The tryptic peptide mixture was eluted with 0.1% this website formic acid. LC-MS/MS analysis was performed using a Thermo Finnigan’s ProteomeX workstation LTQ linear ion trap MS (Thermo Electron, San Jose, CA) equipped with NSI sources (San Jose, CA) as reported previously (Heo et al., 2007). Briefly, 12 μL of peptide from the

in-gel digestion was injected and loaded onto a peptide trap cartridge (Agilent, Palo Alto, CA). Trapped peptides were eluted onto a 10 cm reversed-phase (RP) PicoFrit column packed in-house with 5 μm, 300 Å pore size C18, followed by gradient elution. Mobile phases consisted of H2O (A) and ACN (B) containing 0.1% v/v formic acid. The flow rate was maintained at 200 nL min−1. The gradient started at 2% B, reached 60% B in 50 min, 80% B in the next 5 min and 100% A in the final 15 min. Data-dependent acquisition (m/z 400–1800) was enabled, and each survey MS scan was followed

by five MS/MS scans with dynamic exclusion within 30 s. The spray voltage was 1.9 kV and the temperature of the ion transfer tube was set to 195 °C. The normalized collision energy was set to 35%. Tandem mass spectra were extracted, and the charge state was deconvoluted and deisotoped using sorcerer 3.4 beta2 (Sorcerer software 3.10.4, Sorcerer Web interface 2.2.0 r334 and Trans-Proteomic Pipeline 2.9.5). All MS/MS samples were analyzed using sequest (Thermo Finnigan, San Jose, CA; version v.27, rev. 11), which was set to search the NCBI database (L. Veliparib order monocytogenes, 6365 entries) with semiTrypsin as the digestion enzyme. SEQUEST search parameters set the fragment ion mass tolerance to 1.00 Da and the parent ion tolerance to 1.5 Da. Oxidation of methionine and the addition of iodoacetamide to cysteine were specified as fixed modifications. nearly To improve false-positive statistics, the decoy option was selected while searching data using the sorcerer program, consequently improving the results by reducing noise. scaffold (version Scaffold-02_04_00, Proteome Software Inc., Portland, OR) was used to validate MS/MS-based peptide and protein identifications. Identifications were accepted only if proteins had a probability >95.0% and

contained at least two identified peptides, as specified by the Peptide Prophet algorithm (Keller et al., 2002). Protein probabilities were assigned by the Protein Prophet algorithm (Nesvizhskii et al., 2003). Proteins containing similar peptides that could not be differentiated based on MS/MS analysis alone were grouped together in order to satisfy the principles of parsimony. The peptide false-positive rate (FPR) was calculated using the scaffold software. For each charge state, the incorrect assignments were tabulated to calculate the FPRi=[(#assigned incorrect at 95% probability)/(total# incorrect assigned)] × 100, with i being the charge state. An assignment was considered correct if associated with a protein that has 95% probability, according to the Protein Prophet algorithm (Hendrickson et al.