Dataset Information

GLYCO: a tool to quantify glycan shielding of glycosylated proteins.

ABSTRACT:

Motivation

Glycans play important roles in protein folding and cell-cell interactions-and, furthermore, glycosylation of protein antigens can dramatically impact immune responses. While there have been attempts to quantify the glycan shielding or coverage of a protein surface, none of the publicly available tools analyzes glycan shielding computationally at an atomistic level.

Results

Here, we developed an in silico approach, GLYCO (GLYcan COverage), to quantify the glycan shielding of a protein surface. The software provides insights into glycan-dense/sparse regions of the entire protein surface or a subset of the protein surface. GLYCO calculates glycan shielding from a single coordinate file or from multiple coordinate files, for instance, as obtained from molecular dynamics simulations or by nuclear magnetic resonance spectroscopy structure determination, enabling analysis of glycan dynamics. Overall, GLYCO provides fundamental insights into the glycan shielding of glycosylated proteins.

Availability and implementation

GLYCO is freely available at GitHub (https://github.com/myungjinlee/GLYCO).

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Lee M

PROVIDER: S-EPMC8796370 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Publications

GLYCO: a tool to quantify glycan shielding of glycosylated proteins.

Lee Myungjin M Reveiz Mateo M Rawi Reda R Kwong Peter D PD Chuang Gwo-Yu GY

Bioinformatics (Oxford, England) 20220101 4

<h4>Motivation</h4>Glycans play important roles in protein folding and cell-cell interactions-and, furthermore, glycosylation of protein antigens can dramatically impact immune responses. While there have been attempts to quantify the glycan shielding or coverage of a protein surface, none of the publicly available tools analyzes glycan shielding computationally at an atomistic level.<h4>Results</h4>Here, we developed an in silico approach, GLYCO (GLYcan COverage), to quantify the glycan shieldi ...[more]

PMID: 34864901

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Project description:BackgroundGlycan-related genes play a fundamental role in various processes for energy acquisition and homeostasis maintenance while adapting to the environment in which the organism exists; however, their role in the microbiome in the environment is unclear.MethodsSequence alignment was performed between known glycan-related genes and complete genomes of microorganisms, and optimal parameters for identifying glycan-related genes were determined based on the alignments. Using the constructed scheme (> 90% of identity and > 25 aa of alignment length), glycan-related genes in various environments were identified from 198 different metagenome data.ResultsAs a result, we identified 86.73 million glycan-related genes from the metagenome data. Among the 12 environments classified in this study, the percentage of glycan-related genes was high in the human-associated environment, suggesting that these environments utilize glycan metabolism better than other environments. On the other hand, the relative abundances of both glycoside hydrolases and glycosyltransferases surprisingly had a coverage of over 80% in all the environments. These glycoside hydrolases and glycosyltransferases were classified into two groups of (1) general enzyme families identified in various environments and (2) specific enzymes found only in certain environments. The general enzyme families were mostly from genes involved in monosaccharide metabolism, and most of the specific enzymes were polysaccharide degrading enzymes.ConclusionThese findings suggest that environmental microorganisms could change the composition of their glycan-related genes to adapt the processes involved in acquiring energy from glycans in their environments. Our functional glyco-metagenomics approach has made it possible to clarify the relationship between the environment and genes from the perspective of carbohydrates, and the existence of glycan-related genes that exist specifically in the environment.

Dataset Information

GLYCO: a tool to quantify glycan shielding of glycosylated proteins.

Motivation

Results

Availability and implementation

Supplementary information

Publications

GLYCO: a tool to quantify glycan shielding of glycosylated proteins.

Similar Datasets

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