The Influence of Charge Distribution on Self-Association and Viscosity

Feb 21, 2012 - momentum transfer, H(q→0), to result in lower viscosity of MAb-2. Charge swap mutants of MAb-1, M-5 and M-7, showed a decrease in cha...
0 downloads 0 Views 3MB Size
Article pubs.acs.org/molecularpharmaceutics

The Influence of Charge Distribution on Self-Association and Viscosity Behavior of Monoclonal Antibody Solutions Sandeep Yadav,† Thomas M. Laue,‡ Devendra S. Kalonia,§ Shubhadra N. Singh,§ and Steven J. Shire*,† †

Late Stage Pharmaceutical Development, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, Durham, New Hampshire 03824, United States § Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut 06268, United States ‡

ABSTRACT: The present work investigates the influence of electrostatic surface potential distribution of monoclonal antibodies (MAbs) on intermolecular interactions and viscosity. Electrostatic models suggest MAb-1 has a less uniform surface charge distribution than MAb-2. The patches of positive and negative potential on MAb-1 are predicted to favor intermolecular attraction, even in the presence of a small net positive charge. Consistent with this expectation, MAb-1 exhibits a negative second virial coefficient (B22), an increase in static structure factor, S(q→0), and a decrease in hydrodynamic interaction parameter, H(q→0), with increase in MAb-1 concentration. Conversely, MAb-2 did not show such heterogeneous charge distribution as MAb-1 and hence favors intermolecular repulsion (positive B22), lower static structure factor, S(q→0), and repulsion induced increase in momentum transfer, H(q→0), to result in lower viscosity of MAb-2. Charge swap mutants of MAb-1, M-5 and M-7, showed a decrease in charge asymmetry and concomitantly a loss in self-associating behavior and lower viscosity than MAb-1. However, replacement of charge residues in the sequence of MAb-2, M-10, did not invoke charge distribution to the same extent as MAb-1 and hence exhibited a similar viscosity and self-association profile as MAb-2. KEYWORDS: electrostatic surface potential, membrane confined electrophoresis, protein charge, viscosity/rheology, second virial coefficient (B22), interaction parameter (kD), static structure factor (S(q)), hydrodynamic interaction parameter (H(q)), high concentration monoclonal antibody solution



INTRODUCTION With the advent of biotechnology, protein-based therapies have emerged as a powerful method of treating many terminal diseases. The quest for designing promising lead molecules and subsequently stable formulations against numerous indications has stimulated interest in understanding the physicochemical aspects as well as the solution behavior of proteins. Almost all protein therapeutics are administered by the parenteral route, and hence the dosage form needs to be formulated either as a solution, a suspension or a reconstituted solid dosage form before administration. Understanding the effect on viscosity, therefore, remains critical to addressing product development, manufacturing and delivery issues associated with high concentration formulations.1 Over the past few years, there has been considerable effort targeted toward managing high concentration viscosity © 2012 American Chemical Society

behavior by modulating the solution conditions such as solution pH,2−6 ionic strength2−7 or cosolutes involving Hofmeister salts,8 hydrophobic agents,9 sugars10 and most promisingly amino acid additives such as arginine salts.11 Additionally, a few studies have focused upon the influence of fundamental molecular aspects such as net charge, effective molecular size and shape, intermolecular interactions and net molecular dipole to the high concentration viscosity behavior of Special Issue: Advances in Biophysical and Bioanalytical Protein Characterization Received: Revised: Accepted: Published: 791

November 7, 2011 February 15, 2012 February 21, 2012 February 21, 2012 dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

Table 1. Mutations in the CDR Sequence of MAb-1 or MAb-2

different monoclonal antibodies (MAbs),12,13 and bovine serum albumin (BSA) as a function of solution pH.5 The results demonstrated that, among the fundamental molecular aspects such as size and shape, net charge, average net molecular dipole and physical intermolecular interactions, it is the nature and magnitude of the intermolecular interactions that are most critical in regulating the high concentration solution behavior. Furthermore, the nature of intermolecular interactions existing in solution could be strikingly different for different MAbs despite a 90−95% sequence identity. It then follows to question whether there are specific amino acid sequence motifs that could be correlated to the high concentration solution behavior of MAbs. Recent work has focused on this aspect by studying the amino acid sequence of two MAbs, MAb-1 and MAb-2, with substantially different viscosity and self-association behavior at high concentrations.14 Specifically, the study details the effect of replacing charged residues in the variable heavy (VH) chain, the variable light (VL) chain or in both VL and VH chains of MAb-1 and MAb-2 to minimize the sequence variation and the concomitant effect on the self-association and viscosity behavior of MAb-1 and MAb-2. The results demonstrated that exposed charge residues in the complementarity determining regions (CDR) of MAb-1 are critical in invoking attractive interactions leading to self-association and highly viscous behavior of MAb-1, wherein swapping of these residues with those present in the sequence of MAb-2 led to a loss in self-association and reduced viscosity of MAb-1 at high concentrations.14 However, the converse case where these charge residues were substituted in the sequence of MAb-2 did not result in an increase in viscosity or self-association behavior,14 and needed further investigation. A protein molecule in solution acquires a well-defined overall 3-dimensional structure with specific surface characteristics, which in turn dictates the intermolecular interactions and subsequent solution behavior. These surface characteristics become especially critical at higher protein concentrations

when the surface to surface separation distance is less than the molecular radii and the structure specific interactions arising from local details contribute to solution behavior in addition to the nonspecific forces. The present study focuses on the threedimensional electrostatic surfaces of MAb-1 and MAb-2 and the previously discussed mutants14 to gain a mechanistic insight into the origin of intermolecular interactions at the molecular level. Mutants with substitutions outside the CDR of MAb-2 were also investigated to understand additional factors responsible for viscosity and self-association behavior of MAb-1 and MAb-2. The incentive of this work lies in trying to understand the influence of specific residues in the sequence that can be modulated to address the viscosity and selfassociation properties and puts forth the possibility of a rational engineering/design of antibody molecules early on as an alternative to modulating solution conditions to optimize high concentration formulations.



