Cyclic peptides represent a middle ground between small and large-molecule drugs, and often possess the easier synthesis and delivery of small molecules yet the specificity of large molecules. Cyclic peptides pose some analytical challenges including non-ribosomal peptides (not in the genome), nonstandard amino acids, both L and D-amino acids, numerous post-translational modifications
(PTMs), and disulfide and other bridges.
Here we describe how to use Byonic to sequence cyclic peptides.
Create FASTA file
Cyclic peptides can undergo random ring opening at each amide bond yielding many linear peptides. In the FASTA file, you should input all shifted sequences in formation as follows.
Generally, cyclic peptides contain non-standard amino acids. Byonic/Byos can support non-natural amino acid sequence analysis. You can obtain the more information on the workflow settings containing non-natural amino acids here.
- Protein database options
The Add decoys box should be unchecked, as some true-positive PSMs will be filtered out because of the high complexity of cyclic peptides.
- Sample digestion
Leave Cleavage site(s) as empty for Top-Down searches:
Put a variable modification of -18.010565 (water loss) on the C-terminus enabling simultaneously search for in vitro cleavage and MS-cleavage of cyclic peptides.
Characterization of cyclic peptides by MS2 is significantly more challenging than elucidation of linear peptides. Cyclic peptides require cleavage of two backbone bonds to generate fragment ions, and the absence of intrinsic N-terminal and C-terminal positions complicates spectral interpretation. While
several data acquisition options including MSn methods and / or alternative activation methods like UVPD have demonstrated ability to analyze these peptides, the bottleneck of the workflow has been the spectral interpretation, requiring laborious manual analysis.
We have demonstrated that Byonic/Byos can search, identify and annotate cyclic peptides. We foresee the advantages of incorporating cyclic peptide search into proteome search engines, such as distinguishing MS-cleavage cyclic peptides from in vitro cleavage cyclic peptides, and searching for sequence variants, unknown modifications, and unnatural amino acids through wildcard search.