. L. Exploring global distortions of biological macromolecules and assemblies from lowresolution structural information and elastic network theory. J. Mol. Biol. 2002, 321, 297−305. P
DOI: 10.1021/acs.jpcb.7b10728 J. Phys. Chem. B XXXX, XXX, XXX−XXX
Article
The Journal of Physical Chemistry B (60) Chacón, P.; Tama, F.; Wriggers, W. Mega-Dalton biomolecular motion captured from electron microscopy reconstructions. J. Mol. Biol. 2003, 326, 485−492. (61) Brooks, B.; Karplus, M. Harmonic dynamics of proteins: normal-modes and fluctuations in bovine pancreatic trypsin-inhibitor. Proc. Natl. Acad. Sci. U.S.A. 1983, 80, 6571−6575. (62) Hayward, S.; de Groot, B. L. Normal modes and essential dynamics. Methods Mol. Biol. 2008, 443, 89−106. (63) Saito, S.; Hasegawa, J.; Kobayashi, N.; Kishi, N.; Uchiyama, S.; Fukui, K. Behavior of monoclonal antibodies: Relation between the second virial coefficient (B2) at low concentrations and aggregation propensity and viscosity at high concentrations. Pharm. Res. 2012, 29, 397−410. (64) Kamerzell, T. J.; Kanai, S.; Liu, J.; Shire, S. J.; Wang, Y. J. Increasing IgG concentration modulates the conformational heterogeneity and bonding network that influence solution properties. J. Phys. Chem. B 2009, 113, 6109−6118. (65) Berli, C. L. A.; Deiber, J. A.; Añoń , M. C. Connection between rheological parameters and colloidal interactions of a soy protein suspension. Food Hydrocolloids 1999, 13, 507−515. (66) Davidson, R. L., Ed. Handbook of Water Soluble Gums and Resins; McGraw-Hill Book Company: San Francisco, CA, 1980; pp 668. (67) Mourey, T. H.; Turner, S. R.; Rubinstein, M.; Frechet, J. M. J.; Hawker, C. J.; Wooley, K. L. Unique behavior of dendritic macromolecules: intrinsic-viscosity of polyether dendrimers. Macromolecules 1992, 25, 2401−2406. (68) Uppuluri, S.; Keinath, S. E.; Tomalia, D. A.; Dvornic, P. R. Rheology of dendrimers. I. Newtonian flow behavior of medium and highly concentrated solutions of polyamidoamine (PAMAM) dendrimers in ethylenediamine (EDA) solvent. Macromolecules 1998, 31, 4498−4510. (69) Roovers, J. Concentration-dependence of the relative viscosity of star polymers. Macromolecules 1994, 27, 5359−5364. (70) Dealy, J. M.; Wang, J. Viscosity and Normal Stress Differences. In Melt Rheology and Its Applications in the Plastics Industry; Engineering Materials and Processes; Springer Science and Business Media: Dordrecht, Netherlands, 2013; Chapter 2, pp 37. (71) Yadav, S.; Shire, S. J.; Kalonia, D. S. Factors affecting the viscosity in high concentration solutions of different monoclonal antibodies. J. Pharm. Sci. 2010, 99, 4812−4829. (72) Beaucage, G. Determination of branch fraction and minimum dimension of mass-fractal aggregates. Phys. Rev. E: Stat., Nonlinear, Soft Matter Phys. 2004, 70, No. 031401. (73) Vekilov, P. G. Metastable mesoscopic phases in concentrated protein solutions. Ann. N. Y. Acad. Sci. 2009, 1161, 377−386. (74) Lu, P. J.; Giavazzi, F.; Angelini, T. E.; Zaccarelli, E.; Jargstorff, F.; Schofield, A. B.; Wilking, J. N.; Romanowsky, M. B.; Weitz, D. A.; Cerbino, R. Characterizing concentrated, multiply scattering, and actively driven fluorescent systems with confocal differential dynamic microscopy. Phys. Rev. Lett. 2012, 108, No. 218103. (75) Zhang, F.; Roosen-Runge, F.; Sauter, A.; Roth, R.; Skoda, M. W. A.; Jacobs, R. M. J.; Sztucki, M.; Schreiber, F. The Role of Cluster Formation and Metastable Liquid−Liquid Phase Separation in Protein Crystallization. Faraday Discuss. 2012, 313. (76) Tanford, C. The Physical Chemistry of Macromolecules; John Wiley and Sons, Inc.: New York, 1961. (77) Hloucha, M.; Lodge, J. F. M.; Lenhoff, A. M.; Sandler, S. I. A patch−antipatch representation of specific protein interactions. J. Cryst. Growth 2001, 232, 195−203. (78) Cheung, J. K.; Shen, V. K.; Errington, J. R.; Truskett, T. M. Coarse-grained strategy for modeling protein stability in concentrated solutions. III: Directional protein interactions. Biophys. J. 2007, 92, 4316−4324. (79) Roosen-Runge, F.; Zhang, F.; Schreiber, F.; Roth, R. Ionactivated attractive patches as a mechanism for controlled protein interactions. Sci. Rep. 2014, 4, No. 7016.
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DOI: 10.1021/acs.jpcb.7b10728 J. Phys. Chem. B XXXX, XXX, XXX−XXX