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]{role="mod"} 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]{role="term"} queries and an RDF-object mapper.
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Traverse structures using either canonical or residue-level rule ordering.
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Operate on monosaccharide and substituents as nodes and bonds as edges.
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Add, remove, and modify these structures to alter glycan properties.
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Identify substructures and motifs, classifying glycans.
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Evaluate structural similarities with one of several ordering and comparator methods.
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Plot tree structures with MatPlotLib, rendering using a configurable symbol nomenclature, such as SNFG, CFG, or IUPAC. Layout using vector graphics for lossless scaling.
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Calculate the mass of a native or derivatized glycan.
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Generate glycosidic and cross ring cleavage fragments for a collection of glycan structures for performing MS/MS database search.
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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.
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Annotate MS spectra with glycan structures, labeling which peaks
: matched a database entry.
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Download all N-Glycans from GlyTouCan
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Find all glycans in a list which contain a particular subtree, or
: find common subtrees in a database of glycans, performing treelet enrichment analysis.
- Synthesize all possible glycans using a set of enzymes starting from
: a set of seed structures.
If you use [glypy]{role="mod"} 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