Title :
Peptide identification by tandem mass spectra: an efficient parallel searching
Author :
Oh, Jung Hun ; Gao, Jean
Author_Institution :
Dept. of Comput. Sci. & Eng., Texas Univ., Arlington, TX, USA
Abstract :
De novo peptide sequencing that determines the amino acid sequence of a peptide via tandem mass spectrometry (MS/MS) has been increasingly used nowadays in proteomics for protein identification. Current de novo methods generally employ a graph theory which usually produces a large number of candidate sequences and causes heavy computational cost while trying to determine a sequence with less ambiguity. We present a novel de novo sequencing algorithm which greatly reduces the number of candidate sequences. By utilizing certain properties of b- and y-ion series in MS/MS spectrum, we propose a reliable two-way parallel searching algorithm to filter out the peptide candidates which are further pruned by an intensity evidence based screening criterion. And we find an adjusted value required to determine the position of end node of b- and y-ion series for the charged +2 precursor in our graph. Results of our algorithm are compared with those of PEAKS, a well-known de novo sequencing software. Experimental results demonstrate the six sequences are identical with the correct sequences. And for the further pruning, rankings of our result remain unchanged even though the screening criterion changes. Therefore we can reduce the number of candidate sequences by adopting a proper screening criterion.
Keywords :
biology computing; mass spectra; molecular biophysics; molecular configurations; parallel algorithms; proteins; PEAKS; amino acid sequence; b-ion series; de novo peptide sequencing; efficient parallel searching; graph theory; peptide identification; protein identification; proteomics; tandem mass spectra; tandem mass spectrometry; two-way parallel searching algorithm; y-ion series; Amino acids; Computational efficiency; Filters; Graph theory; Mass spectroscopy; Peptides; Proteins; Proteomics; Sequences; Software algorithms;
Conference_Titel :
Bioinformatics and Bioengineering, 2005. BIBE 2005. Fifth IEEE Symposium on
Print_ISBN :
0-7695-2476-1
DOI :
10.1109/BIBE.2005.45