Computational Modelling Group

Christopher Cave-Ayland

Position
Postgraduate Research Student
Institution
Electronics and Computer Science (FPAS)
E-mail
cica1v07@soton.ac.uk
Contact
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With a background in biomedical sciences I am interested in the biological applications of modelling proteins, and their interactions with ligands in the context of pharmaceutical applications. The final focus of my thesis is still undetermined however will likely focus on one of two following areas.

Firstly the modelling of protein-ligand interactions with the aim of expediting the production of pharmaceutically active compounds. This essentially represents an optimisation problem whereby the correct orientation and position of the ligand with respect to the protein binding site is sought to find the lowest energy state. Additional degrees of freedom are introduced through conformational flexibility of the ligand molecule and the protein binding site making the search space voluminous and difficult. This is well covered ground with clearly defined limitations and methodologies however it is hoped that applying insights from complexity science may suggest powerful approaches from different fields that can be applied to this problem.

The second avenue of research may involve examining how oncogenic mutations in intracellular kinases can alter conformational equilibria, leading to inappropriate kinase activity that leads to the activation of signalling pathways associated with cell growth and division. Comprehensive databases are available cataloguing mutations associated with cancers. The study of conformational changes through molecular modelling is impeded by the long time scales over which modelling must be carried out How different mutations give rise to conformational changes is still poorly understood, especially in cases where mutations lie in regions not overtly associated with regulating protein activity. Understanding the effects of these mutations and how to stabilise the inactive conformations may provide novel therapeutic targets. With the approach of individualised cancer therapies based around detecting specific mutations within patients and tailoring treatments appropriately the ability to understand the effect of individual mutations on different proteins will be increasingly important.

Overarching the biological and pharmaceutical applications of this work are the fundamental methodologies used in molecular simulations. I am interested in the methodological issues surrounding the modelling of large biological molecules. Thus I am interested in developing and/or extending the methodologies employed in the modelling of these systems in the context of complexity science.

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