Proteomic Database Search Engine for Two-Dimensional Partial Covariance Mass Spectrometry

• Published in: Analytical chemistry (Washington) Vol. 93; no. 45; pp. 14946 - 14954
• Main Authors: Driver, Taran, Bachhawat, Nikhil, Pipkorn, Rüdiger, Frasiński, Leszek J, Marangos, Jon P, Edelson-Averbukh, Marina, Averbukh, Vitali
• Format: Journal Article
• Language: English
• Published: Washington American Chemical Society 16.11.2021
• Subjects: Chemistry; Contaminants; Covariance; Fragments; Mass spectrometry; Mass spectroscopy; Matching; Peptides; Proteins; Scientific imaging; Search engines; Sequences; Spectroscopy
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/acs.analchem.1c00895

We present a protein database search engine for the automatic identification of peptide and protein sequences using the recently introduced method of two-dimensional partial covariance mass spectrometry (2D-PC-MS). Because the 2D-PC-MS measurement reveals correlations between fragments stemming from the same or consecutive decomposition processes, the first-of-its-kind 2D-PC-MS search engine is based entirely on the direct matching of the pairs of theoretical and the experimentally detected correlating fragments, rather than of individual fragment signals or their series. We demonstrate that the high structural specificity afforded by 2D-PC-MS fragment correlations enables our search engine to reliably identify the correct peptide sequence, even from a spectrum with a large proportion of contaminant signals. While for peptides, the 2D-PC-MS correlation-matching procedure is based on complementary and internal ion correlations, the identification of intact proteins is entirely based on the ability of 2D-PC-MS to spatially separate and resolve the experimental correlations between complementary fragment ions.