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[Display omitted] • Improved mechanistic understanding of the interactions in aqueous protein solutions. • Rapid and resource-efficient identification of potential excipient mixtures by methodical selection. • Correlation between charge & side chain length of the amino acid and the respective influence on the protein stability. • Ratio/molalities of excipients as decisive factor in design of aqueous protein formulations. • Potential of transferability of excipient mixture choice to different proteins. Still today, high-concentration protein formulations are often developed based on high-throughput experimental screening approaches. Although likely delivering working formulations, these approaches do not lead to a deep/mechanistic understanding of the protein phase behavior in solution. Within this work, we thus optimized and enhanced a recent approach for an initial low effort selection of potential excipients and excipient mixtures to be used in high-concentration protein formulations. This approach considers both: molecular interactions and thermodynamic determinants to access the phase behavior of the proteins in solution, as well as pharmaceutical engineering boundaries (such as osmotic pressure and osmolality) to deliver on optimal formulation conditions. Water activity coefficient γ W -calculations (used to describe the protein environment in solution), unfolding temperature (conformational stability) and protein-protein interactions (colloidal stability) are used as determinants. Amino acids (20 proteinogenic amino acids), selected amino acid mixtures, as well as mixtures of amino acids and trehalose (l -arginine-trehalose; l -histidine-trehalose) are considered as model excipients. The approach is extends by studying the long-term stability of the predicted formulation conditions for a γ-globulin from human blood and denosumab. The results reveal, that by combining protein-specific experiments as well as model-based studies for the selection of excipient mixtures in high concentration protein formulations, the effort as well as the resource requirements can be reduced significantly. [ABSTRACT FROM AUTHOR]

Protein self-interactions measured via second osmotic virial coefficients ( B 22 ) and dynamic light scattering interaction parameter values ( k D ) are often used as metrics for assessing the favorability of protein candidates and different formulations during monoclonal antibody (MAb) product development. Model predictions of B 22 or k D typically do not account for glycans, though glycosylation can potentially impact experimental MAb self-interactions. To the best of our knowledge, the impact of MAb glycosylation on the experimentally measured B 22 and k D values has not yet been reported. B 22 and k D values of two fully deglycosylated MAbs and their native (i.e., fully glycosylated) counterparts were measured by light scattering over a range of pH and ionic strength conditions. Significant differences between B 22 and k D of the native and deglycosylated forms were observed at a range of low to high ionic strengths used to modulate the effect of electrostatic contributions. Differences were most pronounced at low ionic strength, indicating that electrostatic interactions are a contributing factor. Though B 22 and k D values were statistically equivalent at high ionic strengths where electrostatics were fully screened, we observed protein-dependent qualitative differences, which indicate that steric interactions may also play a role in the observed B 22 and k D differences. A domain-level coarse-grained molecular model accounting for charge differences was considered to potentially provide additional insight but was not fully predictive of the behavior across all of the solution conditions investigated. This highlights that both the level of modeling and lack of inclusion of glycans may limit existing models in making quantitatively accurate predictions of self-interactions.

A novel approach towards modeling proteins in aqueous solutions by applying perturbed-chain statistical associating fluid theory (PC-SAFT) is proposed in this work. Lysozyme and bovine serum albumin (BSA) were chosen as model proteins due to a vast database available in literature. However, the huge majority of these literature data had been measured at certain ionic strengths, which is disadvantageous in order to derive pure-component parameters for proteins. Thus, in a first step within this work osmotic coefficients of dialyzed lysozyme and of dialyzed BSA in pure water were measured at 298.15 K. The data were very different for dialyzed and non-dialyzed solutions and further showed a strong dependence on pH and ionic strength. In a second step, the pure-component parameters of lysozyme and BSA were adjusted to the measured osmotic coefficients and to solution densities of dialyzed lysozyme or dialyzed BSA. PC-SAFT explicitly takes into account the complex association behavior between protein and water as well as among the proteins. Therefore, the number of protein association sites of one protein was determined from the sum of association sites of the single amino-acid constituents of a protein available from previous work (Ind. Eng. Chem. Res 50 (2011) 141–151). Similarly, the two PC-SAFT parameters “segment number” and “segment diameter” of a protein were summed or averaged from the single amino-acid constituents. This approach allowed modeling densities and osmotic coefficients of protein solutions with reasonable accuracy compared to experimental data. [ABSTRACT FROM AUTHOR]

The development of a precipitation or crystallization step requires knowing the solubility of the target protein and its crystallization behavior in aqueous solutions at different pH, temperatures and in the presence of precipitating agents, especially salts. Within this work, a solubility model for proteins based on the second osmotic virial coefficient B 22 is developed. For this, a relation between protein solubility and B 22 was combined with the extended DLVO model. This solubility model was then used to model and also predict the protein solubility of lysozyme and monoclonal antibody for different salts, salt concentrations, and pH. The modeled as well predicted B 22 and protein solubility data of lysozyme in the presence of sodium chloride and sodium p-toluenesulfonate and of a monoclonal antibody in the presence of ammonium sulfate at different pH shows good agreement with experimental data. [ABSTRACT FROM AUTHOR]

