A Turn-Key Approach for Large-Scale Identification of Complex Posttranslational Modifications
journal contributionposted on 17.12.2015 by Jian Wang, Veronica G. Anania, Jeff Knott, John Rush, Jennie R. Lill, Philip E. Bourne, Nuno Bandeira
Any type of content formally published in an academic journal, usually following a peer-review process.
The conjugation of complex post-translational modifications (PTMs) such as glycosylation and Small Ubiquitin-like Modification (SUMOylation) to a substrate protein can substantially change the resulting peptide fragmentation pattern compared to its unmodified counterpart, making current database search methods inappropriate for the identification of tandem mass (MS/MS) spectra from such modified peptides. Traditionally it has been difficult to develop new algorithms to identify these atypical peptides because of the lack of a large set of annotated spectra from which to learn the altered fragmentation pattern. Using SUMOylation as an example, we propose a novel approach to generate large MS/MS training data from modified peptides and derive an algorithm that learns properties of PTM-specific fragmentation from such training data. Benchmark tests on data sets of varying complexity show that our method is 80–300% more sensitive than current state-of-the-art approaches. The core concepts of our method are readily applicable to developing algorithms for the identifications of peptides with other complex PTMs.