The future of Proteomics: The Consensus

After the Big Nature papers about the Human Proteome [1][2] the proteomics community has been divided by the same well-known topics than genomics had before: same reasons, same discussions [3-7]. No one discusses about the technical issues, the instrument settings, nothing about the samples processing, even anything about the analytical method (Most of both projects are "common" bottom-up experiments). Main issues are data-analysis problems and still Computational Proteomics Challenges.  

Evaluation of Proteomic Search Engines for PTMs Identification

The peptide-centric MS strategy is called bottom-up, in which proteins are extracted from cells, digested into peptides with proteases, and analyzed by liquid chromatography tandem mass spectrometry (LC−MS/MS). More specifically, peptides are resolved by chromatography, ionized in mass spectrometers, and scanned to obtain full MS spectra. Next, some high-abundance peptides (precursor ions) are selected and fragmented to obtain MS/MS spectra by high- energy C-trap dissociation (HCD) or collision-induced dissociation (CID). 

Then, peptides are commonly identified by searching the MS/MS spectra against a database and finally assembled into identified proteins. Database searching plays an important role in proteomics analysis because it can be used to translate thousands of MS/MS spectra into protein identifications (IDs). 

Many database search engines have been developed to quickly and accurately analyze large volumes of proteomics data. Some of the more well-known search engines are Mascot,  SEQUEST, PEAKS DB, ProteinPilot, Andromeda, and X!Tandem. Here a list of commonly use search engines in proteomics and mass spectrometry.