From osmotic second virial coefficient (B22 ) to phase behavior of a monoclonal antibody.

Antibodies are complex macromolecules and their phase behavior as well as interactions within different solvents and precipitants are still not understood. To shed some light into the processes on a molecular dimension, the occurring self-interactions between antibody molecules were analyzed by means of the osmotic second virial coefficient (B22 ). The determined B22 follows qualitatively the phenomenological Hofmeister series describing the aggregation probability of antibodies for the various solvent compositions. However, a direct correlation between crystallization probability and B22 in form of a crystallization slot does not seem to be feasible for antibodies since the phase behavior is strongly dependent on their anisotropy. Kinetic parameters have to be taken into account due to the molecular size and complexity of the molecules. This is confirmed by a comparison of experimental data with a theoretical phase diagram. On the other hand the solubility is thermodynamically driven and therefore the B22 could be used to establish a universal solubility line for the monoclonal antibody mAb04c and different solvent compositions by using thermodynamic models.

Influence of macromolecular precipitants on phase behavior of monoclonal antibodies.

For the successful application of protein crystallization as a downstream step, a profound knowledge of protein phase behavior in solutions is needed. Therefore, a systematic screening was conducted to analyze the influence of macromolecular precipitants in the form of polyethylene glycol (PEG). First, the influence of molecular weight and concentration of PEG at different pH-values were investigated and analyzed in three-dimensional (3-D) phase diagrams to find appropriate conditions in terms of a fast kinetic and crystal size for downstream processing. In comparison to the use of salts as precipitant, PEG was more suitable to obtain compact 3-D crystals over a broad range of conditions, whereby the molecular weight of PEG is, besides the pH-value, the most important parameter. Second, osmotic second virial coefficients as parameters for protein interactions are experimentally determined with static light scattering to gain a deep insight view in the phase behavior on a molecular basis. The PEG-protein solutions were analyzed as a pseudo-one-compartment system. As the precipitant is also a macromolecule, the new approach of analyzing cross-interactions between the protein and the macromolecule PEG in form of the osmotic second cross-virial coefficient (B23 ) was applied. Both parameters help to understand the protein phase behavior. However, a predictive description of protein phase behavior for systems consisting of monoclonal antibodies and PEG as precipitant is not possible, as kinetic phenomena and concentration dependencies were not taken into account.

Meeting report VLPNPV: Session 10: Virus-like particle and nano-particle vaccines.

Session 10 of the Virus-like Particle and Nano-Particle Vaccines meeting 2014 focused on new methods in vaccine technology to accelerate process development, manufacturing and quality control. The session presented new ways of quantifying and characterizing particle samples. In addition platform approaches for production and purification of virus-like particle (VLP) vaccines were highlighted.

Self-interaction chromatography in pre-packed columns: a critical evaluation of self-interaction chromatography methodology to determine the second virial coefficient.

The characterization of protein-protein interactions is commonly conducted via self-interaction chromatography to describe magnitude and direction of the interactions with the resulting osmotic second virial coefficient (B22). However, the method is invasive and protein immobilization on the adsorber surface can influence the results obtained. In order to replace batch immobilization procedures followed by a column packing, direct on-column preparation was optimized in terms of protein immobilization under a continuous flow. Surface load was measured applying a novel method based on partial least squares analysis of spectral scans to reduce analytical error when determining the amount of immobilized protein. Subsequently influencing parameters such as the effects of absolute surface load, injected protein concentration and distribution of protein orientation were analyzed and system performance evaluated. The results disprove the consistency of the SIC method regarding the non-random orientation of proteins on adsorber particles. Thus the determined B22-values differ quantitatively from those determined with static light scattering. Furthermore, variations in immobilization conditions influence the results obtained. These results make clear that SIC does not fulfill the theoretical framework of B22-analysis. It is rather a qualitative measure of protein-protein interactions in the respective system used for experimentation.

3D structure-based protein retention prediction for ion-exchange chromatography.

The interest in understanding fundamental mechanisms underlying chromatography drastically increased over the past decades resulting in a whole variety of mostly semi-empirical models describing protein retention. Experimental data about the molecular adsorption mechanisms of lysozyme on different chromatographic ion-exchange materials were used to develop a mechanistical model for the adsorption of lysozyme onto a SP Sepharose FF surface based on molecular dynamic simulations (temperature controlled NVT simulations) with the Amber software package using a force-field based approach with a continuum solvent model. The ligand spacing of the adsorbent surface was varied between 10 and 20A. With a 10A spacing it was possible to predict the elution order of lysozyme at different pH and to confirm in silico the pH-dependent orientation of lysozyme towards the surface that was reported earlier. The energies of adsorption at different pH values were correlated with isocratic and linear gradient elution experiments and this correlation was used to predict the retention volume of ribonuclease A in the same experimental setup only based on its 3D structure properties. The study presents a strong indication for the validity of the assumption, that the ligand density of the surface is one of the key parameters with regard to the selectivity of the adsorbent, suggesting that a high ligand density leads to a specific interaction with certain binding sites on the protein surface, while at low ligand densities the net charge of the protein is more important than the actual charge distribution.