The goal in proteomics to identify all peptides in a complex mixture has been largely addressed using various LC MS/MS approaches, such as data dependent acquisition, SRM/MRM, and data independent acquisition instrumentation. Despite these developments, many peptides remain unsequenced, often due to low abundance, poor fragmentation patterns, or data analysis difficulties. Many of the unidentified peptides exhibit strong evidence in high resolution MS(1) data and are frequently post-translationally modified, playing a significant role in biological processes. Proteomics Workbench (PWB) software was developed to automate the detection and visualization of all possible peptides in MS(1) data, reveal candidate peptides not initially identified, and build inclusion lists for subsequent MS(2) analysis to uncover new identifications. We used this software on existing data on the autophagy regulating kinase Ulk1 as a proof of concept for this method, as we had already manually identified a number of phosphorylation sites Dorsey, F. C. et al (J. Proteome. Res. 8(11), 5253-5263 (2009)). PWB found all previously identified sites of phosphorylation. The software has been made freely available at http://www.proteomicsworkbench.com . Graphical Abstract ᅟ.
Keywords: Computational proteomics; MS1 data analysis; Mass spectrometry; PTMs; Peptide identification; Post-translational modifications.