Software for Peak Finding and Elemental Composition Assignment for Glycosaminoglycan Tandem Mass Spectra
Glycosaminoglycans (GAGs) Covalently Linked to Proteoglycans (PGs) Are Characterized by Repeating Disaccharide Units and Variable Sulfation Patterns Along the Chain. GAG Length and Sulfation Patterns Impact Disease Etiology, Cellular Signaling, and Structural Support for Cells. We and Others Have Demonstrated the Usefulness of Tandem Mass Spectrometry (MS 2 ) for Assigning the Structures of GAG Saccharides; However, Manual Interpretation of Tandem Mass Spectra is Time-Consuming, So Computational Methods Must Be Employed. in the Proteomics Domain, the Identification of Monoisotopic Peaks and Charge States Relies on Algorithms that Use Averagine, or the Average Building Block of the Compound Class Being Analyzed. Although These Methods Perform Well for Protein and Peptide Spectra, They Perform Poorly on GAG Tandem Mass Spectra, Because a Single Average Building Block Does Not Characterize the Variable Sulfation of GAG Disaccharide Units. in Addition, It is Necessary to Assign Product Ion Isotope Patterns to Interpret the Tandem Mass Spectra of GAG Saccharides. to Address These Problems, We Developed GAGfinder, the First Tandem Mass Spectrum Peak Finding Algorithm Developed Specifically for GAGs. We Define Peak Finding as Assigning Experimental Isotopic Peaks Directly to a Given Product Ion Composition, as Opposed to Deconvolution or Peak Picking, Which Are Terms More Accurately Describing the Existing Methods Previously Mentioned. GAGfinder is a Targeted, Brute Force Approach to Spectrum Analysis that Uses Precursor Composition Information to Generate All Theoretical Fragments. GAGfinder Also Performs Peak Isotope Composition Annotation, Which is Typically a Subsequent Step for Averagine-Based Methods. Data Are Available Via ProteomeXchange with Identifier PXD009101.
J. D. Hogan et al., "Software for Peak Finding and Elemental Composition Assignment for Glycosaminoglycan Tandem Mass Spectra," Molecular and Cellular Proteomics, vol. 17, no. 7, pp. 1448 - 1456, Elsevier; American Society for Biochemistry and Molecular Biology, Jul 2018.
The definitive version is available at https://doi.org/10.1074/mcp.RA118.000590
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01 Jul 2018
National Institutes of Health, Grant R21HL131554