MATERIALS AND METHODS Monoclonal Antibodies and Mutated Antibodies. The monoclonal antibodies MAb-1, MAb-2, M-1, M-5, M-6, M-7, M-10, M-13 and M-14 were produced at Genentech Inc. (South San Francisco, CA). The antibodies MAb-1 and MAb-2 have 92% sequence similarity and were constructed with the same human IgG1 framework and κ light chain whereby the major differences reside in the CDR and flanking amino acid residues. Previously, MAb-1 was studied by Liu et al.,2 Kanai et al.8 and Yadav et al.,4,6,14,15 and MAb-2 was studied by by Liu et al.2 and Yadav et al.6,14 Description of Mutants. The rationale for design of the charge-swap mutants, M-5, M-6, M-7 and M-10, has been described previously.14 Briefly, M-5, M-6 and M-7 represent mutations made in the sequence of MAb-1, whereas M-10 is the MAb-2 mutant. M-5 and M-6 have changes only in the VL or the VH chains, respectively. In the case of M-7, the charged residues in both the VL and VH chains were swapped. M-10 792

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

CP-25-1 measuring cell (Anton Paar, Graz, Austria). A solvent trap was used to prevent solvent evaporation. The sample viscosity was obtained for a 50 μL sample for 60 s with 1 s step resolution at a constant shear rate of 1000 s−1. Viscosity measurements are reported as an average of 10−12 of the stabilized viscosity measurements at 25 ± 0.1 °C. Sample analysis and data reporting were controlled using Anton Paar RheoPlus Software (Anton Paar, Graz, Austria). Dynamic Light Scattering (DLS). DLS studies for samples MAb-1, MAb-2, M-5, M-6, M-7 and M-10 were conducted at 25 ± 0.1 °C using a Malvern Zetasizer Nano Series (Worcestershire, U.K.) as described previously.14 Diffusion coefficients for M-13 and M-14 were measured using a DynaPro PlateReader Plus (Wyatt, Santa Barbara, CA) at a laser wavelength of 838.88 nm. Fifty microliter aliquots of filtered samples were transferred into sterile, 384-well, glass bottom Greiner Sensoplates (Greiner bio-one, Monroe, NC). Wyatt Technology Dynamics Software was used to schedule and automate three 20 s acquisitions for each sample. Sample replicate (n = 4) data were averaged to reduce systematic errors in sample preparation and analysis. Measurements were performed at 25 °C. The interaction parameter kD was obtained from the slope of linear fits to the mutual diffusion coefficient (Dm) versus protein concentration (c) plots:16

represents a mutant where the charged residues present in the sequence of MAb-1 were substituted in both the VL and VH chain sequence of MAb-2. Since the replacement of charge residues in the VL and VH chains of MAb-1 (mutants M-5, M6 and M-7) showed a decrease in self-association and viscosity,14 it was expected that, when these charged residues are substituted back in the sequence of MAb-2 (mutant M-10), M-10 should show an increase in viscosity and self-association. Although M-10 did show a slight decrease in repulsive interactions, no significant self-association or viscosity increase was observed.14 This suggested the involvement of additional factors that contribute to the high viscosity of MAb-1. The three-dimensional homology electrostatic surfaces model discussed in this work were generated and compared to understand this aspect. Simultaneously, the amino acid sequences of MAb-1 and MAb-2 were compared outside the CDRs to locate charge residue differences outside the CDR, which may be responsible for the observed behavior of M-10. There are two additional charge residues outside CDRs in the sequence of MAb-1, which are absent in the sequence of MAb2. M-13 and M-14 represent the MAb-2 mutant wherein these two residues have been substituted with the charged residues present in the sequence of MAb-1, in addition to the substitution already present in the VL and VH chain of MAb-2, i.e. M-10. A description of the different mutants used in this study has been summarized in Table 1. Sample Preparation. Sodium chloride, histidine base, histidine-hydrochloride monohydrate, sodium hydroxide and hydrochloric acid were obtained from Fisher Scientific (Fair Lawn, NJ, USA). All chemicals used were reagent grade or higher. The histidine-HCl (His-Cl) solution was prepared to pH 6.0 by combining 16.6 mM histidine-hydrochloride monohydrate, 13.3 mM histidine free base and deionized water purified using an Elga PURELAB Ultra (Celle, Germany) water purification system. Higher ionic strength buffers were prepared by adjusting the total solution ionic strength to 150 mM using sodium chloride. The MAbs were dialyzed into HisCl buffers using Pierce Slide-A-Lyzer dialysis cassettes or Millipore (Billerica, MA) Amicon Ultra centrifugation tubes (30 kDa MWCO). Following dialysis, MAb stock solutions were concentrated by ultrafiltration using Amicon Ultra centrifugal filtration devices (30 kDa MWCO). The MAb stock solutions were diluted to the desired concentration with the appropriate buffer and filtered through 0.22 μm Millex-W syringe filters (Millipore) prior to viscosity and light scattering measurements. After buffer exchange, the concentrations of the samples were determined using a UV spectrophotometer and an absorptivity of 1.6 (mg/mL)−1 cm−1 for MAb-1, M-1, M-5, M-6, M-7, M-11, and 1.5 (mg/mL)−1 cm−1 for MAb-2 and M10 at 280 nm for 0.1% IgG1 solutions. The solution pH was checked for each dialyzed sample. Required concentrations were prepared by dilution with the respective buffer. The Donnan and excluded volume contribution for high concentration samples was accounted for as described previously6 to achieve the final retentate pH and ionic strength as targeted after dialysis. Analytical Methods. Viscosity Measurements. The viscosities of samples MAb-1, MAb-2, M-5, M-6, M-7 and M10 were measured with an MCR300 cone and plate rheometer (Anton Paar, Ashland, VA) as described previously.14 The viscosities of M-13 and M-14 were measured using an Anton Paar Physica MCR 501 concentric cylinder cone and plate rheometer (Anton Paar, Graz, Austria) using an Anton Paar

Dm = Ds(1 + kDc)

(1)

where Ds is the self-diffusion coefficient (the value of Dm at infinite dilution as c → 0),17 kD is the interaction parameter, and c is the concentration of the protein (g/mL). The hydrodynamic radius (Rh) of the molecules can be estimated from the Ds using the Stokes−Einstein equation, Ds = kBT/ 6πηRh, where, kB is the Boltzmann constant, T is the temperature in kelvins, η is the solvent viscosity, i.e. c → 0. The estimated Rh from DLS measurements was substituted for “a” for calculating the underlying charge from the measured effective charge in eq 3. Membrane Confined Electrophoresis (MCE). The Debye− Hückel−Henry corrected charge (ZDHH) was determined from the steady state approach under an applied electric field using membrane confined electrophoresis (MCE).18,19 The electrophoresis was monitored, on 2 mg/mL IgG solutions, in a quartz cuvette the top and bottom of which were sealed with semipermeable cellulose membranes permeable to buffer but not to macroions. Separate buffer supply systems were used for the top and bottom electrodes to minimize the possibility of stray electrical paths that might bypass the cuvette. A constant flow of buffer prevents redistribution of buffer components during electrodialysis to ensure constant buffer composition in the analysis chamber. A weak electric field was applied across the cuvette, which results in the migration of macroions that was monitored using a collimated UV light and linear photodiode array to provide absorbance readings along path of migration in the cuvette. At steady state, when the electrophoretic migration balances the concentration gradient driven by back diffusion, the concentration of the macroion at a position x can be expressed as19 ⎧ Z*E ⎫ c(x) = c(xo)exp ⎨ (x − xo)⎬ ⎭ ⎩ kBT

