Modulating non-native aggregation and electrostatic protein-protein interactions with computationally designed single-point mutations.

Non-native protein aggregation is a ubiquitous challenge in the production, storage and administration of protein-based biotherapeutics. This study focuses on altering electrostatic protein-protein interactions as a strategy to modulate aggregation propensity in terms of temperature-dependent aggregation rates, using single-charge variants of human γ-D crystallin. Molecular models were combined to predict amino acid substitutions that would modulate protein-protein interactions with minimal effects on conformational stability. Experimental protein-protein interactions were quantified by the Kirkwood-Buff integrals (G22) from laser scattering, and G22 showed semi-quantitative agreement with model predictions. Experimental initial-rates for aggregation showed that increased (decreased) repulsive interactions led to significantly increased (decreased) aggregation resistance, even based solely on single-point mutations. However, in the case of a particular amino acid (E17), the aggregation mechanism was altered by substitution with R or K, and this greatly mitigated improvements in aggregation resistance. The results illustrate that predictions based on native protein-protein interactions can provide a useful design target for engineering aggregation resistance; however, this approach needs to be balanced with consideration of how mutations can impact aggregation mechanisms.

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