Peak Filtering, Peak Annotation, and Wildcard Search for Glycoproteomics.

Autor:	Roushan A; Research and Development Group, Protein Metrics Inc, Cupertino, California, USA., Wilson GM; Research and Development Group, Protein Metrics Inc, Cupertino, California, USA., Kletter D; Research and Development Group, Protein Metrics Inc, Cupertino, California, USA., Sen KI; Research and Development Group, Protein Metrics Inc, Cupertino, California, USA., Tang W; Research and Development Group, Protein Metrics Inc, Cupertino, California, USA., Kil YJ; Research and Development Group, Protein Metrics Inc, Cupertino, California, USA., Carlson E; Research and Development Group, Protein Metrics Inc, Cupertino, California, USA., Bern M; Research and Development Group, Protein Metrics Inc, Cupertino, California, USA. Electronic address: bern@proteinmetrics.com.
Jazyk:	angličtina
Zdroj:	Molecular & cellular proteomics : MCP [Mol Cell Proteomics] 2021; Vol. 20, pp. 100011. Date of Electronic Publication: 2020 Dec 08.
DOI:	10.1074/mcp.RA120.002260
Abstrakt:	Glycopeptides in peptide or digested protein samples pose a number of analytical and bioinformatics challenges beyond those posed by unmodified peptides or peptides with smaller posttranslational modifications. Exact structural elucidation of glycans is generally beyond the capability of a single mass spectrometry experiment, so a reasonable level of identification for tandem mass spectrometry, taken by several glycopeptide software tools, is that of peptide sequence and glycan composition, meaning the number of monosaccharides of each distinct mass, e.g., HexNAc(2)Hex(5) rather than man5. Even at this level, however, glycopeptide analysis poses challenges: finding glycopeptide spectra when they are a tiny fraction of the total spectra; assigning spectra with unanticipated glycans, not in the initial glycan database; and finding, scoring, and labeling diagnostic peaks in tandem mass spectra. Here, we discuss recent improvements to Byonic, a glycoproteomics search program, that address these three issues. Byonic now supports filtering spectra by m/z peaks, so that the user can limit attention to spectra with diagnostic peaks, e.g., at least two out of three of 204.087 for HexNAc, 274.092 for NeuAc (with water loss), and 366.139 for HexNAc-Hex, all within a set mass tolerance, e.g., ± 0.01 Da. Also, new is glycan "wildcard" search, which allows an unspecified mass within a user-set mass range to be applied to N- or O-linked glycans and enables assignment of spectra with unanticipated glycans. Finally, the next release of Byonic supports user-specified peak annotations from user-defined posttranslational modifications. We demonstrate the utility of these new software features by finding previously unrecognized glycopeptides in publicly available data, including glycosylated neuropeptides from rat brain. Competing Interests: Conflict of interest Authors declare no competing interests. (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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