(2)

where c(x) is the concentration at a position x, c(xo) is the concentration at a initial reference position xo, Z* is the effective electric charge of a macroion, E is the applied electric 793

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

surface definition with simple harmonic average smoothing.30 The resulting electrostatic surfaces were visualized by PyMoL. Static Light Scattering (SLS). SLS studies were conducted at 25 ± 0.1 °C using Malvern Instruments (Worcestershire, U.K.) Zetasizer Nano S. Sample preparation steps were similar to that used for DLS. The average scattered intensity was obtained using the attenuation corrected derived count rates collected at 173° as described elsewhere.15 The excess Rayleigh ratio, i.e. the ratio of the light scattering intensity of a solution in excess of the solvent to the intensity of incident light per unit volume and solid angle normalized with respect to intensity of incident light, can be expressed as35

field, kB is the Boltzmann constant and T is the sample temperature in kelvins. The effective electrical charge Z* was transformed to the underlying protein charge ZDHH using the Debye−Hückel−Henry equation:20,21 ⎧ 1 + κa ⎫ ⎬ ZDHH = Z*⎨ ⎩ f (κa) ⎭

(3)

where κ is the inverse Debye length, which is a function of solution ionic strength, a is the macroion radius out to the surface of shear and f(κa) is the Henry’s function defined by the ratio of the radius of curvature to the thickness of the electrical double layer around the particle.22 Homology Modeling and Electrostatic Potential Calculations. The homology models of MAb-1 and MAb-2 were generated by superimposing the crystal structure of domain fragments of anti-HER2 (PDBs 3D6G and 3N85) onto the atomic coordinates of the template structure23,24 using Modeller9v7.25 Briefly, the initial homology model of MAb-1 was built by aligning the sequences of anti-Her2 and MAb-1 using the Modeller9v7 “align2d” function. Following this, the initial homology model for each protein was generated from the anti-HER2 coordinates using the Modeler’s automated comparative modeling algorithm (automodel) and ga341 statistical potential for fold assessment. Hydrogen atoms were added to the initial homology model prior to energy minimization of the coordinates in vacuo using the GROMACS 4.5.3 molecular dynamics software suite and the steepest descent method with a step size of 0.01 nm in order to eliminate the steric clashes that resulted from the presence of the hydrogen atoms. Energy minimization continued until the maximum force of the system converged to a value of less than 500 kJ mol−1 nm−1. The final coordinates deviated from the initial structure by an rmsd of less than 0.5 Å but eliminated several steric clashes.26 PROCHECK27 was used to determine the quality of the stereochemistry of the energy minimized model, and no residues were found to be in the disallowed regions of the Ramachandran plot.28 The PyMoL29 molecular graphic system (Schrödinger LLC, San Diego, CA) was used for the 3D molecular visualization and performing point mutations to generate PDB files for the mutants followed by energy minimization using GROMACS 4.5.3.26 The adaptive Poisson−Boltzmann Solver version 1.3 (APBS)30 was used for generating the electrostatic potential surface for the MAbs and designed mutants. For APBS calculations, the PDB2PQR31,32 version 1.5 was used with the AMBER forcefield33 to generate the PQR file from the PDB coordinates, and utilized the PROPKA34 to determine the protonation state and radius of the individual atoms at pH 6.0 for the respective MAbs and designed mutants. PROPKA calculates the structure based pKa values for ionizable groups accounting for the pKa variations due to desolvation, hydrogen bonding and intraprotein interactions related to the positions and chemical nature of residues surrounding the specific ionization site.34 The pH-specific PQR file was subsequently used to calculate the electrostatic surface charge distribution of MAb-1 with a linearized Poisson−Boltzmann (PB) equation and cubic B-spline discretization of the charge distributions. PB calculations were performed at 298 K with a dielectric constant of 78.0 for water and 4.0 for the protein interior. The ion concentrations were set to 0.015 M with ionic radius of 2.0 Å. Ion accessibility is defined using an inflated van der Waals radius. The dielectric coefficient is defined using the molecular

R θ = KMw cP(q) S(q)

(4)

where, Mw is the molecular weight of the solute, c is the concentration in g/mL, the optical constant K = [2πn(dn/ dc)]2]/NAλo4 with NA corresponding to Avogadro’s number and dn/dc is the refractive index increment of the solute under a given set of solution conditions. The P(q) is the form factor accounting for intraparticle effects, and S(q) is the static structure factor accounting for interparticle interference to the scattered intensity. Both P(q) and S(q) are functions of scattering vector, q, which is related to the wavelength of incident light, λ, and the angle of observation, θ, as q=

4πn ⎛⎜ θ ⎞⎟ sin ⎝2⎠ λ

(5)

When the radius of the scattering particle, a, is much less than the wavelength of the incident light, λ, such that there are no multiple scattering effects, P(q) = 1. In the limit of low q, i.e. (q ≈ 0), such that q−1 is greater than the interparticle separation distance, S(q) may be expressed as a virial expansion in solute concentration such that at low concentration eq 4 may be written as36

Kc 1 = + 2B22 c R Mw

(6)

where B22 represents the second virial coefficient. For the present experimental setup, the product aq ≈ 0.14, with a = 5.5 nm being the typical radius of an IgG1 molecule, such that the limit q → 0 holds. Positive and negative values of B22 signify repulsive and attractive intermolecular interactions, respectively.37



RESULTS AND DISCUSSION Viscosity Measurements. Figure 1 summarizes the results of viscosity measurements on MAb-1, MAb-2 and the designed mutants. The viscosity data of all IgG1s except M-13 and M-14 have been reported and discussed previously.14 Briefly, the replacement of charge residues in either the VL (M-5) or VH (M-6) or both in VL and VH (M-7) led to a decrease in viscosity indicating the contribution of these charge residues to the viscosity behavior of MAb-1. However, the substitution of the same charge residues at respective positions in the sequence of MAb-2 (M-10) did not show an increased viscosity. M-13 and M-14 are MAb-2 mutants where in addition to the CDRs the charge substitutions were also made in the framework region (Table 1) to closely match the sequence of MAb-2 and MAb-1 outside the CDRs and verify if these contribute to the viscosity and self-associating behavior of MAb-1. However the replacement of charge residues outside the CDR (M-13 and M14) did not show any increase in viscosity behavior. This 794

