title: Basophile: accurate fragment charge state prediction improves peptide identification rates.
abstract: In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of charged peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
authors.forename: Dong
authors.initials: D
authors.lastname: Wang
authors.forename: Surendra
authors.initials: S
authors.lastname: Dasari
authors.forename: Matthew C
authors.initials: MC
authors.lastname: Chambers
authors.forename: Jerry D
authors.initials: JD
authors.lastname: Holman
authors.forename: Kan
authors.initials: K
authors.lastname: Chen
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Liebler
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Orton
authors.forename: Samuel O
authors.initials: SO
authors.lastname: Purvine
authors.forename: Matthew E
authors.initials: ME
authors.lastname: Monroe
authors.forename: Chang Y
authors.initials: CY
authors.lastname: Chung
authors.forename: Kristie L
authors.initials: KL
authors.lastname: Rose
authors.forename: David L
authors.initials: DL
authors.lastname: Tabb
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D030562:Databases, Protein; D004563:Electrochemistry; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D008956:Models, Chemical; D010446:Peptide Fragments / Q000737:chemistry*; D010455:Peptides / Q000032:analysis* / Q000737:chemistry; D011498:Protein Precursors / Q000737:chemistry; D012984:Software; D053719:Tandem Mass Spectrometry / Q000379:methods
chemical_list: D010446:Peptide Fragments; D010455:Peptides; D011498:Protein Precursors