title: A stringent approach to improve the quality of nitrotyrosine peptide identifications.
abstract: Tyrosine nitration is the consequence of a complex machinery of formation and merging of oxygen and nitrogen radicals, and has been associated with both physiological pathways as well as with several human diseases. The latter turned this posttranslational protein modification into an interesting biomarker, being either a consequence of the disease or a factor contributing to the disease onset. However, the interpretation of MS and MS/MS data of peptides containing nitrotyrosine has proven to be very challenging and consequently, the risk of linking MS/MS spectra to incorrect peptide sequences exists and has been reported. Here, we discuss the causes of data misinterpretation and describe a general method to avoid mistakes of MS/MS spectrum misinterpretation. Central in our approach is the reduction of nitrotyrosine into aminotyrosine and the use of the Peptizer algorithm to inspect MS/MS quality-related assumptions.
authors.affiliation: Department of Medical Protein Research, VIB, Ghent, Belgium. bart.ghesquiere@vib-ugent.be
authors.forename: Bart
authors.initials: B
authors.lastname: Ghesquière
authors.forename: Kenny
authors.initials: K
authors.lastname: Helsens
authors.forename: Joël
authors.initials: J
authors.lastname: Vandekerckhove
authors.forename: Kris
authors.initials: K
authors.lastname: Gevaert
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D019295:Computational Biology; D006801:Humans; D010449:Peptide Mapping / Q000592:standards / Q000706:statistics & numerical data; D010455:Peptides / Q000737:chemistry*; D040901:Proteomics / Q000379:methods / Q000592:standards* / Q000706:statistics & numerical data; D011786:Quality Control; D012984:Software; D053719:Tandem Mass Spectrometry / Q000592:standards* / Q000706:statistics & numerical data; D014443:Tyrosine / Q000031:analogs & derivatives* / Q000032:analysis
chemical_list: D010455:Peptides; C002744:3-nitrotyrosine; D014443:Tyrosine