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A Glycoinformatics Toolkit

Project description

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Glycobiology is the study of the biological functions, properties, and structures of carbohydrate biomolecules, also called glycans. These large, tree-like molecules are complex, having a wide variety of building blocks as well as modifications and substitutions on those building blocks.

glypy is a Python library providing code for reading, writing, and manipulating glycan structures, glycan compositions, monosaccharides, and their substituents. It also includes interfaces to popular glycan structure databases, GlyTouCan and UnicarbKB using SPARQL queries and an RDF-object mapper.

Example Use Cases

  1. Traverse structures using either canonical or residue-level rule ordering.

  2. Operate on monosaccharide and substituents as nodes and bonds as edges.

  3. Add, remove, and modify these structures to alter glycan properties.

  4. Identify substructures and motifs, classifying glycans.

  5. Evaluate structural similarities with one of several ordering and comparator methods.

  6. Plot tree structures with MatPlotLib, rendering using a configurable symbol nomenclature, such as SNFG, CFG, or IUPAC. Layout using vector graphics for lossless scaling.

  7. Calculate the mass of a native or derivatized glycan.

  8. Generate glycosidic and cross ring cleavage fragments for a collection of glycan structures for performing MS/MS database search.

  9. Perform substructure similarity searches with exact ordering or topological comparison and exact or fuzzy per-residue matching to classify a structure as an N-linked glycan.

  10. Annotate MS spectra with glycan structures, labeling which peaks matched a database entry.

  11. Download all N-Glycans from GlyTouCan

  12. Find all glycans in a list which contain a particular subtree, or find common subtrees in a database of glycans, performing treelet enrichment analysis.

  13. Synthesize all possible glycans using a set of enzymes starting from a set of seed structures.

Citing

If you use glypy in a publication please cite:

Klein, J., & Zaia, J. (2019). glypy - An open source glycoinformatics library. Journal of Proteome Research. https://doi.org/10.1021/acs.jproteome.9b00367

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