Phosphorylation is a protein posttranslational modification. It is responsible of the activation/inactivation of disease-related\npathways, thanks to its role of ââ?¬Å?molecular switch.ââ?¬Â The study of phosphorylated proteins becomes a key point for the proteomic\nanalyses focused on the identification of diagnostic/therapeutic targets. Liquid chromatography coupled to tandem mass\nspectrometry (LC-MS/MS) is themost widely used analytical approach. Although unmodified peptides are automatically identified\nby consolidated algorithms, phosphopeptides still require automated tools to avoid time-consuming manual interpretation. To\nimprove phosphopeptide identification efficiency, a novel procedure was developed and implemented in a Perl/C tool called\nPhosphoHunter, here proposed and evaluated. It includes a preliminary heuristic step for filtering out the MS/MS spectra\nproduced by nonphosphorylated peptides before sequence identification. Amethod to assess the statistical significance of identified\nphosphopeptides was also formulated. PhosphoHunter performance was tested on a dataset of 1500 MS/MS spectra and it was\ncompared with two other tools:Mascot and Inspect. Comparisons demonstrated that a strong point of PhosphoHunter is sensitivity,\nsuggesting that it is able to identify real phosphopeptides with superior performance. Performance indexes depend on a single\nparameter (intensity threshold) that users can tune according to the study aim. All the three tools localized >90% of phosphosites
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