Computational Design To Reduce Conformational Flexibility and Aggregation Rates of an Antibody Fab Fragment

Abstract

Computationally guided semirational design has significant potential for improving the aggregation kinetics of protein biopharmaceuticals. While improvement in the global conformational stability can stabilize proteins to aggregation under some conditions, previous studies suggest that such an approach is limited, because thermal transition temperatures ( T) and the fraction of protein unfolded ( f) tend to only correlate with aggregation kinetics where the protein is incubated at temperatures approaching the T. This is because under these conditions, aggregation from globally unfolded protein becomes dominant. However, under native conditions, the aggregation kinetics are presumed to be dependent on local structural fluctuations or partial unfolding of the native state, which reveal regions of high propensity to form protein-protein interactions that lead to aggregation. In this work, we have targeted the design of stabilizing mutations to regions of the A33 Fab surface structure, which were predicted to be more flexible. This Fab already has high global stability, and global unfolding is not the main cause of aggregation under most conditions. Therefore, the aim was to reduce the conformational flexibility and entropy of the native protein at various locations and thus identify which of those regions has the greatest influence on the aggregation kinetics. Highly dynamic regions of structure were identified through both molecular dynamics simulation and B-factor analysis of related X-ray crystal structures. The most flexible residues were mutated into more stable variants, as predicted by Rosetta, which evaluates the ΔΔ G for each potential point mutation. Additional destabilizing variants were prepared as controls to evaluate the prediction accuracy and also to assess the general influence of conformational stability on aggregation kinetics. The thermal conformational stability, and aggregation rates of 18 variants at 65 °C, were each examined at pH 4, 200 mM ionic strength, under which conditions the initial wild-type protein was <5% unfolded. Variants with decreased T values led to more rapid aggregation due to an increase in the fraction of protein unfolded under the conditions studied. As expected, no significant improvements were observed in the global conformational stability as measured by T. However, 6 of the 12 stable variants led to an increase in the cooperativity of unfolding, consistent with lower conformational flexibility and entropy in the native ensemble. Three of these had 5-11% lower aggregation rates, and their structural clustering indicated that the local dynamics of the C-terminus of the heavy chain had a role in influencing the aggregation rate.

Engineering Stability, Viscosity, and Immunogenicity of Antibodies by Computational Design

“…Zhang et al 124 performed a computational design calculation to explore relationships between conformational and colloidal stabilities of the Fab region of an antibody, the T m of which was 71.8 C, based on measurements made with the UNit instrument (Unchained Laboratories, UK). In their strategy, potentially flexible regions were first identified based on MD simulations of a homology model of the antibody and B-factors derived from crystal structures of the homologous antibodies (53%-90% sequence identities).…”

Models for Antibody Behavior in Hydrophobic Interaction Chromatography and in Self-Association

“…Antibody bivalency would then facilitate formation of HMWS. Partial unfolding of proteins is generally considered as a risk factor for formation of oligomers via non-specific interactions, including in antibody solutions44 . This is not to say that the CDRs are predominantly unfolded, rather that partial unfolding in a sub-population would lead to self-association.The second feature (in addition to CDRs length) used in the linear fit ofFigure 2bis the maximum surface (non-interfacial) NPP ratio of a Fab.…”

Insights into the stability of a therapeutic antibody Fab fragment by molecular dynamics and its stabilization by computational design

“…The C226S heavy-chain variant was used to avoid the formation of linked Fab dimers. We used the Rosetta method “minirosetta”, as detailed in previous works [48].…”

“…Next, the “BuildModel” command was used to introduce the point mutations, optimize the structure of the new protein variant, and calculate the stability change upon mutation. The Rosetta “ddg_monomer” method was used, where an example of mutation and option files, listing the parameters of the executable, can be seen in previous work [48]. Jobs were submitted to the UCL Legion High-Performance Computing Facility.…”