Decoding Oxidation State Landscapes Within Individual Native Peptides by Nanopore
ABSTRACT Protein oxidation generates diverse chemical states that regulate cellular signaling yet progressively accumulate as molecular damage during aging. However, characterizing oxidation‐state heterogeneity of individual proteins or peptides remains challenging, as conventional ensemble methods average over coexisting species. Here, we report a nanopore strategy based on a confined hydrogen‐bond network to decode oxidation states within individual native peptides. By engineering a constricted recognition region enriched with hydrogen‐bond interactions, the changes induced by diverse oxidation states were specifically recognized. This enables discrimination of closely related oxidative modifications, including proline hydroxylation, methionine oxidation, and tryptophan oxidation, even at ultra‐low abundance. We show that the reversible and regulated oxidation state could be clearly distinguished from irreversible and damaged oxidation with the same mass without separation or purification. Furthermore, we quantified heterogeneous oxidation distributions generated under controlled oxidative conditions. This approach provides a molecular‐level strategy for characterizing oxidation‐state heterogeneity in individual peptides, with potential applications in studying oxidative modifications associated with aging and disease in future biological investigations.
Authors
- Jun‐Ge Li
- Meng‐Yin Li (ORCID: https://orcid.org/0000-0002-0347-4194)
- Yi‐Tao Long (ORCID: https://orcid.org/0000-0003-2571-7457)
- Jie Jiang (ORCID: https://orcid.org/0000-0002-4894-5973)
- Xia Zhou
- Yan Gao
Institutions
- University of Science and Technology of China (CN)
- Nanjing University of Science and Technology (CN)
- Nanjing University (CN)
Publication Details
- Journal
- Angewandte Chemie
- Published
- 2026-09-08
- DOI
- https://doi.org/10.1002/ange.9376050
- Primary Topic
- Nanopore and Nanochannel Transport Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00