Research Highlights

Post-Translational Modification Prediction

The PILOT_PTM algorithm is designed to search the universe of post-translational modifications and annotate a peptide sequence with the modifications that best explain the experimental data. The overall framework for PILOT_PTM consists initially of the identification of globally and locally significant peaks. The highest intensity filtered peaks are labeled as globally significant. Any other filtered peak is labeled as locally significant if the peak intensity is greater than all other peaks within a 5.0-Da mass window. A set of singly charged support peaks (red) is then isolated for a candidate ion peak (blue). Each peak labeled as globally or locally significant will be assigned a set of supporting peaks based on the filtered MS/MS. The output from an optimal solution of PILOT_PTM (the blue peaks on the left) represents all MS/MS peaks that are activated for the optimal solution. The sets of blue peaks on the right represent all candidate ion peak sets that will activate the optimal combination of MS/MS peaks. Finally, a cross-correlation is performed to isolate the best set of modifications for the template sequence.

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