Peptide metabolism: High resolution Mass Spectrometry tool to investigate Peptide structure and amine bond metabolic susceptibility

American Peptide Symposium, Whistler (Canada)… 17 June 2017 



Several in-silico approaches have been developed such as PeptideCutter to predict peptide cleavage sites for different proteases. Moreover, several databases exist where this information is collected and stored such as MEROPS. Despite these new methodologies there are still some limitations in their usage: inability to handle unnatural amino acids and cyclic peptides. The aim of this work is to develop a new methodology to analyze the mass spectrometry driven experimental data to find those metabolites, then determine their structures, database all the results in a chemistry aware manner and finally to compute the peptide bond susceptibility by using a frequency analysis of the metabolic liability.

This approach uses ultra-performance liquid chromatography with high resolution mass spectrometry to obtain the analytical data from incubations of peptides with different enzyme matrices. Metabolite identification was performed on 13 commercial peptide compounds and 4 positive substrates for the four selected proteases (serine and aspartic). The peptides were incubated for three hours with five time points being taken during the experiment. The compounds were diverse with respect to linear and cyclic structure, containing natural and unnatural amino acids and ranged in molecular weight.

The analysis of this data set resulted in 45 metabolites that were annotated in the database. The frequency analysis revealed 26 site of cleavage and the Trp-Ser being the most frequently cleaved bond for all cases. Selectivity was identified for pancreatic elastase and trypsin/chymotrypsin because the Ser-Tyr and Leu-Ser were revealed as a most frequently cleaved bond, respectively. These results agreed with previous studies. 

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