13 Nov Software assisted analysis for peptide catabolism

Anna Escolà (1,2), Antoni Riera(1,2), Aurora Valeri (3), Ismael Zamora(4,5), Tatiana Radchenko(4,5)

1. Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain; 2. Department de Química Inorgánica i Orgánica, Universitat de Barcelona, Barcelona, Spain; 3. Molecular Horizon S.R.L, Perugia, Italy;4. Pompeu Fabra University, Barcelona Spain; 5. Lead Molecular Design, S.L, Sant Cugat del Vallés, Spain

 

The interest in using peptide molecules as therapeutic agents is due to their high selectivity and efficacy. However, most peptide-derived drugs cannot be administered orally because of their instability in the gastrointestinal tract. To achieve better ADME properties the following chemical modifications are typically applied: substitution of the common L-amino acids to D-amino acids, cyclization of the peptide and others. Somatostatin or Somatotropin release-inhibiting factor (SRIF14) is a natural hormone that is being used as gastric anti-secretory drug as well as to treat growth hormone secretion disorders and endocrine tumors. The substitution of phenylalanine, using non-natural aromatic amino acids to enhance the aromatic interactions, naturally present in the hormone between Phe6, Phe7 and Phe11 has been studied before.

We used a new approach implemented in Mass-MetaSite to process data-dependent acquisition (DDA) liquid chromatography high-resolution mass spectrometry (LC-HRMS) analytical data. This data was collected for a set of eight peptide drugs (somatostatin and seven synthetic analogues, containing non-standard amino acids) incubated with human serum. The samples obtained were used to perform metabolite identification, to reveal potential cleavage sites and to store the processed information in a searchable format within a database (WMB). During the metabolite identification study in total 17 metabolites were found resulting in 8 distinct cleavage sites. We compared the percent of remaining parent peptide with respect to the time for all investigated peptides to compute the half-life for each case. Moreover, we evaluated the influence of the chemical modifications on the half-life time of the investigated compounds comparing to the value obtained for somatostatin. All compounds from the dataset were hydrolyzed with the different velocity. More stable compounds were the compounds where following replacements were done both Phe7 to Msa7, Trp8 to D-Trp8 and/or both Cys3 and Cys14 to D-Cys.

We demonstrated that the developed approach can elucidate metabolite structure of cyclic peptides and those containing unnatural amino acids. The processed information obtained could be stored in a searchable format within a database leading to frequency analysis of the labile sites for the analyzed peptides. This new algorithm may be useful to optimize peptide drug properties with regards to cleavage sites, stability, metabolism and degradation products in drug discovery.