Theoretical Approaches
Molecular Dynamics
In general, in SBCB we are interested in using computational methods to explore the relationship between structure and function in membrane proteins. This is important, as membrane proteins account for ~25% of all genes, and play key roles in the physiology of cells. In the context of Systems Biology we are interested in using multi-scale simulations to ‘bridge the gap’ between molecular structure of membrane proteins and more complex signalling systems, described in more abstract computational terms. We have collaborations with a number of experimental groups, on systems ranging from bacterial chemotaxis to cell signalling at membranes in relation to cancer. We also have links to simulation groups in Germany and elsewhere in Europe who are developing comparable multiscale approaches for other systems including drug detoxification and signalling in relation to asthma.
Our group uses a multi-scale biomolecular modelling approach, combining atomistic and coarse-grained molecular dynamics with elastic network modelling, to understand the structure-function relationships of membrane proteins. Such techniques allow us to probe the behaviour of detailed models of biomolecular systems, typically over experimentally inaccessible timescales, and allow us to describe the flexibility of proteins and their interactions with their environment. A key part of our work in the systems centre is the development of high throughput multi-scale techniques in order to e.g. understanding of signalling mechanisms in the methyl-accepting chemoreceptor proteins (MCPs). High throughput techniques allow us to integrate simulations with experimental data on both wild type and mutant protein behaviour
A key aim of this programme is to develop links between biomolecular modelling and more conventional systems modelling. To this end we wish to use agent-based models to capture e.g. the essence of helix/helix interactions in receptors, thus enabling modelling of larger scale membrane systems dynamics. This approach will explore combining the use of agent based models with the output for coarse-grained molecular dynamics simulation to describe the dynamics of selected membrane signalling systems.
Mathematical Approaches
Mathematical approaches aim to address issues across a number of spatial scales. At the subcellular level, we are using clustering techniques and information theory to understand microarray data and infer network architecture from data. At the cell and tissue level we are employing ODE, PDE and hybrid cell-based models.
Computational Approaches
There are a number of computational approaches spread through the centre. From the perspective of Data Analysis and Visualisation: We have started the Cellular and Sub-cellular quantitative image analysis platform ; there are extensive bioinformatics efforts trying to characterize networks of protein interactions; and we are establishing a toolkit for the analysis of biological timeseries. From the perspective of Simulation see mathematical approaches for more details; but briefly we are using ODE, PDE, Discrete state, cell based modelling approaches and MD simulations and investigating the role of fluctuations in our models.
Engineering Approaches
In Engineering Science at Oxford, we use control engineering tools for designing optimal experiments to discriminate between models of biochemical systems, modelled using nonlinear differential equations.
The purpose of these experiments is to produce a set of experimental data that can be used to invalidate some of the candidate models, thus narrowing down the possible interaction networks. At the same time, we use systems engineering approaches to analyze Systems Biology models using SOSTOOLS for robust stability and robust performance (this work is supported by EPSRC project EP/E05708X/1, see sysos.eng.ox.ac.uk/control/sysos). Moreover, we use control engineering design methodologies to propose modifications and feedback mechanisms for Synthetic Biology. We coordinate a newly established Network in Synthetic Biology (co-funded by BBSRC, EPSRC, ESRC and AHRC, BB/F018479/1) which aims to create the necessary environment for control/electrical/computer engineers, physicists, biochemists and ELSI members to interact and address current challenges in the new field of Synthetic Biology (see www.rosbnet.org).