Toward integration of glycan chemical databases: an algorithm and software tool for extracting sugars from chemical...

Area of Science:

• Glycoscience
• Computational Chemistry
• Bioinformatics

Background:

• Glycan data integration across research fields is essential but challenging due to diverse structure representations.
• Existing methods struggle to integrate glycan data between chemistry and biology.
• The Web 3.0 Unique Representation of Carbohydrate Structures (WURCS) was developed for unique glycan representation.

Purpose of the Study:

• To develop a method for extracting sugar structures from chemical compounds.
• To enable the integration of glycan data from chemical structures into broader scientific resources.
• To create software for automated sugar extraction and WURCS conversion.

Main Methods:

• Developed a novel algorithm to define and identify sugar structures within chemical formulae.
• Implemented the algorithm into software called MolWURCS.
• Tested MolWURCS on glycoconjugate molecules.

Main Results:

• The algorithm successfully identifies and extracts sugar moieties from complex glycoconjugate molecules.
• MolWURCS can distinguish sugars from other biomolecules like amino acids, nucleic acids, and lipids.
• The developed software provides a unique WURCS representation for extracted sugars.

Conclusions:

• MolWURCS facilitates the integration of chemical glycan data into glycoscience resources.
• The software enables consistent and unique representation of glycan structures.
• This advancement supports cross-disciplinary research in glycoscience.