Improving the Identification
Rate of Endogenous Peptides Using Electron Transfer
Dissociation and Collision-Induced Dissociation
Eisuke Hayakawa
Gerben Menschaert
Pieter-Jan De Bock
Walter Luyten
Kris Gevaert
Geert Baggerman
Liliane Schoofs
10.1021/pr400446z.s014
https://acs.figshare.com/articles/dataset/Improving_the_Identification_Rate_of_Endogenous_Peptides_Using_Electron_Transfer_Dissociation_and_Collision_Induced_Dissociation/2346511
Tandem
mass spectrometry (MS/MS) combined with bioinformatics tools
have enabled fast and systematic protein identification based on peptide-to-spectrum
matches. However, it remains challenging to obtain accurate identification
of endogenous peptides, such as neuropeptides, peptide hormones, peptide
pheromones, venom peptides, and antimicrobial peptides. Since these
peptides are processed at sites that are difficult to predict reliably,
the search of their MS/MS spectra in sequence databases needs to be
done without any protease setting. In addition, many endogenous peptides
carry various post-translational modifications, making it essential
to take these into account in the database search. These characteristics
of endogenous peptides result in a huge search space, frequently leading
to poor confidence of the peptide characterizations in peptidomics
studies. We have developed a new MS/MS spectrum search tool for highly
accurate and confident identification of endogenous peptides by combining
two different fragmentation methods. Our approach takes advantage
of the combination of two independent fragmentation methods (collision-induced
dissociation and electron transfer dissociation). Their peptide spectral
matching is carried out separately in both methods, and the final
score is built as a combination of the two separate scores. We demonstrate
that this approach is very effective in discriminating correct peptide
identifications from false hits. We applied this approach to a spectral
data set of neuropeptides extracted from mouse pituitary tumor cells.
Compared to conventional MS-based identification, i.e., using a single
fragmentation method, our approach significantly increased the peptide
identification rate. It proved also highly effective for scanning
spectra against a very large search space, enabling more accurate
genome-wide searches and searches including multiple potential post-translational
modifications.
2013-12-06 00:00:00
fragmentation methods
peptide identification rate
MS
electron transfer dissociation
search space
Electron Transfer Dissociation