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

indicated the contribution from direct charge−charge interactions.6 MAb-1 showed a kD = −19.79 ± 1.1 mL/g signifying the presence of attractive interactions, whereas MAb-2 showed intermolecular repulsion with a positive kD (+11.09 ± 0.07 mL/ g) at pH 6.0, 15 mM solution ionic strength. The replacement of charge residues in the VL and VH chains of MAb-2 (M-10) or in the VL and VH chains of MAb-2 as well as outside of the CDR (M-13 and M-14) showed a positive slope depicting intermolecular repulsions. Neither of the above mutations in the sequence of MAb-2 invoked strong attractive interactions as observed with MAb-1. The DLS results for MAb-1 mutants have been discussed previously.14 A transition from attractive to repulsive interactions was observed for M-5 and M-7, whereas M-6 showed only a slight decrease in the strength of intermolecular attractions (kD = −14.22 ± 1.2 mL/g). The kD data for all these molecules are tabulated in Table 2. Average Net Charge Measured on MAbs. The average net charge on MAbs at pH 6.0, computed theoretically from primary structure and experimental measurements using electrophoretic light scattering (ELS) (methodology described previously6,14) as well as membrane confined electrophoresis (MCE), are shown in Table 2. The average net charge computed from ELS data for the IgG1s has been reported and discussed previously.14 The measurement capabilities of ELS to determine the electrophoretic mobilities may be limited for various reasons such as joule heating, metal electrodes in contact with protein solution, measurements being performed using constant voltage rather than constant current and electrode polarization especially at high ionic strengths. The use of MCE circumvents most of these limitations and hence was used to determine the average net charge on MAbs and designed mutants. The Zav from ELS was lower with higher variability than the ZDHH from MCE with relatively smaller standard deviations. The discussion of techniques and variability/inconsistency of charge measured using different techniques such as MCE and ELS is outside the scope of this work, but will be discussed in forthcoming manuscripts that would also involve the use of other applicable techniques and various principles of charge estimation. Even though the two techniques showed some inconsistency, the trend observed in the measured net charge for different IgG1s was the same. From both MCE and ELS, M-5 and M-7 showed a higher net charge than MAb-1, whereas M-6 showed slightly lower net charge or nearly the same charge as (within ELS errors) MAb-1. M-10 on the other hand showed a lower net charge than MAb-2 with both techniques. Furthermore both Zav and ZDHH showed ∼15 units lower magnitude compared to the theoretical charge estimated from amino acid sequence, which appears to be a consequence of specific ion binding effects.38,39 Although the change in intermolecular interactions and viscosity behavior of M-5 and M-7 can be explained based on the increase in net molecular charge (Table 2) leading to intermolecular repulsions (Table 2, reference 13) and a concomitant loss in self-association and lower viscosity for these mutants (Figure 1), the same explanation does not account for either M-6 or M-10. M-6 and M-10 showed a decrease in net molecular charge compared to MAb-1 or MAb2, respectively, but the viscosity showed a sharp decrease for M6 and no change for M-10 (Figure 1) even though the intermolecular interactions were attractive for M-6 and repulsive for M-10 (Table 2). The inconsistency of the global

Figure 1. Viscosity profile of MAb-1, MAb-2 and the designed mutants as a function of IgG concentration at solution pH 6.0, 15 mM ionic strength. The viscosity was measured using a cone/plate measuring system at a shear rate of 1000/s.

indicates that there are still additional details to be understood in order to correlate the viscosity and self-associating behavior of MAb-1 to sequence specific motifs. Dynamic Light Scattering. Figure 2 shows the mutual diffusion coefficient (Dm) of MAb-1, MAb-2 and the designed

Figure 2. Mutual diffusion coefficient (Dm) as a function of IgG concentration at pH 6.0, 15 mM ionic strength. The lines are linear best fits with slope and intercept representing DskD and Ds (selfdiffusion coefficient), respectively.

MAb-2 mutants M-10, M-13 and M-14. The interaction parameter (kD) can be obtained from the slope of linear fits in Figure 2 (eq 1) and can be used to assess the nature of intermolecular interactions in the system. However, unlike B22, which is purely an equilibrium thermodynamic interaction parameter, the kD obtained from diffusion measurements also constitutes in itself a hydrodynamic contribution from the frictional drag. Hence, even though a positive value of kD signifies repulsive intermolecular interactions, only a negative kD of less than −5.34 mL/g corresponds to attractive interactions for MAbs. The kD of −5.34 mL/g represents the theoretical contribution from the frictional drag for MAbs with a hydrodynamic solvation volume of ∼2.9 cm3/g for a typical IgG1 molecule.6 For the studied IgG1s, all the negative kD values determined were more negative than −5.34 mL/g and hence 795

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

Table 2. The Average Theoretical and Experimental Net Charge on MAbs and Interaction Parameter kD at pH 6.0, 15 mM Solution Ionic Strength MAb-1 MAb-2 M-5 M-6 M-7 M-10 M-13 M-14

theor pIa

theor chargeb

7.5 8.8 8.6 7.5 8.6 8.3 8.3 7.9

22.6 31.9 29.1 18.9 25.4 29.2 29.2 27.2

Zav charge (ELS)c 4.58 8.31 8.61 4.95 7.39 4.98

± ± ± ± ± ±

ZDHH charge (MCE)d

1.05 0.68 1.39 0.45 0.64 0.72

6.26 11.86 10.34 3.42 12.42 8.43

± ± ± ± ± ±

0.19 0.47 0.41 0.1 0.37 0.42

kD (mL/g)e −19.79 11.09 8.04 −14.22 10.66 7.13 9.62 5.69

± ± ± ± ± ± ± ±

1.1 0.07 0.66 1.2 0.04 0.87 0.96 1.38

B22 × 10−5 (mol mL/g2)f −7.2 ± 15 ± 0.9 9.4 ± −4.8 ± 4.4 ± 7.9 ±

1.1 1.1 0.9 0.8 0.7

a

Theoretical pI computed from primary amino acid sequence. bTheoretical charge at pH 6.0 computed from primary amino acid sequence. Experimentally determined charge at pH 6.0, 15 mM ionic strength from Debye−Huckel approximation to linearized Poisson−Boltzmann equation, methodology detailed in ref 14. The errors represent standard deviation of 3−6 experimental replicates. dExperimentally determined charge at pH 6.0, 15 mM ionic strength using membrane confined electrophoresis. eInteraction parameter (kD) from DLS measurements, Table 2 in ref 14. The errors represent standard deviation of 3−6 experimental replicates. fSecond virial coefficient (B22) calculated from the slopes of Debye plots, Figure 5. c

