The Mascot search algorithm is one of the most commonly used tools for protein identification. Tandem mass spectrometry data searched against a protein sequence database is utilized for identifying peptides and proteins, each reported with a score. Higher Mascot scores are associated with lower chances of random hits. The process of peak selection performed by the search engine prior to the search is a critical aspect of the process. Here, we show that Mascot divides the MS/MS spectrum into fixed m/z regions for peak selection, starting at the lowest m/z value of the peak list. Therefore, modifying the m/z range of the peak lists by insertion of a dummy peak with low m/z value changes the ensemble of peaks used for searching. As a consequence, Mascot peptide scores and search results are altered significantly and a different subset of the peptides present in the sample is identified after processing. We further show that the effect can be exploited and additional proteins and peptides can be identified by repeating the search with a combined set of differently processed files, even when applying identical false-positive rates.