GLYCO-2: a Tool to Quantify Glycan Shielding of Glycosylated Proteins with Improved Data Processing and Computation Speed

MotivationGlycans bound to glycoproteins mediate immune response, including antibody recognition and immune evasion. Previously, we developed an in silico tool GLYCO (GLYcan COverage) to quantify the glycan shielding of a protein surface, applying it to various studies. However, GLYCO lacks sufficient computational efficiency when analyzing larger datasets. ResultsHere we introduce GLYCO-2 which improves the computational speed by [~]4- fold compared to GLYCO by adopting a new analytical cylinder method with k-d trees. GLYCO-2 can calculate glycan shielding from a single coordinate file or from multiple frames derived from molecular dynamics simulations accounting for the inherent flexibility of oligosaccharides. We applied GLYCO-2 to quantify glycan shielding of influenza hemagglutinin (HA) proteins across diverse subtypes that infect humans, revealing an increasing trend in glycan shielding over time within each subtype, likely contributing to immune evasion. Overall, the enhanced computational efficiency of GLYCO-2 allows for faster and easier quantification of glycans, which contributes to the understand of glycan shielding effects in fields such as immunology and vaccine design. Availability and implementationGLYCO-2 is freely available at https://github.com/meteosR/GLYCO-2/ Contactmyungjin.lee@nih.gov or reda.rawi@nih.gov Supplementary informationSupplementary data are available at Bioinformatics online.