Unrestricted identification of modified proteins using MS/MS

Abstract

Proteins undergo PTM, which modulates their structure and regulates their function. Estimates of the PTM occurrence vary but it is safe to assume that there is an important gap between what is currently known and what remains to be discovered. The highest throughput and most comprehensive efforts to catalogue protein mixtures have so far been using MS-based shotgun proteomics. The standard approach to analyse MS/MS data is to use Peptide Fragment Fingerprinting tools such as Sequest, MASCOT or Phenyx. These tools commonly identify 5-30% of the spectra in an MS/MS data set while only a limited list of predefined protein modifications can be screened. An important part of the unidentified spectra is likely to be spectra of peptides carrying modifications not considered in the search. Bioinformatics for PTM discovery is an active area of research. In this review we focus on software solutions developed for unrestricted identification of modifications in MS/MS data, here referred to as open modification search tools. We give an overview of the conceptually different algorithmic solutions to evaluate the large number of candidate peptides per spectrum when accounting for modifications of unrestricted size and demonstrate the value of results of large-scale open modification search studies. Efficient and easy-to-use tools for protein modification discovery should prove valuable in the quest for mapping the dynamics of proteomes.

A Face in the Crowd: Recognizing Peptides Through Database Search

“…Appropriate sequence databases and search configurations prevent reduced identification rates and excessive search times. While simple sets of PTMs may be identified through these algorithms, researchers may need dedicated software tools for data sets in which broader palettes of modifications are present (62). Database search tools are most powerful when integrated into pipelines with other tools, such as those that perform quantitation and sophisticated protein inference.…”

Systematic Errors in Peptide and Protein Identification and Quantification by Modified Peptides

“…The simplest idea would be to allow for different variable modifications in the standard database search. However, because of the combinatorial expansion of the search space, this procedure increases the score thresholds for significant peptide identifications and may thus decrease the total number of identifications at a given FDR (15). Based on our results we propose an alternative strategy, which involves four steps (see Fig.…”

“…To systematically identify peptide modifications in this sample we used the ModifiComb algorithm (19) implemented in MaxQuant (18). Similar to other algorithms ModifiComb can detect modifications in an unbiased manner (15). First, a standard database search is performed to identify unmodified "base" peptides.…”

“…The identification of peptides with modifications is particularly challenging: On the one hand, allowing for multiple possible modifications in a standard database search leads to a combinatorial expansion that dramatically increases the search space (15). On the other hand, when a specific modification is not considered, peptides carrying this modification cannot be correctly identified.…”

Software Analysis of Uncorrelated MS1 Peaks for Discovery of Post-Translational Modifications

“…More recently, investigators have adopted unrestrictive search approaches [36][37][38][39], where all possible modifications are searched at once. When combined with conventional protein database search strategies, these methods are limited by the number of simultaneous variable peptide modifications that can be searched.…”