Automated glycopeptide analysis-review of current state and future directions

Abstract

Glycosylation of proteins is involved in immune defense, cell-ell adhesion, ellular reognition and pathogen binding and is one of the most common and ccomplex post-translational modifications. Science is still struggling to assign detailed mechanisms and functions to this form of conjugation. Even the structural analysis of glycoproteins- glycoproteomics-remains in its infancy due to the scarity of high-throughput analytical platforms capable of determining glycopeptide composition and structure, especially platforms for ccomplex biological mixtures. Glycopeptide composition and structure can be determined with high mass-acuray mass spectrometry, particularly when combined with chromatographic separation, but the sheer volume of generated data necessitates computational software for interpretation. This review disusses the current state of glycopeptide assignment software-advances made to date and issues that remain to be addressed. The various software and algorithms developed so far provide important insights into glycoProteomics. However, thereis currently no freely available software that can analyzespectral data in batch and unambiguously determine glycopeptide compositions for N- and O-linked glycopeptides from relevant biological sources such as human milk and serum. Few programs are capable of aiding in structural determination of the glycan component. To significantly advance the field of glycoProteomics, analytical software and algorithms are required that: (i) solve for both N- and O-linked glycopeptide compositions, structures and glycosites in biological mixtures; (ii) are high-throughput and process data in batches; (iii) can interpretmass spectral data from a variety of sources and (iv) are open source and freely available. © The Author 2012. Published by Oxford University Press.