NGCM-20: Simulation of biological systems at long length and distance scales
Biological systems and processes are notoriously complex and difficult to understand. They span distance scales across nine orders of magnitude ranging from individual small molecules (1 nm) to whole organisms (1 m), and times scales of 21 orders of magnitude from individual bond breaking in an enzyme (1 ps) to the human lifetime (2 Gs). While there are many computer modelling approaches available to understand a particular length and timescale, the seamless linking of these methods remains an unsolved challenge. This PhD project will work to address this problem at the molecular level, with a particular emphasis on solving real biological problems.
The types of problem we are seeking to address include modelling large-scale self-assembly of biological membranes, how membrane composition affects the biological function of embedded proteins, how changes in protein conformation regulate protein function, particularly in the context of protein-protein interactions, and how seemingly simple changes in pH or ionic concentration affect membranes, proteins and DNA. We have long-standing collaborations with the pharmaceutical industry, and linking drug discovery to solving these problems is a big target for us.
To address these challenges we will take two broad approaches. The first involves combining different scales of model in either separate or combined simulations. This is so-called multiscale modelling. The second involves finding approaches to accelerate slow events in our simulations, so-called enhanced sampling methods. Ultimately we wish to combine strategies. In both approaches we will build on our existing experience. For example, we have developed multiscale models of biological membranes allowing us to simulate drug permeation through these important cellular barriers. Extending these models to include whole-proteins in mixed component membranes is underway. To enhance sampling in proteins, we have developed an approach to increase the velocities of low-frequency vibrations. This is effectively frequency-dependent heating, and has been shown to significantly improve the sampling of flexible loops. In this PhD project you will further develop and extend these and related methods, to target specific biological problems.
Applicants should have a good undergraduate degree in chemistry, physics or biochemistry, and a keen interest in developing and applying computational methods to biological problems.
If you wish to discuss the project informally, please contact Jon Essex at firstname.lastname@example.org
This project is run through participation in the EPSRC Centre for Doctoral Training in Next Generation Computational Modelling (http://ngcm.soton.ac.uk). For details of our 4 Year PhD programme, please see
To apply for this project please visit http://www.ngcm.soton.ac.uk/apply.html
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