Mass Spectrometry-Based Structural Characterization and Reaction Kinetics Profiling of Stapled Peptides through Enzymatic Linearization

Peptide stapling stabilizes bioactive conformations and expands the chemical space of macrocyclic peptide therapeutics. However, competing stapling pathways often generate structurally heterogeneous products, complicating connectivity assignment and quantitative analysis of macrocyclization selectivity. Here, we develop a mass spectrometry (MS)-based analytical platform that enables structural elucidation of stapled peptides and mechanistic interrogation of their formation pathways. The method employs MS-grade proteases to achieve controlled enzymatic linearization of stapled macrocycles under mild conditions, converting rigid cyclic architectures into linear surrogates that are amenable to tandem MS sequencing while preserving staple-dependent connectivity information. When integrated with ion mobility spectrometry, the workflow enables separation and quantitative monitoring of regioisomeric stapled products, allowing direct assessment of site-selective macrocyclization kinetics. Extension of the approach through covalent labeling further demonstrates its ability to localize modification sites within constrained mono- and bicyclic stapled peptides. Together, this platform enables the systematic analysis of stapling connectivity, topology, reaction selectivity, and chemical modification patterns in rigid stapled peptide systems, offering a valuable analytical tool for the characterization and optimization of macrocyclic therapeutics.

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Publication Details

Journal
Analytical Chemistry
Published
2026-06-17
DOI
https://doi.org/10.1021/acs.analchem.6c01200
Primary Topic
Chemical Synthesis and Analysis
Type
article
Field-Weighted Citation Impact
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article

Mass Spectrometry-Based Structural Characterization and Reaction Kinetics Profiling of Stapled Peptides through Enzymatic Linearization

Ming Cheng, Youhong Hu, Zijian Gong, Xinrui Shi et al.
Analytical Chemistry
Chemical Synthesis and Analysis
article

Mass Spectrometry-Based Structural Characterization and Reaction Kinetics Profiling of Stapled Peptides through Enzymatic Linearization

Ming Cheng, Youhong Hu, Zijian Gong, Xinrui Shi, Sun Y, Wei Zheng
article en

Abstract

Peptide stapling stabilizes bioactive conformations and expands the chemical space of macrocyclic peptide therapeutics. However, competing stapling pathways often generate structurally heterogeneous products, complicating connectivity assignment and quantitative analysis of macrocyclization selectivity. Here, we develop a mass spectrometry (MS)-based analytical platform that enables structural elucidation of stapled peptides and mechanistic interrogation of their formation pathways. The method employs MS-grade proteases to achieve controlled enzymatic linearization of stapled macrocycles under mild conditions, converting rigid cyclic architectures into linear surrogates that are amenable to tandem MS sequencing while preserving staple-dependent connectivity information. When integrated with ion mobility spectrometry, the workflow enables separation and quantitative monitoring of regioisomeric stapled products, allowing direct assessment of site-selective macrocyclization kinetics. Extension of the approach through covalent labeling further demonstrates its ability to localize modification sites within constrained mono- and bicyclic stapled peptides. Together, this platform enables the systematic analysis of stapling connectivity, topology, reaction selectivity, and chemical modification patterns in rigid stapled peptide systems, offering a valuable analytical tool for the characterization and optimization of macrocyclic therapeutics.

Analytical Chemistry
Binzhou Medical University (CN), Shandong University of Aeronautics (CN), Chinese Academy of Sciences (CN), Second Hospital of Shandong University (CN), Shanghai Institute of Materia Medica (CN), Advanced Research Institute (US), Institute for Advanced Study (DE)
Openalex Percentile: Top 11%
Chemical Synthesis and Analysis
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