Glycosylator
Glycosylator models and refines glycans in protein structures to support identification and analysis of N-linked glycosylation and complex multi-branching carbohydrate conformations.
Key Features:
- Glycan modeling: Models glycans within protein structures ranging from monosaccharides to complex multi-branching glycan structures.
- N-linked glycosylation support: Represents glycosylation at asparagine residues and across sequons for analysis of N-linked glycosylation.
- Genetic algorithm refinement: Applies a genetic algorithm to refine modeled glycans, remove steric clashes, and explore alternative conformations.
- Template-based identification: Identifies specific three-dimensional glycans on protein structures using a library of predefined templates.
- Extensible polymer library: Provides a generic library design that allows incorporation of additional polymer types.
- CHARMM topology basis: Uses the CHARMM force field as the molecular topology basis to enable generation of new complex sugar moieties without internal code changes.
- Implementation: Implemented as a Python framework.
Scientific Applications:
- Glycan identification in structures: Identification and modeling of glycans in protein structural models.
- N-linked glycosylation analysis: Analysis of glycosylation at asparagine residues and across sequons.
- Structural refinement: Refinement of glycan conformations to resolve steric clashes for structural and functional studies.
- Generation of novel sugar moieties: Generation and parametrization of new complex sugar moieties using CHARMM-based topologies.
- Glycoinformatics and biomolecular modeling: Support for research workflows in glycoinformatics and biomolecular modeling.
Methodology:
Implemented in Python, Glycosylator uses a library of predefined glycan templates and the CHARMM force field as its molecular topology basis and applies a genetic algorithm to refine modeled glycans and remove steric clashes; its generic library structure permits adding polymer types and generating new complex sugar moieties without changing internal code.
Topics
Details
- Tool Type:
- command-line tool
- Programming Languages:
- Python
- Added:
- 1/9/2020
- Last Updated:
- 12/3/2020
Operations
Publications
Lemmin T, Soto C. Glycosylator: a Python framework for the rapid modeling of glycans. BMC Bioinformatics. 2019;20(1). doi:10.1186/s12859-019-3097-6. PMID:31640540. PMCID:PMC6806574.