nm. The Debye screening length (κ−1) at 15 mM ionic strength is 2.49 and 9.63 nm at 1 mM ionic strength suggesting that at concentrations above 100 mg/mL and low ionic strength the molecules no longer experience each other as point charges, but rather the molecular surfaces are so close that the interactions stemming from asymmetry of surface charge distribution become important. To verify whether the observed viscosity and self-association behavior of MAbs and designed mutants can be correlated with localized surface charge distribution, the electrostatic surfaces for MAbs were generated using APBS at pH 6.0, 15 mM solution ionic strength. Electrostatic Surface Charge Distribution. Figures 4A− H shows the electrostatic surface potentials for MAb-1, MAb-2 and the designed mutants. The encircled area highlights the change in charge surface charge distribution upon mutation of charge residues in the CDRs. MAb-1 shows a distinctively negatively charged surface in the CDR. Swapping charge residues in the VL (mutant M-5, Figure 4B) and both VL and VH (mutant M-7, Figure 4D) chain resulted in a loss of the negative patch in the CDR. However, swapping of charge residues in the VH chain (mutant M-6, Figure 4C) did not make any significant difference in the encircled electrostatic surface. MAb-2 (Figure 4E), on the other hand, did not carry the negative patch in the CDR and did not show as much heterogeneous surface as MAb-1. The substitution of charge residues in MAb-2 (mutant M-10, Figure 4F) did result in some negative surface in the CDR region (encircled area, Figure 4F), however not to the same extent as MAb-1 (Figure 4A). Similarly, M-13 and M-14 (Figure 4G,H) showed the same heterogeneous surface in the CDR as M-10. To elucidate the thermodynamic contribution of the surface charge distribution induced charge−charge interaction to the self-associating and viscosity behavior of IgG1s, the second virial coefficient (B22) was determined using static light scattering. Static Light Scattering. Figures 5A−D compares the Debye plots of MAb-1 and MAb-2 with the mutants, serving to highlight the change in intermolecular interactions upon mutation at pH 6.0, 15 mM ionic strength. The effect of an increase in solution ionic strength to 150 mM adjusted using NaCl on the B22 of MAb-1 and MAb-2 is also plotted in Figures 5A and 5D, respectively. The replacement of charge residues only in the VL chain of MAb-1 (M-5) resulted in transition of intermolecular interactions from attractive (MAb-1, B22 = −7.2 × 10−5 mol mL/g2) to repulsive (M-5, B22 = +9.4 × 10−5 mol

net molecular charge to the high concentration viscosity behavior is in agreement with previous observations.12 Even though, as discussed, the trending of net molecular charge is inconsistent with the high concentration viscosity behavior, the self-association and viscosity behavior at high concentrations is mediated primarily by electrostatic interactions at low ionic strengths and can be modulated by the addition of salts and counterions.2,4,6,8 As the molecules get relatively close to each other, the global net molecular charge may not drive the solution behavior. Figure 3 shows the average surface-to-surface interseparation distance, calculated from the inverse cube root of the protein number density (ρn−1/3) for an IgG1 molecule, using a typical molecular weight of 150 kDa and average Stokes diameter of 11 nm, and the Debye length (κ) plotted as a function of solution ionic strength. At concentrations of 100−200 mg/mL the average surface-to-surface distance decreases from 2.5 to 0.5

Figure 3. The surface-to-surface (S−S) interseparation distance (left axis) calculated for an IgG molecule as a function of concentration (bottom X axis), assuming spherical shape with typical diameter (dH) of 11 nm and Mw of 150 kD. The Debye length (right axis) calculated as a function of solution ionic strength (top X axis) . 796

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

Figure 4. The electrostatic potential surface for (A) MAb-1, (B) M-5, (C) M-6, (D) M-7, (E) MAb-2, (F) M-10, (G) M-13 and (H) M-14 at pH 6.0, 15 mM solution ionic strength generated using APBS plugin in Pymol. The red and blue contours indicate −1 and +1 KT/e isosurface potential.

mL/g2, Figure 5A). Interestingly, the replacement of charge residues only in the VH chain of MAb-1 (M-6) did not result in a significant change in attractive interactions (M-6, B22 = −4.8 × 10−5 mol mL/g2, Figure 5C). M-7 with replacement of charge residues in both the VL and VH chains of MAb-1 showed intermolecular repulsion (M-7, B22 = +4.4 × 10−5 mol mL/g2, Figure 5B). M-10 where the charge residues of MAb-1 have been substituted in the VL and VH sequence of MAb-2 showed only a slight decrease in intermolecular repulsion (MAb-2, B22 = +1.5 × 10−4 mol mL/g2; and M-10, B22 = +7.9 × 10−5 mol mL/g2, Figure 5D). Increasing the solution ionic strength increased the B22 of MAb-1 (B22 = −4.8 × 10−5 mol mL/g2 at 150 mM, Figure 5A), indicating that attractive interactions still persist in MAb-1. Conversely, MAb-2 showed a transition from repulsive to attractive interactions with a slightly negative B22 value (MAb-2; B22 = −1.2 × 10−5 mol mL/ g2 at 150 mM, Figure 5D). Both the impact of solution ionic strength and charge swap mutations indicate the involvement of

surface charge residues in governing the intermolecular interactions of these MAbs. The B22 values correlate well with protein precipitation, solubility, crystallization and aggregation.40−45 A distinction however needs to be made as to how the nature of intermolecular interactions affects viscosity. The viscosity, or the resistance to flow, is a result of momentum transfer between flowing layers, which is affected by how the molecules in the system interact. The presence of repulsive interactions (B22 > 0) has been termed “good” solvent conditions that prevent molecular association and enhance the colloidal stability.43 Conversely, attractive interactions enhance selfassociation to favor aggregation or even precipitation of macromolecules from solution and are termed “poor” solvent conditions.43 Even though the intermolecular repulsions would result in an increase in solution viscosity over that of the noninteracting case, in comparison to attractive interactions the presence of intermolecular repulsions will enhance momentum 797

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

Figure 5. Debye plots for (A) MAb-1 and M-5, (B) MAb-1 and M-6, (C) MAb-1 and M-7, (D) MAb-2 and M-10. The lines are linear best fits with slope and intercept representing 2B22 and 1/Mw respectively.

Figure 6. Schematic differentiating the effect of long-range network versus aggregation on the solution viscosity.

transfer and hence results in a relatively lower viscosity. On the contrary, intermolecular attraction increases the self-association and aggregation behavior thereby hindering the momentum transfer and hence slowing down the molecular diffusivity, as indicated by the decrease in Dm with increasing concentration for MAb-1 (Figure 2). Thus, it is critical to note that although reversible self-association would increase the solution viscosity at concentrations where the equilibrium favors the selfassociated state, that irreversible aggregation resulting in a phase separated solute precipitation will lead to a decrease in

solution viscosity. As a further point for clarification, Figure 6 provides a pictorial representation of the difference between self-association and irreversible aggregation. The term “self-association” as depicted on the right-hand side of Figure 6 simply implies a molecular alignment leading to long-range order or a transient network in solution,6 such that at the time scale of measurement the molecule appears to be bigger with a lower Dm, higher dH or higher apparent Mw than an ideal case monomer. However, these are transient interactions and are completely reversible as the solution 798

