GlycReSoft

GlycReSoft assigns glycan compositions from liquid chromatography-mass spectrometry (LC-MS) data by leveraging biosynthetic network relationships among glycans to improve identification sensitivity and accuracy.

Key Features:

• Biosynthetic Network Relationships: Incorporates biosynthetic network relationships to evaluate related glycan compositions during assignment.
• Likelihood Scoring Functions: Optimizes likelihood scoring functions based on the chemical properties of glycans and LC-MS-derived mass and abundance information.
• Network Laplacian Regularization: Applies network Laplacian regularization to smooth likelihood scores and integrate prior knowledge about expected glycan families.
• Graph-Based Representation and Versatility: Expresses relationships between compositions as a graph, enabling application to N-glycans, O-glycans, and heparan sulfate.

Scientific Applications:

• Glycan Composition Assignment: Assigning glycan compositions from LC-MS data in complex biological samples analyzed by high-resolution mass spectrometry.
• Glycosylation Studies: Investigating roles of glycans in biological processes and disease mechanisms through more accurate composition assignments.
• Bioinformatics and Systems Biology: Supporting bioinformatics and systems biology analyses that require characterization of glycosylation patterns.

Methodology:

Computational methods include biosynthetic network exploration, likelihood scoring functions optimized on glycan chemical properties and MS-derived mass/abundance substructures, network Laplacian regularization for score smoothing and prior integration, and graph-based representation of composition relationships.