An Expanded Conformation of an Antibody Fab Region by X-Ray Scattering, Molecular Dynamics, and smFRET Identifies an Aggregation Mechanism.

Protein aggregation is the underlying cause of many diseases, and also limits the usefulness of many natural and engineered proteins in biotechnology. Better mechanistic understanding and characterization of aggregation-prone states is needed to guide protein engineering, formulation, and drug-targeting strategies that prevent aggregation. While several final aggregated states-notably amyloids-have been characterized structurally, very little is known about the native structural conformers that initiate aggregation. We used a novel combination of small-angle x-ray scattering (SAXS), atomistic molecular dynamic simulations, single-molecule Förster resonance energy transfer, and aggregation-prone region predictions, to characterize structural changes in a native humanized Fab A33 antibody fragment, that correlated with the experimental aggregation kinetics. SAXS revealed increases in the native state radius of gyration, Rg, of 2.2% to 4.1%, at pH 5.5 and below, concomitant with accelerated aggregation. In a cutting-edge approach, we fitted the SAXS data to full MD simulations from the same conditions and located the conformational changes in the native state to the constant domain of the light chain (CL). This CL displacement was independently confirmed using single-molecule Förster resonance energy transfer measurements with two dual-labeled Fabs. These conformational changes were also found to increase the solvent exposure of a predicted APR, suggesting a likely mechanism through which they promote aggregation. Our findings provide a means by which aggregation-prone conformational states can be readily determined experimentally, and thus potentially used to guide protein engineering, or ligand binding strategies, with the aim of stabilizing the protein against aggregation.

An ultra scale-down approach identifies host cell protein differences across a panel of mAb producing CHO cell line variants.

During the manufacture of biopharmaceutical products, the final product must lie within strict pre-set specifications, for example the host cell protein (HCP) content. A number of specific HCPs have been identified in particular products and the interactions between product/HCPs have also been recently investigated; however, a comparison of the HCP dynamics between related cell lines and their response to early downstream processing to aid process development and cell line selection has not been published. We have utilised a proteomic approach coupled with an ultra scale-down study to determine the HCP profile dynamics, at harvest and during early downstream processing, across a panel of recombinant GS-CHOK1SV antibody producing cell lines. The results reveal that cell culture viability upon harvest has the greatest impact upon shear sensitivity and HCP concentration. Whilst the general HCP population/profile was broadly similar across the cell lines, the actual amounts of some specific HCPs in the supernatant differed and a number of cell line specific differences in the response to early downstream processing were observed. We anticipate that such knowledge can now be applied to cell line selection and downstream processing development to target reduction/removal of general and specific problematic HCPs before and during downstream processing.

Mapping the Aggregation Kinetics of a Therapeutic Antibody Fragment.

The analytical characterization of biopharmaceuticals is a fundamental step in the early stages of development and prediction of their behavior in bioprocesses. Protein aggregation in particular is a common issue as it affects all stages of product development. In the present work, we investigate the stability and the aggregation kinetics of A33Fab, a therapeutically relevant humanized antibody fragment at a wide range of pH, ionic strength, and temperature. We show that the propensity of A33Fab to aggregate under thermally accelerated conditions is pH and ionic-strength dependent with a stronger destabilizing effect of ionic strength at low pH. In the absence of added salts, A33Fab molecules appear to be protected from aggregation due to electrostatic colloidal repulsion at low pH. Analysis by transmission electron microscopy identified significantly different aggregate species formed at low and high pH. The correlations between apparent midpoints of thermal transitions (Tm,app values), or unfolded mole fractions, and aggregation rates are reported here to be significant only at the elevated incubation temperature of 65 °C, where aggregation from the unfolded state predominates. At all other conditions, particularly at 4-45 °C, aggregation of A33 Fab was predominantly from a native-like state, and the kinetics obeyed Arrhenius behavior. Despite this, the rank order of aggregation rates observed at 45 °C, 23 and 4 °C still did not correlate well to each other, indicating that forced degradation at elevated temperatures was not a good screen for predicting behavior at low temperature.

Thermodynamic parameters for salt-induced reversible protein precipitation from automated microscale experiments.

Reversible precipitation can be used as an efficient purification tool for proteins. In addition, identifying conditions under which precipitation or aggregation occurs is of key importance in the bioprocessing and pharmaceutical industry, as this can aid in better formulations and hinder aggregation in chromatography. We have evaluated the precipitation of proteins as determined by light scattering in microplates as a tool for the high-throughput determination of thermodynamic parameters for protein precipitation, with the potential for screening of formulation additives and relevant bioprocess conditions such as pH. This provides a useful complementary technique to existing microplate-based protein thermostability measurements. Using hen egg-white lysozyme and alcohol dehydrogenase as model proteins we have determined the extent of reversible precipitation as a function of ammonium sulfate and sodium chloride concentrations, and also demonstrated global fitting of the data to generate a model where the fraction precipitated can be predicted for any given condition. The global fit provided thermodynamic parameters, including the free energy for protein precipitation, and also allowed an approximate determination of the average size of the structural nucleus that contributes to the free energy of precipitation for each protein. The rapid collection of thermodynamic parameters for protein precipitation, in parallel with protein thermostability measurements, will provide a powerful platform for protein formulation, and also lead to datasets useful for testing theoretical predictions of reversible precipitation based on the molecular modeling of specific protein structure interactions.