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.
Published by Oxford University Press 2021. This work is written by US Government employees and is in the public domain in the US.