Glycosylation is one of the most frequently used post-translational modifications (PTM), where proteins are altered with various glycan molecules. Such glycans are sometimes found only in particular groups, species, or organisms. For example, blood group antigens, Galα1,3Gal motif, and N-glycolylneuraminic acid (NeuGc) are not found in humans, and exposure to these non-self glycans can trigger severe allergic reactions in humans. Thus, it is essential to prevent the presence of any antigenic carbohydrate in biopharmaceuticals, and a majority of them are produced in animal cell lines. Therefore, it is crucial to design molecules that can be used to detect the presence of such antigenic carbohydrates in food or pharmaceuticals. Such biomolecules can be particular proteins called lectins, antibodies, and aptamers. The project “SUGARSmart” looks at the development of computational workflow to engineer glycan recognition molecules and enhance their binding affinity and specificity.
The objective of this Marie Skłodowska Curie Action (MSCA) has been to (1) improve computational methodologies for modeling antibody-glycan recognition and (2) develop a computation workflow for the rational design of glycan recognition molecules. A parallel goal of this MSCA Fellowship is to foster the development of the researcher’s career in the glycosciences.