Proteome-Wide Identification of Proteins and Their Modifications with Decreased Ambiguities and Improved False Discovery Rates Using Unique Sequence Tags

Identifying proteins and their modification states and with
known levels of confidence remains as a significant
challenge for proteomics. Random or decoy peptide
databases are increasingly being used to estimate the false
discovery rate (FDR), e.g., from liquid chromatography−tandem mass spectrometry (LC−MS/MS) analyses of
tryptic digests. We show that this approach can significantly underestimate the FDR and describe an approach
for more confident protein identifications that uses unique
partial sequences derived from a combination of database
searching and amino acid residue sequencing using high-accuracy MS/MS data. Applied to a Saccharomyces
cerevisiae tryptic digest, the approach provided 3 132
confident peptide identifications (∼5% modified in some
fashion), covering 575 proteins with an estimated zero
FDR. The conventional approach provided 3 359 peptide
identifications and 656 proteins with 0.3% FDR based
upon a decoy database analysis. However, the present
approach revealed ∼5% of the 3 359 identifications to be
incorrect and many more as potentially ambiguous (e.g.,
due to not considering certain amino acid substitutions
and modifications). In addition, 677 peptides and 39
proteins were identified that had been missed by conventional analysis, including nontryptic peptides, peptides
with a variety of expected/unexpected chemical modifications, known/unknown post-translational modifications,
single nucleotide polymorphisms or gene encoding errors,
and multiple modifications of individual peptides.