Collision Induced Unfolding Predicts the Aggregation of Glycoengineered Monoclonal Antibodies

Monoclonal antibody (mAb) therapeutics exhibit substantial structural heterogeneity, requiring analytical methods capable of rapidly assessing critical quality attributes (CQAs) that influence stability and developability. Non-native aggregation is a key CQA, given its propensity to decrease mAb efficacy and increase immunogenicity. However, current analytical tools commonly used to screen mAbs during drug development provide limited structural insight into aggregation prone monomeric structures. Orthogonal tools such as ion mobility-mass spectrometry (IM-MS), collision-induced unfolding (CIU), and IM-selected CIU (IM-CIU) enable rapid gas-phase structural characterization of proteins, offering the ability to enhance the resolution of complex structural mixtures, bridging the gap left by conventional aggregation analyses. In this study, we establish CIU as a prompt predictor of mAb aggregation propensity. Analysis of IgG1 CIU fingerprints revealed a high-energy bimodal structural population, quantified here as the ‘A/B ratio’, that correlates with pH-induced aggregation observed in our forced degradation studies. IM-CIU and CIU-electron capture dissociation (ECD) further characterized these structural populations, allowing us to localize the A/B ratio diagnostically to the hinge region of the mAb. We conclude by demonstrating that A/B ratio data, collected for glycoengineered mono-disperse mAb glycoforms can be used to test and predict the ability of specific glycans to protect mAbs from aggregation. Together, these results establish CIU-derived structural metrics as rapid predictors of mAb aggregation propensity, enabling higher-throughput structural assessment of biotherapeutic stability and glycoform-dependent effects.