Computer Simulations of Biological Macromolecules

Computational models are invaluable for visualisation in molecular biology, as they employ our best quantitative physical understanding of biomolecules and their interactions to predict their dynamics, which is often missing from biophysical experiments. Now that biophysical techniques are revealing highly organised supermacromolecular architectures at the length-scale directly above that of single molecules, which was invisible until very recently, there is a need for new computational tools to interpret these experiments.

We are developing two lines of research in supermacromoleular biology – one for DNA, and one for proteins. While it is well known that DNA is the molecule of heredity and that the sequence of bases in DNA encodes the genetic information that defines an organism, the way in which genomes are regulated is not understood. Recent experimental data shows that the physical arrangement of DNA within the nucleus is critical to genetic control. We have developed a model system involving small DNA circles that we can analyse both by experimental methods and atomistic computer modelling using well established computer programs to understand how the packaging of DNA helps in the control and regulation of the cell, and how it influences recognition by other molecules, such as proteins and drug molecules.

We are also writing our own modelling software that provides a continuum mechanics description of proteins, and which uses experimental electron microscopy data as input to the calculations. The model uses the Finite Element algorithm that we have generalised to include thermal fluctuations, known as Fluctuating Finite Element Analysis (FFEA), we are using this program to model the action of molecular motors such as myosin and dynein, and are improving our physical description of biomolecules and their interactions by adding more accurate representations of the hydrodynamic environment Our approach is highly multidisciplinary, and we can adapt projects to suit researchers with backgrounds as diverse as physics, maths, chemistry, biology and computer science. Collaborative projects including experimental work are also available.