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.
Keywords: de novo sequencing • database searching • borderline hits • MS/MS • MS BLAST • PepNovo