Form and Function of Biological Molecules Physics and chemistry provides the tools to describe forces that drive molecular interactions. In biology the same forces are in play, but compounded by the complexity of biological molecules. This complexity is described on one level by the linear sequences of DNA, RNA, and protein, but in many cases is only fully realised when these molecules are considered in 3-dimensions. Biological complexity is closely linked to the ability of molecules to make multiple interactions, each encoded by matching surfaces where complementary shape and charge have evolved. Our group develops theoretical methods, based in physics and chemistry, to analyse such interactions. The methods can then be used to predict which molecules interact, and thereby establish how information is transferred along biological pathways. This is the sort of anlaysis that drives computational screening of drug candidates against a biological target, making predictions of which candidates will interact most strongly, guiding subsequent experiments. A related area is the role of pH in biology. We know that pH, within a cell for example, is tightly regulated and applying computational methods it is possible to see at a molecular level the consequences of a failure in pH regulation.

Jim is a Reader in the Faculty of Life Sciences. His research group works in the areas of bioinformatics and structural modelling of biological molecules, complementing the work of other staff in the Structural and Functional Systems grouping.

Jim started his University education with a Physics degree at the University of Bristol (1979) before moving into the Biochemistry Department at Bristol for his PhD (1983). A period as a post-doctoral Fellow at Yale University with Fred Richards and Tom Steitz (1983-1988), was followed by 10 years at the BBSRC Institute of Food Research, and a short spell at Glasgow University. In 2000 he took up a Lectureship at UMIST, and moved (with the Universities merger) to the current UoM.

In following a primary interest of developing algorithms to dissect structure/function relationships in proteins and other molecules, collaborations are maintained with several theoretical and experimental groups within and outside the UK. A major teaching activity is directing the UoM MSc in Bioinformatics and Systems Biology. Jim is currently on the Editorial Board of several journals, including Biophysical Chemistry.

Structural Bioinformatics and Macromolecular Modelling

Full laboratory pages for Jim Warwicker's Group are at Warwicker group

We are developing models to calculate interactions within biological molecules and their complexes, thereby assessing contributions to structural stability and ligand binding energies. Model development looks to identify areas in which the physics and chemistry of macromolecular systems can be simplified whilst maintaining the detailed 3-dimensional information generated by structural studies. Recent effort has been directed towards improving prediction of pH-dependence through the introduction of a measure of rigidity/flexibility within proteins.

Theoretical work generates hypotheses for structure-function relationships that are used to interrogate the structural and genomic databases, giving predictions of protein redox activity, analysis of enzyme catalytic rate enhancement, and estimation of pH-dependence in both the folded and unfolded states. The Figure shows interactions with the dipole field of the modelled catalytic transition state of a phospholipase.

Models are now suitable for application to energy transducing systems, such as the molecular complexes of respiration and photosynthesis. We have also made predictions for various properties of prion proteins (PrPs), particularly pH-dependence of the C-terminal folded domain and the influence of an adjacent membrane. These have been linked to experimental collaborations, providing experimental design in collaboration with the partner groups. A broader interest concerns the molecular determinants of specificity and affinity for self-aggregating proteins and peptides across neurodegenerative diseases, and the implications for potential therapeutic agents.

Funding:

BBSRC, Wellcome Trust, UKIERI