Unveiling antimicrobial peptide-generating human proteases using PROTEASIX.

Journal: Journal of proteomics
PMID:

Abstract

UNLABELLED: Extracting information from peptidomics data is a major current challenge, as endogenous peptides can result from the activity of multiple enzymes. Proteolytic enzymes can display overlapping or complementary specificity. The activity spectrum of human endogenous peptide-generating proteases is not fully known. Hence, the indirect study of proteolytic enzymes through the analysis of its substrates is largely hampered. Antimicrobial peptides (AMPs) represent a primordial set of immune defense molecules generated by proteolytic cleavage of precursor proteins. These peptides can be modulated by host and microorganismal stimuli, which both dictate proteolytic enzymes' expression and activity. Peptidomics is an attractive approach to identify peptides with a biological role and to assess proteolytic activity. However, bioinformatics tools to deal with peptidomics data are lacking. PROTEASIX is an excellent choice for the prediction of AMPs-generating proteases based on the reconstitution of a substrate's cleavage sites and the crossing of such information with known proteases' specificity retrieved by several publicly available databases. Therefore, the focus of the present tutorial is to explore the potential of PROTEASIX when gather information concerning proteases involved in the generation of human AMPs and to teach the user how to make the most out of peptidomics results using PROTEASIX.

Authors

  • Paulo Bastos
    Institute of Biomedicine - iBiMED, Department of Medical Sciences, University of Aveiro, Portugal; QOPNA, Mass Spectrometry Center, Department of Chemistry, University of Aveiro, Portugal. Electronic address: pauloandrediasbastos@ua.pt.
  • Fábio Trindade
    Institute of Biomedicine - iBiMED, Department of Medical Sciences, University of Aveiro, Portugal; Department of Physiology and Cardiothoracic Surgery, Faculty of Medicine, University of Porto, Porto, Portugal.
  • Rita Ferreira
    QOPNA, Mass Spectrometry Center, Department of Chemistry, University of Aveiro, Portugal.
  • Mercedes Arguello Casteleiro
    School of Computer Science, University of Manchester, Kilburn Building, Oxford Road, Manchester, UK.
  • Robert Stevens
    School of Computer Science, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom. Electronic address: robert.stevens@manchester.ac.uk.
  • Julie Klein
    Institut National de la Sante et de la Recherche Medicale (INSERM), U1048, Toulouse, 24105, France.
  • Rui Vitorino
    Institute of Biomedicine - iBiMED, Department of Medical Sciences, University of Aveiro, Portugal; Department of Physiology and Cardiothoracic Surgery, Faculty of Medicine, University of Porto, Porto, Portugal. Electronic address: rvitorino@ua.pt.