Prediction of Proteases Involved in Peptide Generation.
Clinical proteomics has led to the identification of a substantial number of disease-associated peptides and protein fragments in several conditions such as cancer, kidney, or cardiovascular diseases. In silico prediction tools that can facilitate linking of identified peptide biomarkers to predicted protease activity might therefore significantly contribute to the understanding of pathophysiological mechanisms of these diseases. Proteasix is an open-source, peptide-centric tool that can be used to predict in silico the proteases involved in naturally occurring peptide generation. From an input peptide list, Proteasix allows for automatic cleavage site reconstruction and protease associations.
School of Computer Science, University of Manchester, Oxford Road, Manchester, UK.
Mercedes Arguello
MA
Casteleiro
School of Computer Science, University of Manchester, Oxford Road, Manchester, UK.
Robert
R
Stevens
Institute of Cardiovascular and Metabolic Disease, INSERM U1048, Toulouse, France. julie.klein@inserm.fr.|Université Toulouse III Paul-Sabatier, Toulouse, France. julie.klein@inserm.fr.
Julie
J
Klein
D015415:Biomarkers; D020134:Catalytic Domain; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D010447:Peptide Hydrolases / Q000737:chemistry / Q000378:metabolism*; D010455:Peptides / Q000737:chemistry / Q000378:metabolism; D059748:Proteolysis; D020543:Proteome; D040901:Proteomics / Q000379:methods*; D013045:Species Specificity; D064878:Web Browser
D015415:Biomarkers; D010455:Peptides; D020543:Proteome; D010447:Peptide Hydrolases
Biomarker; Cleavage site; Database; Open-source; Peptide; Protease