title: An algorithm for identifying multiply modified endogenous proteins using both full-scan and high-resolution tandem mass spectrometric data.
abstract: Mass spectrometry based proteomic experiments have advanced considerably over the past decade with high-resolution and mass accuracy tandem mass spectrometry (MS/MS) capabilities now allowing routine interrogation of large peptides and proteins. Often a major bottleneck to 'top-down' proteomics, however, is the ability to identify and characterize the complex peptides or proteins based on the acquired high-resolution MS/MS spectra. For biological samples containing proteins with multiple unpredicted processing events, unsupervised identifications can be particularly challenging. Described here is a newly created search algorithm (MAR) designed for the identification of experimentally detected peptides or proteins. This algorithm relies only on predefined list of 'differential' modifications (e.g. phosphorylation) and a FASTA-formatted protein database, and is not constrained to full-length proteins for identification. The algorithm is further powered by the ability to leverage identified mass differences between chromatographically separated ions within full-scan MS spectra to automatically generate a list of likely 'differential' modifications to be searched. The utility of the algorithm is demonstrated with the identification of 54 unique polypeptides from human apolipoprotein enriched from the high-density lipoprotein particle (HDL), and searching time benchmarks demonstrate scalability (12 high-resolution MS/MS scans searched per minute with modifications considered). This parallelizable algorithm provides an additional solution for converting high-quality MS/MS data of multiply processed proteins into reliable identifications.
authors.affiliation: Department of Proteomics, Merck & Co., Inc., 126 E. Lincoln Avenue, P.O. Box 2000, Rahway, NJ 07065, USA.
authors.forename: Matthew T
authors.initials: MT
authors.lastname: Mazur
authors.forename: Ray
authors.initials: R
authors.lastname: Fyhr
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001056:Apolipoproteins C / Q000737:chemistry; D030562:Databases, Protein; D006801:Humans; D008075:Lipoproteins, HDL / Q000737:chemistry; D008969:Molecular Sequence Data; D010455:Peptides / Q000737:chemistry; D011506:Proteins / Q000737:chemistry* / Q000145:classification; D040901:Proteomics / Q000379:methods*; D020539:Sequence Analysis, Protein; D012984:Software; D053719:Tandem Mass Spectrometry / Q000379:methods*
chemical_list: D001056:Apolipoproteins C; D008075:Lipoproteins, HDL; D010455:Peptides; D011506:Proteins