Unrestrictive Identification of Multiple Post-translational Modifications from Tandem Mass Spectrometry Using an Error-tolerant Algorithm Based on an Extended Sequence Tag Approach

Abstract

Identification of post-translational modifications (PTMs) is important to understanding the biological functions of proteins. MS/MS is a useful tool to identify PTMs. Most existing search tools are restricted to take only a few types of PTMs as input. Here we describe a new algorithm, called MODi (pronounced "mod eye"), that rapidly searches for all known types of PTMs at once without limiting a multitude of modified sites in a peptide. MODi introduces the notion of a tag chain, a combination structure made from multiple sequence tags, that effectively localizes modified regions within a spectrum and overcomes de novo sequencing errors common in tag-based approaches. MODi showed its performance competence by identifying various types of PTMs in analysis of PTM-rich proteins such as glyceraldehyde-3-phosphate dehydrogenase and lens protein. We demonstrated that MODi innovatively manages the computational complexity of identifying multiple PTMs in a peptide, which may exist in a greater variety than usually expected. In addition, it is suggested that MODi has great potential to discover novel modifications.