- Professor Vito Ferro, UQ
- Professor Deirdre Coombe, Curtin University
Glycosaminoglycans (GAGs), also known as mucopolysaccharides, are negatively-charged polysaccharide compounds. They are a key constituent of the extracellular matrix and act as a filler substance between cells and fibres in tissues. These molecules also play a role in several viral infections, in which they enhance cell entry and release of the viruses.
Interest continues to grow in understanding the precise nature of the interactions between GAGs and their binding partners and in defining specific biologically active sequences or arrangements of domains.
Existing biomolecular modelling programs have been applied to model these structures but there is still room to improve molecular recognition of protein–GAG complexes. Development of computational tools for GAGs has the potential to aid in innovations in human health and disease, glycomimetic drug design, and more.
You will work with the atomistic 3D models of biological molecules of interest in our group.
This work concentrates on structure-based approaches and the successful applicant will therefore apply a range of computational modelling and drug design techniques such as molecular docking, protein folding, high performance computing and visualisation tools.
You will work in a highly interdisciplinary environment and will have the opportunity to collaborate with experimental researchers for experimentally validating the established models and generated hypothesis.
QUT has access to high performance computing systems (supercomputers) for the researchers. You will be using open source and commercial modelling software.
Existing biomolecular modelling programs have been applied to model these structures but there is still room to improve molecular recognition of protein–GAG complexes.
This project aims to develop a computational framework to model to model, dock, and simulate protein–GAG/GAG mimetics and serve as a tool to reveal the atomic details behind the molecular roles GAGs play in various biological processes.
This will advance knowledge in the fields of chemistry and biology.
Skills and experience
The ideal applicant is a highly motivated individual with a strong interest in applying computational tools to address complex chemical and biological questions.
A solid background in chemistry and biophysics is required, such as an undergraduate or dual degrees in pharmacy, chemistry, biology, computing or a related discipline.
Previous experience with computational chemistry, cheminformatics, or computational drug design tools and software packages is a plus.
You may be eligible to apply for a research scholarship.
Contact the supervisor for more information.