Predictive simulations of molecules in membranes

This computational project will tackle fundamental questions in physical chemistry that are also of great industrial significance. The four-year studentship is funded by an industrial CASE (iCASE) award involving Unilever and EPSRC. The project builds on an existing partnership between Unilever and the Department of Chemistry at Durham University. Candidates should have strong background in computational chemistry, especially molecular simulation. Programming skills are also highly desirable.

The partitioning of a molecule between aqueous solution and lipid bilayers is quantified by the logarithm of its membrane-water partition coefficient log K_MW. This quantity is used in risk assessments for the formulation of household products to estimate tendency for passive partitioning through cell membranes and absorption in skin and organisms. However, accurate measurements of log K_MW are challenging and time-consuming. Moreover, membranes differ in composition (for example, cholesterol content), which affects the interactions with a given solute and multiplies the task of characterisation.

Predictive computer simulations are an attractive alternative to experimental measurement. This approach is challenging too; explicit simulations with all-atom resolution are prohibitively slow for high-throughput screening of many solutes in different membranes. The aim of this project is to develop systematic methods for simulating the interactions of solutes with membranes using coarse-grained (CG) simulations. CG models work at a carefully chosen lower level of resolution than all-atom simulations, while preserving physical properties as quantitatively as possible. We will exploit the latest developments in CG simulation to work with a wide chemical space and complex membrane compositions. As well as making quantitative predictions of log K_MW, the methods will be applied to study membrane-mediated interactions and will be useful to the wider scientific community in any field where CG modelling is needed.

The award includes funds for travel to national and international conferences. The successful candidate will also spend a total of three months on site at Unilever's site in Colworth, to establish and benefit from networks within the company.

Durham University has particular strengths in computational chemistry and soft matter, hosting the Durham Centre for Soft Matter and an EPSRC Centre for Doctoral Training in soft matter (SOFI²) together with the Universities of Leeds and Edinburgh. Durham's Chemistry Department was ranked first in the UK for the impact of its research in the most recent national Research Excellence Framework (REF 2014). The University's collegiate system offers all students further opportunities for interdisciplinary and extracurricular activities. Durham itself is a picturesque medieval city in northeast England, centred on a World Heritage Site consisting of the 11th century Castle (now part of the University) and Cathedral.

Unilever’s Safety and Environmental Assurance Centre (SEAC) plays an essential part in ensuring that Unilever's products are safe and that its business is environmentally sustainable. SEAC’s world-class reputation for safety and sustainability science plays a key role in Unilever achieving its purpose, by working across the business to build safety and environmental sustainability at all levels. Unilever are committed to safety without animal testing and are leaders in non-animal safety science.

Eligibility: Full fees and stipend may be awarded to both UK and non-UK students, subject to a cap on the number of non-UK students overall. Applications from non-UK candidates are therefore welcomed and encouraged. Apply here using course code F1A001. Informal enquiries should be directed to m.a.miller@durham.ac.uk.

Deadline for applications: 19 March 2021