Researchers from the University of Queensland are using the National Computational Infrastructure to study the behaviour of biomolecules such as proteins and cell membranes with atomic precision.
Of particular interest is the way these biomolecules interact. Understanding the way that proteins and other molecules bind to cell membranes is challenging because of the variety and complexity of the processes involved.
Professor Alan Mark explains that "Experimentally you can't observe these systems in atomic detail. The only way to really understand how these molecules move and interact is by calculation."
The team uses molecular dynamics simulations to model up to half a million atoms interacting together.
Using what they know from experimental data, the team can design and test the simulations to be as accurate as possible. Once the simulations succeed in predicting experimental results, they can be used to investigate novel problems. Professor Mark says "If we can predict the properties of systems we know well, we can not only trust that the simulations are behaving correctly but we can then look at other things that aren't observable experimentally."
The movement of molecules as they interact, such as the rotation of a hormone receptor following the binding of a hormone to turn on a cell, is impossible to visualise directly. These computational methods allow the researchers to discover exactly what is going on in those systems.
The long term goal of the research is to model cell self-assembly. When cells form, all of the proteins and lipids inside them assemble spontaneously. "The membrane that forms the outside of the cell, together with its many components, self-assembles into a vast array of structures and functional complexes purely based on the underlying thermodynamics and the interactions between the atoms," says Professor Mark.
"We've been trying for a long time to understand the true complexity of the biological membranes," he says. Modelling individual components of these complex systems is already providing new information on key elements controlling cell behaviour. "The more accurately we can simulate these systems, the better we will be able to understand life at an atomic level."
