Glycosylator: a Python framework for the rapid modeling of glycans

• Published in: BMC bioinformatics Vol. 20; no. 1; pp. 513 - 7
• Main Authors: Lemmin, Thomas, Soto, Cinque
• Format: Journal Article
• Language: English
• Published: London BioMed Central 22.10.2019; BioMed Central Ltd; BMC
• Subjects: Algorithms; Applications programming; Asparagine; Biochemistry; Bioinformatics; Biomedical and Life Sciences; Biomolecular modeling; Biotechnology; Computational biology; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Fructose; Glycan modeling; Glycoprotein; Graphical user interfaces; Life Sciences; Methods; Microarrays; Molecular dynamics; N-linked glycosylation; Nitrogen (Chemical element); Polysaccharides; Software; Structural analysis; Sugar; Web site management software; Workflow software; United States; linked glycosylation; Biomolecular modeling; Glycan modeling; Glycoprotein
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-019-3097-6

Background Carbohydrates are a class of large and diverse biomolecules, ranging from a simple monosaccharide to large multi-branching glycan structures. The covalent linkage of a carbohydrate to the nitrogen atom of an asparagine, a process referred to as N- linked glycosylation, plays an important role in the physiology of many living organisms. Most software for glycan modeling on a personal desktop computer requires knowledge of molecular dynamics to interface with specialized programs such as CHARMM or AMBER. There are a number of popular web-based tools that are available for modeling glycans (e.g., GLYCAM-WEB (http:// https://dev.glycam.org/gp/ ) or Glycosciences.db ( http://www.glycosciences.de/ )). However, these web-based tools are generally limited to a few canonical glycan conformations and do not allow the user to incorporate glycan modeling into their protein structure modeling workflow. Results Here, we present Glycosylator, a Python framework for the identification, modeling and modification of glycans in protein structure that can be used directly in a Python script through its application programming interface (API) or through its graphical user interface (GUI). The GUI provides a straightforward two-dimensional (2D) rendering of a glycoprotein that allows for a quick visual inspection of the glycosylation state of all the sequons on a protein structure. Modeled glycans can be further refined by a genetic algorithm for removing clashes and sampling alternative conformations. Glycosylator can also identify specific three-dimensional (3D) glycans on a protein structure using a library of predefined templates. Conclusions Glycosylator was used to generate models of glycosylated protein without steric clashes. Since the molecular topology is based on the CHARMM force field, new complex sugar moieties can be generated without modifying the internals of the code. Glycosylator provides more functionality for analyzing and modeling glycans than any other available software or webserver at present. Glycosylator will be a valuable tool for the glycoinformatics and biomolecular modeling communities.