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.