Rapid validation of protein identifications with the borderline statistical confidence via de novo sequencing and MS BLAST searches.
Protein identifications with the borderline statistical confidence are typically produced by matching a few marginal quality MS/MS spectra to database peptide sequences and represent a significant bottleneck in the reliable and reproducible characterization of proteomes. Here, we present a method for rapid validation of borderline hits that circumvents the need in, often biased, manual inspection of raw MS/MS spectra. The approach takes advantage of the independent interpretation of corresponding MS/MS spectra by PepNovo de novo sequencing software followed by mass spectrometry-driven BLAST (MS BLAST) sequence-similarity database searches that utilize all partially inaccurate, degenerate and redundant candidate peptide sequences. In a case study involving the identification of more than 180 Caenorhabditis elegans proteins by nanoLC-MS/MS analysis on a linear ion trap LTQ mass spectrometer, the approach enabled rapid assignment (confirmation or rejection) of more than 70% of Mascot hits of borderline statistical confidence.
Wielsch
Natalie
N
Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany.
Thomas
Henrik
H
Surendranath
Vineeth
V
Waridel
Patrice
P
Frank
Ari
A
Pevzner
Pavel
P
Shevchenko
Andrej
A
D000595:Amino Acid Sequence; D000818:Animals; D029742:Caenorhabditis elegans Proteins / Q000032:analysis* / Q000302:isolation & purification; D019295:Computational Biology / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods; D008969:Molecular Sequence Data; D040901:Proteomics / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*
D029742:Caenorhabditis elegans Proteins