A Parent Mass Filter Algorithm for Peptide Sequencing from Tandem Mass Spectra

In this paper, we propose a database search peptide sequencing algorithm, called PMF-MI (Parent Mass Filter with Mass Index), that work well on spectra with missing peaks and few tags, such as the GPM database. The main idea in PMF-MI is to use the parent mass as an effective filter for the set of putative peptides to be considered. Then, this set of putative peptides can be globally matches against the given spectrum for scoring. This method eliminates the need for having tags to filter the peptide database. Similar ideas have been proposed in the past, we push this idea further by performing a full pre-indexing of all the peptides in the database by their parent masses. This pre indexing of the peptide database has to be performed only once and based on current database sizes, the entire index uses only 20GB. A typical parent mass of a given spectrum will produce a set of about 200,000 putative peptides on average which our index can retrieve in less than a second. We ran our PMF-MI algorithm on the GPM spectra where the annotated peptide agrees with the precursor peptide mass of the spectra. On this dataset of 877 spectra, our PMF-MI algorithm is competitive with INSPECT, the state of the art database search method today. Our PMF-MI recovered 367 correct peptides compared to 376 for INSPECT (based on top 10 ranked results).