Organisers

• Mark Sansom (University of Oxford, United Kingdom)
• Rebecca Wade (EML Research, Germany)

Supports

   CECAM

Oxford Centre for Integrative Systems Biology

   EML Research

Description

Potentially, structural biology and biomolecular modelling/simulations should play a key role in systems biology [1]. Structural and biomolecular simulations of macromolecules and their complexes may provide quantitative parameters for modelling and enable design of functional perturbations of complex systems. Thus, the role of structurally-informed modelling in systems biology should be to provide sufficient understanding to enable correct formulation of more tractable mathematical descriptions of systems whilst retaining the essence of the underlying physical processes.

Thus, one must consider how to formulate the connection between the structures of individual proteins and developing an understanding how a complex biological system involving many such proteins works. One current approach is to exploit multiscale modelling and simulation techniques [2,3] which may allow us to simulate the spatial and temporal properties of large systems. Indeed, considerable progress has been recently achieved in the multiscale modeling of complex biological processes, with multiscale models used to investigate the structure and dynamics of lipid membranes, proteins, peptides and DNA over length and time scales ranging from the atomic to the macroscopic. The success of such models relies upon new theories and methods for constructing accurate multiscale bridges that transfer information between models with different resolutions.

Another approach [4] is exemplified by the estimation of kinetic parameters for the mathematical modelling of biochemical pathways using protein structure information to provide a basis for iterative manipulation of biochemical pathways. One promising approach is the use of comparative molecular field analyses to estimate enzyme kinetic parameters.

In summary, much of ‘traditional’ systems biology aims to predict the emergent behaviour of biological systems on the basis of formal mathematical descriptions of interactions between the set of molecules involved. By combining such formal representations with multi-scale biomolecular models, we should be able to transform somewhat abstract representations of systems into models that reflect biological and biophysical reality with sufficient accuracy to enable prediction of the consequences of molecular level perturbations such as mutations and/or binding of drug molecules [5].

Scientific Objectives

• 1. To examine the prospects for multi-scale simulation in modelling complex cellular and sub-cellular systems;
• 2. To explore the relationships between ‘bottom-up’ biomolecular modelling and ‘top-down’ systems biology modelling of such systems, with a view to developing hybrid models which integrate the two approaches
• 3. To evaluate the two approaches, in terms of their relationship to experimental data on emergent properties of cellular systems

References

1. Beltrao P, Kiel C, Serrano L (2007) Structures in systems biology. Curr Opin Struct Biol. 17:378-384

2. Ayton, G. A., Noid, W. G., and Voth, G. A. (2007) Multiscale modeling of biomolecular systems: in serial and in parallel. Curr. Opin. Struct. Biol. 17, 192-198.

3. Sherwood, P., Brooks, B. R., and Sansom, M. S. P. (2008) Multiscale methods for macromolecular simulations. Curr. Opin. Struct. Biol. 18:630-640

4. Stein, M., Gabdoulline, R.R., Wade, R.C. (2007) Bridging from molecular simulation to biochemical networks. Curr. Opin. Struct. Biol. 17:166-172

5. Aloy P., Russell, R.B. (2006) Structural systems biology: modelling protein interactions Nature Rev. Molec. Cell Biol. 7: 188-197