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Integrated Experimental and Molecular Modeling Techniques to Investigate the Buffer Effects on Glucagon Stability

Journal 2026 · IF 4.1 · 发表于 2026 年 3 月 6 日
作者: Xu Zi-Ting,Li Bogang,Deng Jiayin,Lv Jia-Yi,Ouyang Defang,Fang Wei-Jie
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摘要

Purposes Peptide drugs are a vital category of biologics. However, unlike the well-studied effects of buffers on small-molecule or macromolecule drugs, the understanding of selecting appropriate buffers for peptide formulations and their specific impacts remains insufficient. This study aimed to systematically evaluate how different buffers affect the stability of the model peptide, glucagon, and to investigate the underlying mechanisms at the molecular level. Methods This work employed glucagon as a model peptide and integrated experimental techniques with computational approaches. Experimental techniques included reverse-phase high-performance liquid chromatography (RP-HPLC), Thioflavin T fluorescence assays, and circular dichroism (CD). Molecular dynamics (MD) simulations were further conducted, utilizing models with different buffer systems and varying peptide counts, to examine the interaction mechanisms between buffers and glucagon from multiple perspectives. Results Compared with other buffers, citrate exerted a unique and significant impact on glucagon stability. RP-HPLC demonstrated its destabilizing effect on the structure, while CD and MD simulations confirmed its role in preserving glucagon’s α-helical structure, attributed to its highest binding energy. However, this strong binding reduced the ζ-potential, compromised colloidal stability, and ultimately promoted aggregation/precipitation. MD simulations further showed that citrate anions formed a denser solvation shell around glucagon, driving oligomerization and aggregation. Conclusions This work uncovers the dual role of citrate buffer on glucagon stability: maintaining local secondary structure while disrupting overall colloidal stability. It provides molecular insights into peptide-excipient interactions and offers valuable guidance for optimizing formulations for other peptide drugs. Graphical

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