Nora Khaldi1, 2; Vaishnavi Vijayakumar1; Andreś Guerrero2; Norman Davey3; Carlito Lebrilla2; Denis Shields1
1University College Dublin, Dublin, IRELAND; 2University college Davis, Davis, USA; 3European Molecular Biology Laboratory, Heidelberg, Germany
NOVEL ASPECT: This tool will greatly advance the understanding of the mechanisms of action of enzymes, and the prediction of bioactive peptides.
For many years, MS has been widely employed for the identification and characterization of proteins and more recently peptides. The sheer volume of data generated by MS warrants the need for sophisticated data handling systems prediction, and visualization.In this work we focus on the peptides produced in a hydrolysate. We have constructed ‘EnzymePredictor’ a software that allows the visualization of the hydrolysate and the prediction of sets of enzymes that have been used or can be used to generate the current hydrolysate’s identified peptides. The software has a friendly visualization output that allows the user to simultaneously view the positional information of the peptides on their source protein, and the possible enzymes that have been used to produce them.

The software EnzymePredictor is coded in perl. To assess the software’s performance we experimentally generated a hydrolysate. We used human breast milk as the raw material, and performed three independent digestions. We chose to use human milk as opposed to a “clean” protein digestion because of its complex nature, which represents the reality of a food hydrolysate.  We carried out a digestion with trypsin; one with chymotrypsin; and a digestion using the combination of both trypsin and chymotrypsin. The latter digestion is to examine if the software is sensitive to the usage of a combination of enzymes. The resulting hydrolysates were then passed through mass-spectrometry and the MassHunter software (Agilent Technologies Inc.) to yield the list of peptides.
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 by the software permits users to evaluate how distinctively particular enzymes may be favoured 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 software successfully identified in each of the three cases the enzymes responsible for the cleaving of the human breast milk proteins.

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∼enzpred/Enzpred.php