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

condition approaches ideality (i.e., c → 0), corresponding to monomeric D s , d H or absolute M w . At a particular concentration, such interactions would result in a higher viscosity than the ideal non-interacting case due to mutual drag experienced by a molecule from neighboring molecules during flow. The presence or absence of such self-associated or equilibrium clusters has been a topic of debate recently.46−48 Conversely, physical aggregation, as depicted on the left-hand side of Figure 6, will drive the solution viscosity to decrease due to a decrease in excluded volume. For instance, the increase in nondissociable aggregate content from 0.2% to 11% in MAb-1 solution, determined by size exclusion chromatography as well as analytical ultracentrifugation by Liu et al.,2 led to a decrease in MAb-1 solution viscosity from 60 to 41 cps (Table 1, reference 2). If all the protein molecules were to aggregate and precipitate out to form a suspension, the solution viscosity would decrease to approach that of the solvent. The following section discusses the possibility of such transient networks affecting the momentum transfer in solution and hence viscosity. Correlation of Surface Charge Distribution with Intermolecular Interaction. A surface where the charge is spread evenly would favor intermolecular repulsion and hinder self-association, which would decrease the apparent weight average molecular weight (Mw,app) with increasing concentration. Conversely, a highly asymmetric surface charge distribution as in MAb-1 (Figure 4A) will allow oppositely charged patches to attract and interact favorably to result in an increase in self-associating and aggregation behavior. Furthermore, at small interseparation distances the molecular surfaces will present complementary orientations to align the opposite charges in an effort to minimize the free energy of the system, possibly resulting in a long-range order and restricting mutual diffusion and momentum transfer to result in a higher energy to be dissipated in a viscous flow. The contribution of these hydrodynamic interactions can be visualized by combining the static and dynamic light scattering data. The strength of hydrodynamic interactions is given by the hydrodynamic function H(q), which accounts for change in frictional coefficient due to collective hydrodynamic effects.49 In the hydrodynamic regime, the contribution of the hydrodynamic interactions H(q→0) to Dm can be represented analogously to eq 44 in Jones and Pusey49 as Dm = Ds

1 − H(q → 0) S(q → 0)

spacing at the highest concentration used (12 mg/mL), calculated as the inverse cube root of protein number density, ρn−1/3, was ∼27 nm (Figure 3) whereas q−1 was ∼38 nm for the current configuration of the optics used for light scattering measurements. Information about S(q→0) can be obtained from rearranging eq 4, which signifies the ratio of apparent molecular weight to molecular weight obtained for ideal solution at a fixed solute concentration and can be expressed as Mapp = Mw S(q → 0)

(8)

where Mapp is the apparent molecular weight obtained in presence of intermolecular interactions and Mw signifies molecular weight observed in the limit of infinite dilution (c → 0). For an ideal solution, when the molecules are well separated such that the intermolecular interactions are negligible, S(q→0) equals one. H(q→0), on the other hand can be obtained by combining eq 4 and 7 to give50 −1

1 − H(q → 0) =

Dm ⎛ Kc ⎞ ⎜ ⎟ DsMw ⎝ R θ ⎠

(9)

Similarly, in the absence of any hydrodynamic effects H(q→0) equals one. The S(q→0) and H(q→0) obtained using SLS and DLS data are plotted as a function of solute concentration in Figure 7. MAb-1 showed a relatively more heterogeneous surface wherein the negative surface on the CDR can interact to attract the positively charged regions. This is reflected in the negative B22 (Figure 5A). It is significant that MAb-1 shows attractive interactions despite carrying a net positive charge (Table 2) at pH 6.0, substantiating that the molecules do not interact as point charges but instead interact as a result of the surface charge distribution and possible other localized molecular details. The presence of attractive interactions favors selfassociating behavior resulting in an increase in structure factor S(q→0) with c (Figure 7A) and hence a decrease in hydrodynamic interaction H(q→0) (increase in 1 − H(q→0) with c, Figure 7B) indicating a decrease in momentum transfer in MAb-1 which results in higher viscosity for MAb-1 at high concentrations (Figure 1). Conversely, the MAb-2 surface exhibits less charge asymmetry favoring intermolecular repulsions (positive B22, Figure 5D) which disfavors selfassociation as reflected in a decrease in structure factor S(q→0) with c, Figure 7A). The repulsion induced increase in momentum transfer results in an increase in hydrodynamic interaction H(q→0) (decrease in 1-H(q→0) with c, Figure 7B) for MAb-2 and consequently a lower viscosity for MAb-2 (Figure 1). The effect of salt further supports the involvement of charge heterogeneity based electrostatic interactions in regulating the viscosity and self-associating behavior of MAb-1 and MAb-2. The mitigation of surface charge induced electrostatic interaction with added salt, due to either counterion screening or specific ion binding,38,39 resulted in a decrease in attraction (Figure 5A) and lower apparent Mw for MAb-1 (S(q→0) with c, Figure 7A), whereas, for MAb-2, it resulted in a negative B22 (Figure 5D) and increase in the self-associating behavior of MAb-2 as reflected in an increase in S(q→0) with c, Figure 7A. Mutating the charge residues in the VL and VH chains of MAb-1, M-5 and M-7, respectively, led to the loss of negative potential surface in the CDR (Figure 4C,D) and hence the transition of intermolecular attraction to repulsive interaction

(7)

where Dm and Ds are the mutual and self-diffusion coefficients respectively, H(q→0) is the hydrodynamic function which accounts for any change in friction coefficient affecting momentum transfer and S(q→0) is the static structure factor, which represents the contribution of interparticle interference to diffusivity in the limit q → 0. The light scattering measurements in the present work are in this hydrodynamic regime, such that the measurement times in DLS (τD) are long compared to the average collision time (τc), and the solution conditions fall in the long wavelength limit such that d ≪ q−1, where d is the mean interparticle spacing and q is the scattering vector (eq 5). For DLS measurements the τc, calculated using the equation50 τc = (4πDsdHρn)−1, varies from ∼1 × 10−5 s (at 3 mg/mL) to ∼3 × 10−6 s (at 12 mg/mL), The τD calculated from the decay of the correlation function, ∼ 4 × 10−5 s, is long relative to the mean collision time (τc). The interparticle 799

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

Even though the present work explains the behavior of M-10, M-13 and M-14, it brings forth a critical aspect with respect to proper conformational orientation of residues in MAb 3D structure as emphasized by the behavior of M-6. M-6, with three histidyl residues substituted in the CDR H3 of MAb-1, showed a negative surface potential resulting in a surface charge heterogeneity comparable to MAb-1 (Figure 4A,C). The intermolecular interactions as assessed from kD (Table 2) or B22 (Figure 5B) were also of similar magnitude with only a slight decrease in long-range order S(q→0) and hydrodynamic interactions (Figure 7A,B). However, the viscosity showed a significant drop compared with MAb-1 (Figure 1). First, these results illustrate the limitation of dilute solution techniques in quantitatively predicting the high concentration behavior. Additionally, the behavior of M-6 suggests that the closely placed histidyl residues in the CDR H3 play a critical role in the self-associating and highly viscous behavior of MAb-1 where, in addition to surface charge asymmetry, the proper conformational placement of charge residues is substantially important. The underlying role of these histidyl residues in governing the self-association and highly viscous behavior of MAb-1 is also evident from the pH dependent viscosity profile of MAb-1. At high concentrations, the MAb-1 solutions are most viscous at pH 6.0,2,4,6 close to the pKa for histidyl residues, and the viscosity drops substantially with a unit change in solution pH to either the acidic or basic side of pH 6.0, emphasizing the considerable impact of the ionization state of histidyl residues.4



CONCLUSION The electrostatic surface charge distribution of proteins plays a dominant role in governing the intermolecular interactions and subsequently the high concentration self-association and viscosity behavior. Variation in the charge distribution reduces the net repulsion between the protein molecules, and could result in orientation dependent intermolecular attractions despite a net positive molecular charge. In particular, the effect of patchy surface charge distribution gets magnified at high concentrations where the oppositely charged patch can align to result in long-range order and highly viscous self-associated systems as exemplified by MAb-1.

