Popitam: Towards new heuristic strategies to improve protein identification from tandem mass spectrometry data

Swiss Institute of Bioinformatics, Geneva, Switzerland.
PROTEOMICS (Impact Factor: 3.97). 01/2003; 3(6):870-8. DOI: 10.1002/pmic.200300402
Source: PubMed

ABSTRACT In recent years, proteomics research has gained importance due to increasingly powerful techniques in protein purification, mass spectrometry and identification, and due to the development of extensive protein and DNA databases from various organisms. Nevertheless, current identification methods from spectrometric data have difficulties in handling modifications or mutations in the source peptide. Moreover, they have low performance when run on large databases (such as genomic databases), or with low quality data, for example due to bad calibration or low fragmentation of the source peptide. We present a new algorithm dedicated to automated protein identification from tandem mass spectrometry (MS/MS) data by searching a peptide sequence database. Our identification approach shows promising properties for solving the specific difficulties enumerated above. It consists of matching theoretical peptide sequences issued from a database with a structured representation of the source MS/MS spectrum. The representation is similar to the spectrum graphs commonly used by de novo sequencing software. The identification process involves the parsing of the graph in order to emphasize relevant sections for each theoretical sequence, and leads to a list of peptides ranked by a correlation score. The parsing of the graph, which can be a highly combinatorial task, is performed by a bio-inspired algorithm called Ant Colony Optimization algorithm.

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Available from: Robin Gras, Jul 28, 2015
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    • "In the present study, we have examined tyrosine nitration of mouse liver mitochondrial proteins after treatment with peroxynitrite followed by 1D and 2D SDS gel electrophoresis, Western blot analysis using an anti-nitrotyrosine antibody, and LC-MS/MS analysis of ingel tryptic digests of the nitrated protein samples. Several algorithms such as Sequest and Popitam were utilized to identify proteins and search post-translational modifications, including tyrosine nitration, based on tandem mass spectrometry data (MS/MS spectra) and peptide sequence databases [10]. On the basis of our initial findings, we focused on the tyrosine nitration of carbamoyl phosphate synthetase 1 (CPS1) in mouse mitochondria. "
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    • "Currently, four identification software packages can be used within swissPIT: Phenyx (GeneBio SA) (Colinge 2003), Popitam (Hernandez 2003), X! Tandem (Craig 2004), and InsPecT (Tanner 2005). The choice of these first four algorithms has been motivated by a number of factors, including their popularity, their known efficiency and their implementation of various search strategies (Hernandez 2005). "
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    • "Their main advantage is the production of results in a reasonable amount of time, but they cannot identify peptides which carry unexpected modifications or mutations. " Open-modification search " tools, such as Popitam [7], OpenSea [15], GutenTag [6] and InsPecT [17], have been specifically designed to handle unexpected amino acid modifications, but they often need preliminary filtering steps. De novo sequencing is another approach, which infers sequence information from the experimental MS/MS spectrum. "
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