The Sulfated Glycosaminoglycans (GAGs) Are Long, Linear Polysaccharide Chains that Are Typically Found as the Glycan Portion of Proteoglycans. These GAGs Are Characterized by Repeating Disaccharide Units with Variable Sulfation and Acetylation Patterns Along the Chain. GAG Length and Modification Patterns Have Profound Impacts on Growth Factor Signaling Mechanisms Central to Numerous Physiological Processes. Electron Activated Dissociation Tandem Mass Spectrometry is a Very Effective Technique for Assigning the Structures of GAG Saccharides; However, Manual Interpretation of the Resulting Complex Tandem Mass Spectra is a Difficult and Time-Consuming Process that Drives the Development of Computational Methods for Accurate and Efficient Sequencing. We Have Recently Published GAGfinder, the First Peak Picking and Elemental Composition Assignment Algorithm Specifically Designed for GAG Tandem Mass Spectra. Here, We Present GAGrank, a Novel Network-Based Method for Determining GAG Structure using Information Extracted from Tandem Mass Spectra using GAGfinder. GAGrank is based on Google's PageRank Algorithm for Ranking Websites for Search Engine Output. in Particular, It is an Implementation of BiRank, an Extension of PageRank for Bipartite Networks. in Our Implementation, the Two Partitions Comprise Every Possible Sequence for a Given GAG Composition and the Tandem MS Fragments Found using GAGfinder. Sequences Are Given a Higher Ranking If They Link to Many Important Fragments. using the Simulated Annealing Probabilistic Optimization Technique, We Optimized GAGrank's Parameters on Ten Training Sequences. We Then Validated GAGrank's Performance on Three Validation Sequences. We Also Demonstrated GAGrank's Ability to Sequence Isomeric Mixtures using Two Mixtures at Five Different Ratios.


Chemical and Biochemical Engineering

Publication Status

Open Access


National Institutes of Health, Grant U01CA221234

International Standard Serial Number (ISSN)

1535-9484; 1535-9476

Document Type

Article - Journal

Document Version

Final Version

File Type





© 2023 Elsevier; American Society for Biochemistry and Molecular Biology, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Publication Date

01 Apr 2021

PubMed ID