EnzymePredictor: A Tool for Predicting and Visualizing Enzymatic Cleavages of Digested Proteins

• Published in: Journal of proteome research Vol. 11; no. 12; pp. 6056 - 6065
• Main Authors: Vijayakumar, Vaishnavi, Guerrero, Andrés N, Davey, Norman, Lebrilla, Carlito B, Shields, Denis C, Khaldi, Nora
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 07.12.2012
• Subjects: Amino Acid Sequence; Catalytic Domain; Chymotrypsin - chemistry; Databases, Protein; Enzyme Assays - methods; Enzymes - chemistry; Humans; Mass Spectrometry; Milk, Human - chemistry; Milk, Human - enzymology; Molecular Sequence Data; Odds Ratio; Peptide Mapping - methods; Peptides - chemistry; Protein Hydrolysates - chemistry; Proteolysis; Software; Substrate Specificity; Time Factors; Trypsin - chemistry; protein digestion; hydrolysate; enzyme cleavage; peptides; fermentation; mass spectrometry; mass spectrometry visualization
• ISSN: 1535-3893; 1535-3907
• DOI: 10.1021/pr300721f

Mass spectrometric analysis of peptides contained in enzymatically digested hydrolysates of proteins is increasingly being used to characterize potentially bioactive or otherwise interesting hydrolysates. However, when preparations containing mixtures of enzymes are used, from either biological or experimental sources, it is unclear which of these enzymes have been most important in hydrolyzing the sample. We have developed a tool to rapidly evaluate the evidence for which enzymes are most likely to have cleaved the sample. EnzymePredictor, a web-based software, has been developed to (i) identify the protein sources of fragments found in the hydrolysates and map them back on it, (ii) identify enzymes that could yield such cleavages, and (iii) generate a colored visualization of the hydrolysate, the source proteins, the fragments, and the predicted enzymes. It tabulates the enzymes ranked according to their cleavage counts. The provision of odds ratio and standard error in the table permits users to evaluate how distinctively particular enzymes may be favored over other enzymes as the most likely cleavers of the samples. Finally, the method displays the cleavage not only according to peptides, but also according to proteins, permitting evaluation of whether the cleavage pattern is general across all proteins, or specific to a subset. We illustrate the application of this method using milk hydrolysates, and show how it can rapidly identify the enzymes or enzyme combinations used in generating the peptides. The approach developed here will accelerate the identification of enzymes most likely to have been used in hydrolyzing a set of mass spectrometrically identified peptides derived from proteins. This has utility not only in understanding the results of mass spectrometry experiments, but also in choosing enzymes likely to yield similar cleavage patterns. EnzymePredictor can be found at http://bioware.ucd.ie/∼enzpred/Enzpred.php