Juergen Hubbuch

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.

Determination of parameters for the steric mass action model—A comparison between two approaches

The application of mechanistic modeling for the optimization of chromatographic steps increased recently due to time efficiency of algorithms and rising calculation power. In the modeling of ion exchange chromatography steps, the sorption processes occurring on adsorbent particle surfaces can be simulated with the steric mass action (SMA) model introduced by Brooks and Cramer (1992) [14]. In this paper, two approaches for the determination of SMA parameters will be carried out and discussed concerning their specific experimental effort, quality of results, method differences, reasons for uncertainties and consequences for SMA parameter determination: Approach I: estimation of SMA parameters based on gradient and frontal experiments according to instructions in Brooks and Cramer (1992) [14] and Shukla et al. (1998) [16]. Approach II: application of an inverse method for parameter estimation, resulting in SMA parameters that induce a best fit of chromatographic data to a mechanistic model for column chromatography. These approaches for SMA parameter determination were carried out for three proteins (ribonuclease A, cytochrome c and lysozyme) at pH 5 and pH 7. The results were comparable and the order of parameter values and their relations to the chromatographic data similar. Nevertheless, differences in the complexity and effort of methods as well as the parameter values themselves were observed. The comparison of methods demonstrated that discrepancies depend mainly on model sensitivities and additional parameters influencing the calculations. However, the discrepancies do not affect predictivity; predictivity is high in both approaches. The approach based on an inverse method and the mechanistic model has the advantage that not only retention times but also complete elution profiles can be predicted. Thus, the inverse method based on a mechanistic model for column chromatography is the most comfortable way to establish highly predictive SMA parameters lending themselves for the optimization of chromatography steps and process control.

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.

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.

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.

Quantification of PEGylated proteases with varying degree of conjugation in mixtures: An analytical protocol combining protein precipitation and capillary gel electrophoresis.

PEGylation, i.e. the covalent attachment of chemically activated polyethylene glycol (PEG) to proteins, is a technique commonly used in biopharmaceutical industry to improve protein stability, pharmacokinetics and resistance to proteolytic degradation. Therefore, PEGylation represents a valuable strategy to reduce autocatalysis of biopharmaceutical relevant proteases during production, purification and storage. In case of non-specific random conjugation the existence of more than one accessible binding site results in conjugates which vary in position and number of attached PEG molecules. These conjugates may differ considerably in their physicochemical properties. Optimizing the reaction conditions with respect to the degree of PEGylation (number of linked PEG molecules) using high-throughput screening (HTS) technologies requires a fast and reliable analytical method which allows stopping the reaction at defined times. In this study an analytical protocol for PEGylated proteases is proposed combining preservation of sample composition by trichloroacetic acid (TCA) precipitation with high-throughput capillary gel electrophoresis (HT-CGE). The well-studied protein hen egg-white lysozyme served as a model system for validating the newly developed analytical protocol for 10kDa mPEG-aldehyde conjugates. PEGamer species were purified by chromatographic separation for calibrating the HT-CGE system. In a case study, the serine protease Savinase(®) which is highly sensitive to autocatalysis was randomly modified with 5kDa and 10kDa mPEG-aldehyde and analyzed. Using the presented TCA protocol baseline separation between PEGamer species was achieved allowing for the analysis of heterogeneous PEGamer mixtures while preventing protease autocatalysis.

Deconvolution of high‐throughput multicomponent isotherms using multivariate data analysis of protein spectra

Gaining a more profound understanding of biopharmaceutical downstream processes is a key demand of the Quality by Design (QbD) guidelines. One of the most dominant approaches to gain process understanding is the extensive use of experimental high‐throughput formats, such as batch chromatography on robotic liquid handling stations. Using these high‐throughput experimental formats, the generation of numerous samples poses an enormous problem to subsequent analytical techniques. Here, a high‐throughput case study for batch chromatographic multicomponent isotherms is presented. To debottleneck the subsequent analytics, a noninvasive technique using UV spectra and multivariate statistics was adapted to a batch chromatographic format. Using this approach, it was possible to integrate the entire analytical setup into the robotic workflow. As a case study, batch isotherms for sulfopropyl sepharose fast flow and the model proteins cytochrome c and lysozyme at various pH values and ionic strengths were recorded. A successful examination of the quality of the analytical procedure compared to classical single wavelength photometry was carried out. To address the growing demand for a more profound process understanding, the experimental data were fitted to the steric mass action isotherm, getting a more detailed insight into the competitive binding behavior at various pH values and ionic strengths.

Water on hydrophobic surfaces: Mechanistic modeling of hydrophobic interaction chromatography.

Mechanistic models are successfully used for protein purification process development as shown for ion-exchange column chromatography (IEX). Modeling and simulation of hydrophobic interaction chromatography (HIC) in the column mode has been seldom reported. As a combination of these two techniques is often encountered in biopharmaceutical purification steps, accurate modeling of protein adsorption in HIC is a core issue for applying holistic model-based process development, especially in the light of the Quality by Design (QbD) approach. In this work, a new mechanistic isotherm model for HIC is derived by consideration of an equilibrium between well-ordered water molecules and bulk-like ordered water molecules on the hydrophobic surfaces of protein and ligand. The models capability of describing column chromatography experiments is demonstrated with glucose oxidase, bovine serum albumin (BSA), and lysozyme on Capto™ Phenyl (high sub) as model system. After model calibration from chromatograms of bind-and-elute experiments, results were validated with batch isotherms and prediction of further gradient elution chromatograms.

Surface tension determination by means of liquid handling stations

The characterization of liquid surfaces with respect to surface tension is of major interest throughout a number of disciplines. In life science technologies and in pharmaceutical production in particular, the surface tension and drop size of liquids are predominating parameters throughout the production process, starting from foaming during fermentation processes, formulation by spray drying, or the drug application by aerosol inhalators. The profiling of surface tension can be further applied for physicochemical drug assessment with predictive power for the compounds pharmacology. In the present study, a high‐throughput approach for the determination of surface tension integrated into a fully automated liquid handling station was developed. The method is based on the accurate gravimetric determination of masses of drops generated at a liquid handler tip using a high‐precision balance. By means of repetitive sample‐conserving drop‐generating procedures, huge numbers of drops and thus statistical significance can be created from a minimal sample volume of a few 100 μL. The developed approach excels in instrumental simplicity, accuracy, precision, and minimal sample consumption. The fully automated setup was validated for a broad range of surface tensions starting from about 25 to 75 mN/m. Eight‐fold determinations of sample liquids exposed standard deviations of less than 0.5%, which demonstrates excellent precision. Further potential revisions of the stalagmometric approach for the determination of interfacial tension between two liquids are described in detail. The employment of liquid handling stations enables the integration of the developed method into the high‐throughput screening paradigm and thus adds high value to the laboratory work flow.