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

22 January 2021, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

We present a protein database search engine for the automatic identi?cation of peptide and protein sequences using the recently introduced method of two-dimensional partial covariance mass spectrometry (2D-PC-MS). Since 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 speci?city a?orded 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 identi?cation 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.

Keywords

Mass spectrometry
Proteomics
search engines
covariances
Partial correlation analysis
top-down mass spectrometry data

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