Abstract: Soluble microbial products (SMP) are organic compounds excreted by microorganisms in their metabolism and decay and the main constituents in effluent from biological wastewater treatment systems. They also have an important contribution to the dissolved organic matters in natural aqueous systems. So far the interactions between SMP colloids have not been well explored. In this work, the interactions between SMP colloids in water and salt solutions were studied by using a combination of static and dynamic light scattering, Fourier transform infrared spectra, Zeta potential and acid-base titration techniques. The second osmotic virial coefficient had a larger value in a 750-mM salt solution than that in a 50-mM solution, indicating that repulsion between SMP colloids increased with an increase in salt concentration, which is contrary with the classic Derjaguin, Landau, Verwey, and Overbeek (DLVO) theory. Such a repulsion was attributed to water structuring and enhanced by the accumulation of hydrophilic counter ions around SMP colloids and the formed hydration force. The repulsion and hydration effect led to the dispersing and deeper draining structure, accompanied by a decreased hydrodynamic radius and increased diffusion coefficient. This hydration force was related to so-called ion specific effect, and electrolyte sodium chloride had a more substantial effect on hydration force than KCl, CsCl, NaBr and NaI. Our results provide an experimental approach to explore the SMP structures, inter-colloid interactions and confirm the non-DLVO forces. [Copyright &y& Elsevier]

Abstract: In this study, the nature of interactions between monoclonal antibodies and polyols was studied using static light scattering. Solutions of mAb-U and mAb-P (4–12mg/mL) were analyzed using static light scattering in buffer, 10% w/v trehalose and ethylene glycol solutions at pH 5.0, 7.0 and 9.0. Mechanical stress studies were conducted by shaking the mAb-U solutions (5mg/mL, pH 5.0, 7.0 and 9.0) and mAb-P solutions (5mg/mL, pH 7.0) at 200rpm for 5 days at 25°C. Addition of trehalose and ethylene glycol resulted in a decrease in the attractive interactions between mAb-U molecules at pH 7.0 and 9.0, and at pH 9.0 between mAb-P molecules. At a higher ionic strength (300mM, pH 5.0) trehalose and ethylene glycol decreased attractive interactions for both mAbs. Mechanical stress studies showed higher aggregation of mAb-U in trehalose solutions than ethylene glycol and buffer solutions at pH 7.0 and 9.0. A converse trend was seen for mAb-P at pH 7.0. This study showed that polyols, conformational stabilizers or destabilizers, decrease attractive interactions between protein molecules. The decrease is a result of masking of the hydrophobic sites on a protein as polyols can have favorable hydrophobic interactions with the surface exposed hydrophobic groups. [Copyright &y& Elsevier]

Static light scattering (SLS) was used to characterize five monoclonal antibodies (MAbs) as a function of total ionic strength (TIS) at pH values between 5.5 and 7.0. Second osmotic virial coefficient ( B 22 ) values were determined experimentally for each MAb as a function of TIS using low protein concentration SLS data. Coarse-grained molecular simulations were performed to predict the B 22 values for each MAb at a given pH and TIS. To include the effect of charge fluctuations of titratable residues in the B 22 calculations, a statistical approach was introduced in the Monte Carlo algorithm based on the protonation probability based on a given pH value and the Henderson-Hasselbalch equation. The charged residues were allowed to fluctuate individually, based on the sampled microstates and the influence of electrostatic interactions on net protein-protein interactions during the simulations. Compared to static charge simulations, the new approach provided improved results compared to experimental B 22 values at pH conditions near the p K a of titratable residues.

Abstract: A general thermodynamic relation was derived to correlate protein solubility to retention in hydrophobic interaction chromatography (HIC). This relation is built on a thermodynamic formulation presented previously by Melander, Horváth and co-workers in the context of the solvophobic theory, but the final result is independent of this model framework. The relation reflects an increase in protein retention in HIC under conditions that promote precipitation or crystallization, consistent with early descriptions of HIC. To examine the contribution of protein solubility to retention in HIC, isocratic elution experiments were performed with four different commercially available agarose media and four model proteins (ribonuclease A (RNA), lysozyme (LYS), myoglobin (MYO), and ovalbumin (OVA)). A wide variety of retention trends were observed as a function of protein, adsorbent type, salt type and concentration, and pH. In general, however, the results show that solubility, or its surrogate, the second osmotic virial coefficient, which reflects solution thermodynamic properties, correlates well with HIC retention in many cases; this includes correctly predicting reverse Hofmeister effects, which cannot be explained by retention models based on the solvophobic theory and preferential interaction theory. However, solution properties could not explain retention behavior under some conditions. In those cases, effects such as protein–surface interactions or conformational change could be important determinants of protein adsorption. [Copyright &y& Elsevier]

Protein purification is often performed using cost-intensive chromatographic steps. To discover economic alternatives (e.g., crystallization), knowledge on protein solubility as a function of temperature, pH, and additives in solution as well as their concentration is required. State-of-the-art models for predicting protein solubility almost exclusively consider aqueous salt systems, whereas "salting-in" and "salting-out" effects induced by the presence of an additional polymer are not considered. Thus, we developed the sol-mxDLVO model. Using this newly developed model, protein solubility in the presence of one salt and one polymer, especially the non-monotonic course of protein solubility, could be predicted. Systems considered included salts (NaCl, Na-p-Ts, (NH(4))(2) SO(4)) and the polymer polyethylene glycol (MW: 2000 g/mol, 12000 g/mol) and proteins lysozyme from chicken egg white (pH 4 to 5.5) and D-xylose ketol-isomerase (pH 7) at 298.15 K. The results show that by using the sol-mxDLVO model, protein solubility in polymer-salt solutions can be modeled in good agreement with the experimental data for both proteins considered. The sol-mxDLVO model can describe the non-monotonic course of protein solubility as a function of polymer concentration and salt concentration, previously not covered by state-of-the-art models., (Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)