Student research project
Supervisor(s): David Ascher
Most proteins work within a network of interactions with other proteins, and the ability to selectively target specific interactions, modulating protein function and providing the opportunity to develop more selective and effective drugs. But while drugs are usually around 100 Å2, proteins interact tightly using way larger protein-protein interfaces, ranging from 1000–6000 Å2. This raises the challenge of how we can use a small molecule to affect an interface many times larger, which until recently was considered to be flat and undruggable.
We and others have had success using fragment-based drug discovery to identify novel protein-protein interaction modulators. This allows us to take advantage of hot-spots within the protein interfaces that mediate a large proportion of the binding energy, growing the molecule to improve binding affinity and drug like properties. The crystal structures of many protein interface modulators with their targets have been solved, which opens up the possibility for us to ask: what are the major components of binding affinity? and can we use this information to predict fragments likely to bind to a given interface? Using structural bioinformatics and machine learning, these questions will be answered, leading to the development of novel programmes. The students will then also have the opportunity to test these experiments in the lab, using biophysical and structural approaches to test fragment binding.
This project is suitable for a Masters, Honours or PhD student.