Proteome Discoverer version
1.4.288 (PD) was used for peptide identifications. All data sets were
searched with Mascot (version 2.2.1), SEQUEST (with probability score
calculation) as provided in PD, and MS Amanda. Advanced search settings
in PD were changed from default in order to store all PSMs in the
result file (all cutoff filters and thresholds were disabled).
Searches for the HeLa and the histone data sets were performed with
7 ppm precursor mass tolerance and 0.03 Da fragment ion mass tolerance
(0.5 for CID). Following Marx et al., we used 5 ppm precursor mass
tolerance and 0.02 Da fragment mass tolerance for the synthetic peptide
library. For HCD and CID, considered fragment ions were left at defaults
for Mascot and SEQUEST, and set to
b and
y ions for MS Amanda. ETD searches with Mascot and MS Amanda
were performed using
c,
y,
z + 1, and
z + 2 ions.
For the HeLa
data sets, oxidation(M) was set as variable modification,
carbamidomethyl(C) as fixed modification, and trypsin as enzyme
allowing up to two missed cleavages. The peptide library was searched
with oxidation(M) and phosphorylation(S,T,Y) as variable modifications
and up to four missed cleavage sites for trypsin.
Variable modification
settings for the histone data set were oxidation(M),
phosphorylation(S,T,Y), methyl(K,R), dimethyl(K,R), trimethyl(K),
and acetyl(K). Methylthio(C) was set as fixed modification,
GluC (C-terminal cleavage after D or E) as enzyme, and two as the
maximum number of missed cleavages.
Performance comparisons
were based on 1% FDR.
33 (link),34 (link) We generated concatenated forward
and reverse (decoy) protein databases
with contaminants using MaxQuant Sequence Reverser (v1.0.13.13).
14 (link) We searched the HeLa data sets against Swiss-Prot_human
36 (link) (release 2013_10), merged the synthetic peptide
sequences with Swiss-Prot_human for the peptide library, and searched
the histone data against the complete Swiss-Prot (release 2013_10).
For FDR calculation, peptides shorter than 7 amino acids were discarded
and conservative FDR estimation was ensured by preferring the decoy
peptide to an equally scored peptide. Peptide grouping for unique
peptide level FDR estimation was solely based on the peptide sequence,
and the highest score was kept for each peptide group.
Dorfer V., Pichler P., Stranzl T., Stadlmann J., Taus T., Winkler S, & Mechtler K. (2014). MS Amanda, a Universal Identification Algorithm Optimized for High Accuracy Tandem Mass Spectra. Journal of Proteome Research, 13(8), 3679-3684.