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Impact of Glycosylation on Protein–Protein Self-Interactions of Monoclonal Antibodies

化学 静电学 糖基化 单克隆抗体 离子强度 聚糖 位阻效应 糖蛋白 动态光散射 维里系数 化学物理 生物物理学 生物化学 抗体 纳米技术 材料科学 物理化学 有机化学 热力学 物理 生物 水溶液 免疫学 纳米颗粒
作者
Veerabhadraiah Palakollu,Lily Motabar,Christopher J. Roberts
出处
期刊:Molecular Pharmaceutics [American Chemical Society]
卷期号:21 (3): 1414-1423
标识
DOI:10.1021/acs.molpharmaceut.3c01069
摘要

Protein self-interactions measured via second osmotic virial coefficients (B22) and dynamic light scattering interaction parameter values (kD) are often used as metrics for assessing the favorability of protein candidates and different formulations during monoclonal antibody (MAb) product development. Model predictions of B22 or kD typically do not account for glycans, though glycosylation can potentially impact experimental MAb self-interactions. To the best of our knowledge, the impact of MAb glycosylation on the experimentally measured B22 and kD values has not yet been reported. B22 and kD values of two fully deglycosylated MAbs and their native (i.e., fully glycosylated) counterparts were measured by light scattering over a range of pH and ionic strength conditions. Significant differences between B22 and kD of the native and deglycosylated forms were observed at a range of low to high ionic strengths used to modulate the effect of electrostatic contributions. Differences were most pronounced at low ionic strength, indicating that electrostatic interactions are a contributing factor. Though B22 and kD values were statistically equivalent at high ionic strengths where electrostatics were fully screened, we observed protein-dependent qualitative differences, which indicate that steric interactions may also play a role in the observed B22 and kD differences. A domain-level coarse-grained molecular model accounting for charge differences was considered to potentially provide additional insight but was not fully predictive of the behavior across all of the solution conditions investigated. This highlights that both the level of modeling and lack of inclusion of glycans may limit existing models in making quantitatively accurate predictions of self-interactions.
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