Аңдатпа
Modern biological research has become highly interdisciplinary, requiring mass spectrometry data generation to be combined with bioinformatics and data analysis skills to obtain meaningful results. However, many researchers who regularly conduct mass spectrometry experiments often lack practical experience in interpreting results and optimizing database searches. This practical article describes the use of the Mascot search engine for identifying peptides and proteins in shotgun proteomics. Using a local Mascot server (version 2.6.2), two datasets were analyzed: an in-house Escherichia coli tryptic lysate obtained on an Impact II QTOF mass spectrometer and a publicly available histone post-translational modifications dataset from the jPOST repository. The workflow includes optimizing search parameters, performing the search, interpreting results, and demonstrating the detection of post-translational modifications. The presented example of histones demonstrates the identification of known lysine modifications (including trimethylation) detected through search. This article serves as a practical guide for researchers wishing to improve their proteomic data analysis skills in Mascot and highlights the critical importance of selecting the right parameters to obtain accurate and reproducible results.