Research in the Wilson group

Image depicting the time scales and system sizes that different computational methods can be used to describe

Research in the group sits at the interface of biochemistry, chemistry, biophysics and computer science. Through using computer models we can obtain high-resolution structural, dynamical and mechanistic information about biochemical processes. The group used a multiscale computational modeling approach with techniques including density functional theory, hybrid (QM/MM) calculations, atomistic molecular dynamics simulations, and coarse grain molecular dynamics simulations. The two main research themes in the group are 1) understanding the membrane embedded enzymes involved in the biosynthesis of glycans and 2) gaining a more complete understanding of non-covalent carbohydrate–protein interactions.

Glycan Synthesis

Glycans play an important role in cell-cell communication and form the basis of immune system recognition and response. The chemical composition of glycans, dictates the information that is stored and relayed between the cells. Glycan biosynthesis is performed by a group of membrane embedded enzymes known as glycosyltransferases. We are interested in understanding the structure and mechanism of action of glycosyltransferase enzymes. Gaining a better understanding of these enzymes will assist in the development of novel therapeutics to aid in the diagnosis and treatment of a variety of disease such as cancer and bacterial infections.

3D structure of a membrane embedded glycosyltransferase
Stacking interaction between a carbohydrate molecule and amino acid residue

Carbohydrate–Protein Interactions

Carbohydrate–protein interactions drive many diverse biological processes and play an important role in development, immunology, infection, and carcinogenesis. Computational techniques allow for the atomistic details of these non-covalent interactions to be investigated. Through gaining a better understanding of these interactions novel technologies exploit these contacts can be developed for diverse biomedical applications.