ArticleBMC bioinformatics2019
Glycosylator: a Python framework for the rapid modeling of glycans.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- A computational analysis of the glycoprotein lipoprotein receptor-related protein 1 structure and the role of glycans as quaternary glue.Bioinformatics (Oxford, England) · 2026Article
- Glycan masking in immunogen design: computational and experimental methods.Frontiers in immunology · 2025Review
- BuildAMol: a versatile Python toolkit for fragment-based molecular design.Journal of cheminformatics · 2024Article
- Microsecond dynamics control the HIV-1 Envelope conformation.Science advances · 2024Article
- A framework for the simulation of individual glycan coordinates to analyze spatial relationships within the glycocalyx.Frontiers in cell and developmental biology · 2024Article
- Molecular Modeling and Simulation of the Mycobacterial Cell Envelope: From Individual Components to Cell Envelope Assemblies.The journal of physical chemistry. B · 2023Review
- Trapping the HIV-1 V3 loop in a helical conformation enables broad neutralization.Nature structural & molecular biology · 2023Article
- Structure and supramolecular organization of the canine distemper virus attachment glycoprotein.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Thirty years of molecular dynamics simulations on posttranslational modifications of proteins.Physical chemistry chemical physics : PCCP · 2022Review
- Structure of the human heterodimeric transporter 4F2hc-LAT2 in complex with Anticalin, an alternative binding protein for applications in single-particle cryo-EM.Scientific reports · 2022Article
- Extended antibody-framework-to-antigen distance observed exclusively with broad HIV-1-neutralizing antibodies recognizing glycan-dense surfaces.Nature communications · 2021Article
- Review
- Glycans in Virus-Host Interactions: A Structural Perspective.Frontiers in molecular biosciences · 2021Review
- Three-Dimensional Structures of Carbohydrates and Where to Find Them.International journal of molecular sciences · 2020Review
- Dissecting the conformation of glycans and their interactions with proteins.Journal of biomedical science · 2020Review
- Comparative ligand structural analytics illustrated on variably glycosylated MUC1 antigen-antibody binding.Beilstein journal of organic chemistry · 2020Article
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2 authors.
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Abstract
backgroundCarbohydrates 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.
resultsHere, 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.
conclusionsGlycosylator 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.
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