Figure 7. The change in (A) static structure factor (S(q→0) = Mw,app/ Mw) and (B) hydrodynamic interactions (H(q→0)) as a function of IgG1 concentration. The lines simply connect the data points to guide the eye.

for M-5 and M-7 (positive B22, Figure 5A,C) and subsequently the loss of long-range order and self-association (S(q→0), Figure 7A). The repulsion induced increase in the momentum transfer (H(q→0), Figure 7B) results in a lower energy dissipated during viscous flow and consequently a lower viscosity for M-5 and M7 (Figure 1). The change in the electrostatic surface potential explains the behavior of M-10 as well. The replacement of charge residues in the sequence of MAb-2 did invoke some negative potential in the CDR region, however, not to the same extent as in MAb-1. This increased negative potential in CDR is reflected as a small decrease in repulsive interaction for M-10 (less positive B22 of M-10 than MAb-2, Figure 5 D) and a small increase in the extent of order and self-association (S(q→0), Figure 7A) and a decrease in momentum transfer H(q→0) compared with that of MAb-2. Hence, M-10 still exhibits similar viscosity as MAb-2, Figure 1. Similarly, M-13 and M-14 showed similar electrostatic potential surface as MAb-10 despite replacing the charge residues outside the CDR, thereby still exhibiting intermolecular repulsion (positive kD, Figure 2) and a lower viscosity. The change in self-association behavior observed for MAb-1, MAb-2 and the designed mutants M-7 and M-10 agrees with the corrected apparent weight average molecular weight observed from sedimentation equilibrium analysis from preparative analytical ultracentrifugation experiments.14



AUTHOR INFORMATION

Corresponding Author

*Late Stage Product Development, Genentech, Inc., 1 DNA Way, S. San Francisco, CA 94080. Tel: (650) 225 2077. Fax: (650) 225 2764. E-mail: [email protected]. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS The authors wish to thank the Antibody Engineering Research Group and Samantha Lien for their help in designing the mutants; Wayne Lilyestrom for help with 3D homology modeling for MAbs; and Tom Patapoff, Yatin Gokarn, Sreedhara Alavattam and Mary Cromwell for their enriching scientific discussions, support and careful review of the manuscript.



REFERENCES

(1) Shire, S. J.; Shahrokh, Z.; Liu, J. Challenges in the development of high protein concentration formulations. J. Pharm. Sci. 2004, 93 (6), 1390−1402. 800

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

(2) 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 (9), 1928−1940. (3) Saluja, A.; Badkar, A. V.; Zeng, D. L.; Nema, S.; Kalonia, D. S. Application of high-frequency rheology measurements for analyzing protein-protein interactions in high protein concentration solutions using a model monoclonal antibody (IgG2). J. Pharm. Sci. 2006, 95 (9), 1967−1983. (4) 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 (3), 1152−1168. (5) Yadav, S.; Shire, S. J.; Kalonia, D. S. Viscosity analysis of high concentration bovine serum albumin aqueous solutions. Pharm. Res. 2011, 28 (8), 1973−1983. (6) Yadav, S.; Shire, S. J.; Kalonia, D. S. Viscosity behavior of high concentration monoclonal antibody solutions: Correlation with interaction parameter and electroviscous effects. J. Pharm. Sci. 2012, 101 (3), 998−1011. (7) 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. 2009, 99 (1), 82−93. (8) 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 (10), 4219−4227. (9) Du, W.; Klibanov, A. M. Hydrophobic salts markedly diminish viscosity of concentrated protein solutions. Biotechnol. Bioeng. 2011, 108 (3), 632−636. (10) He, F.; Woods, C. E.; Litowski, J. R.; Roschen, L. A.; Gadgil, H. S.; Razinkov, V. I.; Kerwin, B. A. Effect of sugar molecules on the viscosity of high concentration monoclonal antibody solutions. Pharm. Res. 2011, 28 (7), 1552−1560. (11) Liu, J.; Shire, S. J. Reduced-viscosity concentrated protein formulations. WO2002030463A2, 2002. (12) 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 (12), 4812−4829. (13) Chari, R.; Jerath, K.; Badkar, A. V.; Kalonia, D. S. Long- and short-range electrostatic interactions affect the rheology of highly concentrated antibody solutions. Pharm. Res. 2009, 26 (12), 2607− 2618. (14) 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 (7), 1750−1764. (15) Yadav, S.; Scherer, T. M.; Shire, S. J.; Kalonia, D. S. Use of dynamic light scattering to determine second virial coefficient in a semidilute concentration regime. Anal. Biochem. 2011, 411 (2), 292− 296. (16) Brown, W.; Nicolai, T., Dynamic Light Scattering: The Method and Some Applications; Oxford University Press: New York, 1993. (17) Veldkamp, W. B.; Votano, J. R. Effects of intermolecular interaction on protein diffusion in solution. J. Phys. Chem. 1976, 80 (25), 2794−2801. (18) Ridgeway, T. M.; Hayes, D. B.; Moody, T. P.; Wilson, T. J.; Anderson, A. L.; Levasseur, J. H.; Demaine, P. D.; Kenty, B. E.; Laue, T. M. An apparatus for membrane-confined analytical electrophoresis. Electrophoresis 1998, 19 (10), 1611−1619. (19) Laue, T. M.; Shepard, H. K.; Ridgeway, T. M.; Moody, T. P.; Wilson, T. J. Membrane-confined analytical electrophoresis. Methods Enzymol. 1998, 295, 494−518. (20) Moody, T. P.; Kingsbury, J. S.; Durant, J. A.; Wilson, T. J.; Chase, S. F.; Laue, T. M. Valence and anion binding of bovine ribonuclease A between pH 6 and 8. Anal. Biochem. 2005, 336 (2), 243−252. (21) Stigter, D. A novel interpretation of steady-state electrophoresis experiments. J. Phys. Chem. B 2000, 104 (15), 3402−3404.

