Determination of Protein-Protein Interactions at High Co-Solvent Concentrations Using Static and Dynamic Light Scattering.

Protein-protein interactions are commonly measured in terms of the second osmotic virial coefficient, B22 from static light scattering (SLS) or the interaction parameter, kD from dynamic light scattering (DLS). Often these measurements are carried out at high co-solvent compositions, where correction factors are required for the light scattering analysis. For lysozyme in aqueous solutions containing the co-solvents NaCl, arginine chloride, urea, sucrose or guanidine chloride, we show that B22 determination requires using in the light scattering equation the refractive index increment of the protein measured at constant solvent chemical potential. Because the increment decreases with increasing co-solvent composition, using a constant value can lead to mis-interpretation of protein-protein interaction trends deduced from the B22 measurements. Furthermore, there is a contribution to the intensity auto-correlation function measured by dynamic light scattering due to co-solvents. This effect is removed by including longer delay times when fitting the cumulant analysis to determine the diffusion coefficients. We show that an experimentally observed correlation between B22 and kD is recovered once these correction factors have been applied. The findings are particularly relevant to biopharmaceutical industry, where B22 and kD measurements are used for screening excipient effects in liquid formulations.

Novel salts of dipicolinic acid as viscosity modifiers for high concentration antibody solutions.

Concentrated monoclonal antibody (mAb) solutions can lead to high viscosity as a result of protein-protein interactions and pose challenges for manufacture. Dipicolinic acid (DPA, pyridine-2,6-dicarboxylic acid) is a potential excipient for reduction of protein solution viscosity and here we describe new DPA salts with improved aqueous solubility. Crystallinity and solubility screens identified ethanolamine and diethanolamine as two promising counterions which generated crystalline, high melting point, anhydrous salt forms of DPA at 2:1 M stoichiometry. These salts significantly reduced the solution viscosity of five mAbs, equal to or better than that for the addition of arginine hydrochloride at equivalent osmolality. The presence of the DPA salts in solution did not significantly perturb the melting point of the mAbs, as determined by calorimetry, indicating an absence of any destabilization of protein conformation. Addition of the DPA salts to the mAb solutions stored at 5 °C over 6 months did not cause additional loss of the monomer fraction, though evidence of increased aggregation and fragmentation for three of the five mAbs was observed during 40 °C (accelerated and stressed) storage. Overall, this study demonstrates that ethanolamine-DPA and diethanolamine-DPA can serve as two novel excipients for viscosity reduction and could be considered by formulation scientists when developing highly concentrated mAb formulations.

Rapid and accurate in silico solubility screening of a monoclonal antibody library.

Antibodies represent essential tools in research and diagnostics and are rapidly growing in importance as therapeutics. Commonly used methods to obtain novel antibodies typically yield several candidates capable of engaging a given target. The development steps that follow, however, are usually performed with only one or few candidates since they can be resource demanding, thereby increasing the risk of failure of the overall antibody discovery program. In particular, insufficient solubility, which may lead to aggregation under typical storage conditions, often hinders the ability of a candidate antibody to be developed and manufactured. Here we show that the selection of soluble lead antibodies from an initial library screening can be greatly facilitated by a fast computational prediction of solubility that requires only the amino acid sequence as input. We quantitatively validate this approach on a panel of nine distinct monoclonal antibodies targeting nerve growth factor (NGF), for which we compare the predicted and measured solubilities finding a very close match, and we further benchmark our predictions with published experimental data on aggregation hotspots and solubility of mutational variants of one of these antibodies.

Coarse-Grained Modeling of Antibodies from Small-Angle Scattering Profiles.

Predicting the concentrated solution behavior for monoclonal antibodies requires developing and using minimal models to describe their shape and interaction potential. Toward this end, the small-angle X-ray scattering (SAXS) profiles for a monoclonal antibody (COE-03) have been measured under solution conditions chosen to produce weak self-association. The experiments are complemented with molecular simulations of a three-bead antibody model with and without interbead attraction. The scattering profile is extracted directly from the molecular simulation to avoid using the decoupling approximation. We examine the ability of the three-bead model to capture features of the scattering profile and the dependence of compressibilty on protein concentration. The three-bead model is able to reproduce generic features of the experimental structure factor as a function of wave vector S(k) including a well-defined shoulder, which is a consequence of the planar structure of the antibody, and a well-defined minimum in S(k) at k ∼ 0.025 Å-1. We also show the decoupling approximation is incapable of accounting for highly anisotropic shapes. The best-fit parameters obtained from matching spherical models to simulated scattering profiles are protein concentration dependent, which limits their applicability for predicting thermodynamic properties. Nevertheless, the experimental compressibility curves can be accurately reproduced by an appropriate parametrization of the Baxter adhesive model, indicating the model provides a semiempirical equation of state for the antibody. The results provide insights into how equations of state can be improved for antibodies by accounting for their anisotropic shapes.

Maternal low-protein diet programs cardiac beta-adrenergic response and signaling in 3-mo-old male offspring.

Low birth weight in humans is associated with an increased risk of cardiovascular disease. Humans with heart failure have a reduced beta-adrenergic response. The aim of this study was to investigate the hemodynamic response to the beta-adrenergic agonist isoproterenol and to identify molecular deficiencies that may be predictive of cardiac failure in a low-birth weight rodent model that develops insulin resistance and type 2 diabetes in adulthood. Wistar rats were fed a control or a low-protein (LP) diet throughout pregnancy and lactation. The resting heart rate and blood pressure of the 3-mo-old male offspring of these dams, termed "control" and "LP" groups, respectively, and their responses to isoproterenol (ISO) infusion were monitored by radiotelemetry. The protein expression of beta-adrenergic signaling components was also measured by Western blot analysis. Basal heart rate was increased in LP offspring (P<0.04), although mean arterial pressure was comparable with controls. Chronotropic effects of ISO were blunted in LP offspring with significant delays to maximal response (P=0.01), a shorter duration of response (P=0.03), and a delayed return to baseline (P=0.01) at the lower dose (0.1 microg.kg-1.min-1). At the higher dose (1.0 microg.kg-1.min-1 ISO), inotropic response was blunted (P=0.03) but quicker (P=0.001). In heart tissue of LP offspring, beta1-adrenergic receptor expression was reduced (P<0.03). beta1-Adrenergic receptor kinase and both stimulatory and inhibitory G protein levels remained unchanged, whereas beta-arrestin levels were higher (P<0.03). Finally, insulin receptor-beta expression was reduced in LP offspring (P<0.012). LP offspring have reduced beta-adrenergic responsiveness and attenuated adrenergic and insulin signaling, suggesting that intrauterine undernutrition alters heart failure risk.