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• W4313554484 abstract "The ability to identify peptides with single-molecule sensitivity would lead to next-generation proteomics methods for basic research and clinical applications. Existing single-molecule peptide sequencing methods can read some amino acid sequences, but they are limited in their ability to distinguish between similar amino acids or post-translational modifications. Here, we demonstrate that the fluorescence intermittency of a peptide labeled with a spontaneously blinking fluorophore contains information about the structure of the peptide. Using a deep learning algorithm, this single-molecule blinking pattern can be used to identify the peptide. This method can distinguish between peptides with different sequences, peptides with the same sequence but different phosphorylation patterns, and even peptides that differ only by the presence of epimerized residues. This study builds the foundation for a targeted proteomics method with single-molecule sensitivity." @default.
• W4313554484 created "2023-01-06" @default.
• W4313554484 creator A5022771045 @default.
• W4313554484 creator A5023547067 @default.
• W4313554484 date "2023-01-05" @default.
• W4313554484 modified "2023-10-01" @default.
• W4313554484 title "Single-Molecule Peptide Identification Using Fluorescence Blinking Fingerprints" @default.
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• W4313554484 doi "https://doi.org/10.1021/jacs.2c12561" @default.
• W4313554484 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36603184" @default.
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