(22) Hunter, R. J., Charge and Potential Distribution at Interface. In Zeta Potential in Colloid Science Principles and Application; Ottewill, R. H., Rowell, R. L., Eds.; Academic Press: New York, 1981; pp 11−58. (23) Padlan, E. A. Anatomy of the antibody molecule. Mol. Immunol. 1994, 31 (3), 169−217. (24) http://www.umass.edu/microbio/rasmol/padlan.htm, Atomic Coordinate Files for Whole IgG1. (25) Eswar, N.; John, B.; Mirkovic, N.; Fiser, A.; Ilyin, V. A.; Pieper, U.; Stuart, A. C.; Marti-Renom, M. A.; Madhusudhan, M. S.; Yerkovich, B.; Sali, A. Tools for comparative protein structure modeling and analysis. Nucleic Acids Res. 2003, 31, 3375−3380. (26) Berendsen, H. J. C.; van der Spoel, D.; van Drunen, R. GROMACS: A message-passing parallel molecular dynamics implementation. Comput. Phys. Commun. 1995, 91, 43−56. (27) Laskowski, R. A.; Macarthur, M. W.; Moss, D. S.; Thornton, J. M. {PROCHECK}: a program to check the stereochemical quality of protein structures. J. Appl. Crystallogr. 1993, 26, 283−291. (28) Hooft, R. W. W.; Sander, C.; Vriend, G. Objectively judging the quality of a protein structure from a Ramachandran plot. Comput. Appl. Biosci. 1997, 13 (4), 425−430. (29) Schrodinger, LLC, The PyMOL Molecular Graphics System, Version 1.3r1. 2010. (30) Baker, N. A.; Sept, D.; Joseph, S.; Holst, M. J.; McCammon, J. A. Electrostatics of nanosystems: Application to microtubules and the ribosome. Proc. Natl. Acad. Sci. U.S.A. 2001, 98 (18), 10037−10041. (31) Dolinsky, T. J.; Czodrowski, P.; Li, H.; Nielsen, J. E.; Jensen, J. H.; Klebe, G.; Baker, N. A. PDB2PQR: expanding and upgrading automated preparation of biomolecular structures for molecular simulations. Nucleic Acids Res. 2007, 35 (Web Server issue), W522− W525. (32) Dolinsky, T. J.; Nielsen, J. E.; McCammon, J. A.; Baker, N. A. PDB2PQR: An automated pipeline for the setup of PoissonBoltzmann electrostatics calculations. Nucleic Acids Res. 2004, 32 (Web Server issue), W665−W667. (33) Sorin, E. J.; Pande, V. S. Exploring the helix-coil transition via all-atom equilibrium ensemble simulations. Biophys. J. 2005, 88 (4), 2472−2493. (34) Li, H.; Robertson, A. D.; Jensen, J. H. Very fast empirical prediction and rationalization of protein pKa values. Proteins: Struct., Funct., Bioinf. 2005, 61 (4), 704−721. (35) Magid, L. In Dynamic Light Scattering: The Method and Some Applications; Brown, W., Ed.; Oxford University Press: New York, 1993; p 554. (36) Yamakawa, H. Modern Theory of polymer Solution; Harper and Row: New York, 1971; Chapter 26. (37) Wilson, W. W. Light scattering as a diagnostic for protein crystal growthA practical approach. J. Struct. Biol. 2003, 142 (1), 56−65. (38) Gokarn, Y. R.; Fesinmeyer, R. M.; Saluja, A.; Razinkov, V.; Chase, S. F.; Laue, T. M.; Brems, D. N. Effective charge measurements reveal selective and preferential accumulation of anions, but not cations, at the protein surface in dilute salt solutions. Protein Sci. 2011, 20 (3), 580−587. (39) Laue, T.; Demeler, B. A postreductionist framework for protein biochemistry. Nat. Chem. Biol. 2011, 7 (6), 331−334. (40) Chi, E. Y.; Krishnan, S.; Randolph, T. W.; Carpenter, J. F. Physical Stability of Proteins in Aqueous Solution: Mechanism and Driving Forces in Nonnative Protein Aggregation. Pharm. Res. 2003, 20 (9), 1325−1336. (41) Ho, J. G. S.; Middelberg, A. P. J; Ramage, P.; Kocher, H. P. The likelihood of aggregation during protein renaturation can be assessed using the second virial coefficient. Protein Sci. 2003, 12 (4), 708−716. (42) Curtis, R. A.; Prausnitz, J. M.; Blanch, H. W. Protein-protein and protein-salt interactions in aqueous protein solutions containing concentrated electrolytes. Biotechnol. Bioeng. 1998, 57 (1), 11−21. (43) George, A.; Wilson, W. W. Predicting protein crystallization from a dilute solution property. Acta Crystallogr., Sect. D: Biol. Crystallogr. 1994, D50 (4), 361−365. 801

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802

Molecular Pharmaceutics

Article

(44) Ruppert, S.; Sandler, S. I.; Lenhoff, A. M. Correlation between the Osmotic Second Virial Coefficient and the Solubility of Proteins. Biotechnol. Prog. 2001, 17 (1), 182−187. (45) Valente, J. J.; Payne, R. W.; Manning, M. C.; Wilson, W. W.; Henry, C. S. Colloidal Behavior of Proteins: Effects of the Second Virial Coefficient on Solubility, Crystallization and Aggregation of Proteins in Aqueous Solution. Curr. Pharm. Biotechnol. 2005, 6 (6), 427−436. (46) Shukla, A.; Mylonas, E.; Di Cola, E.; Finet, S.; Timmins, P.; Narayanan, T.; Svergun, D. I. Absence of equilibrium cluster phase in concentrated lysozyme solutions. Proc. Natl. Acad. Sci. U.S.A. 2008, 105 (13), 5075−5080. (47) Stadler, A. M.; Schweins, R.; Zaccai, G.; Lindner, P. Observation of a large-scale superstructure in concentrated hemoglobin solutions by using small angle neutron scattering. J. Phys. Chem. Lett. 2010, 1 (12), 1805−1808. (48) Stradner, A.; Sedgwick, H.; Cardinaux, F.; Poon, W. C. K.; Egelhaaf, S. U.; Schurtenberger, P. Equilibrium cluster formation in concentrated protein solutions and colloids. Nature 2004, 432 (7016), 492−495. (49) Jones, R. B.; Pusey, P. N. Dynamics of suspended colloidal spheres. Annu. Rev. Phys. Chem. 1991, 42 (1), 137−169. (50) Muschol, M.; Rosenberger, F. Interactions in undersaturated and supersaturated lysozyme solutions: Static and dynamic light scattering results. J. Chem. Phys. 1995, 103 (24), 10424−10432.

802

dx.doi.org/10.1021/mp200566k | Mol. Pharmaceutics 2012, 9, 791−802