07.20.21 - Elin Barrett: Computational Methods for Next-Generation Risk Assessment of Consumer Goods
13 Jul 2021





​Elin Barrett, Unilever, UK

Host: Alin Elena - this seminar is part of CCP5 Summer School (summer2021.ccp5.ac.uk)


Tuesday 20th July 2021 at 16:15-17:15

Zoom Link: https://ukri.zoom.us/j/95492111635

Computational Methods for Next-Generation Risk Assessment of Consumer Goods

​​An understanding of passive partitioning through cell membranes is critical to the safety assessment of chemicals. There is growing evidence that partitioning parameters such as membrane-water (KMW) can describe the interactions of polar, charged, amphiphilic or surface-active compounds where other parameters such as octanol-water partitioning (KOW) fail.

However, accurate laboratory measurement of membrane-solute interactions is challenging and time-consuming.  Moreover, membranes differ in composition (e.g. 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.  Simulations that represent all atoms explicitly are too slow for such complex systems, but coarse-grained models, which work at a judiciously chosen lower level of detail, can bridge the gap.  Coarse-grained modelling is often utilised to study biological systems, as it decreases the degrees of freedom of the system, allowing for access to larger systems and timescales. A largely automated workflow for running coarse-grained simulations for neutral and ionisable molecules has been developed in partnership between Unilever and Durham University. The method uses freely available, open-source tools to parametrise a coarse-grained model of a solute, run a series of simulations, and analyse the results to obtain log KMW.

This presentation gives an overview of existing computational methods used to predict log KMW and shows how the coarse-graining approach can be successfully applied to a diverse range of molecules. 

Contact: Lomas, Georgia (STFC,DL,SC)