A spectrum graph-based protein sequence filtering algorithm for proteoform identification by top-down mass spectrometry

Abstract

Database search is the main approach for identifying proteoforms using top-down tandem mass spectra. However, it is extremely slow to align a query spectrum against all protein sequences in a large database when the target proteoform that produced the spectrum contains post-translational modifications and/or mutations. As a result, efficient and sensitive protein sequence filtering algorithms are essential for speeding up database search. In this paper, we propose a novel filtering algorithm, which generates spectrum graphs from subspectra of the query spectrum and searches them against the protein database to find good candidates. Compared with the sequence tag and gaped tag approaches, the proposed method circumvents the step of tag extraction, thus simplifying data processing. Experimental results on real data showed that the proposed method achieved both high speed and high sensitivity in protein sequence filtration.

A graph-based filtering method for top-down mass spectral identification

“…This paper is an extension of the work originally reported in [22]. In this paper, we propose the spectrum graph matching (SGM) problem and a novel filtering algorithm based on SGM, which constructs spectrum graphs from subspectra of query spectra, and uses the spectrum graphs to filter protein sequences.…”