• Aberdeen University Featured PhD Programmes
  • University of Pennsylvania Featured PhD Programmes
  • Staffordshire University Featured PhD Programmes
  • FindA University Ltd Featured PhD Programmes
  • University of Cambridge Featured PhD Programmes
  • University of Tasmania Featured PhD Programmes
University of Tasmania Featured PhD Programmes
Norwich Research Park Featured PhD Programmes
University of Leeds Featured PhD Programmes
Imperial College London Featured PhD Programmes
FindA University Ltd Featured PhD Programmes

Computational modelling of protein-ligand binding

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (UK Students Only)
    Funded PhD Project (UK Students Only)

Project Description

The optimisation of protein-ligand interactions is a vital component in the various drug design strategies commonly employed today, including Structure Based Drug Design and Fragment Based Drug Design. One of the more sophisticated computational approaches to optimising the ligand to give improved binding affinity involves classical computer simulations combined with statistical mechanics allowing relative and absolute binding affinities to be calculated. However, such calculations are not without their difficulties. Specifically, the empirical force fields used are often inadequate to capture some of the more specific types of intermolecular interaction, and almost exclusively exclude explicit polarisation. If ligand binding is associated with changes in the number of explicitly bound waters in the protein-ligand complex, or results in significant reorganisation of the protein structure, then again current computational approaches will not reliably capture these processes.

To address these outstanding issues, the extension of classical molecular dynamics and Monte Carlo simulations is proposed. The use of empirical polarisable force fields or QM/MM methods may help address the deficiencies of existing force fields, while Grand Canonical Monte Carlo and other enhanced sampling approaches, including Hamiltonian Replica Exchange and Hybrid Monte Carlo methods, may assist in improving overall sampling and hence capture the large-scale structural reorganisations often associated with ligand binding events.

In this project, these sophisticated simulation approaches will be further developed and applied in the context of protein-ligand binding. Specific emphasis will be placed on the use of these methods on systems of current pharmaceutical interest, and collaboration with the pharma industry will be used to ensure the relevance and impact of the methodology developed.

Funding Notes

The project is funded for 3 years and welcomes applicants from the UK who have or expect to obtain at least an upper second class degree in Chemistry, Physics, Biochemistry or allied subjects/relevant disciplines. Funding will cover fees and a stipend at current research council rates of £ 14,296 per annum.

Owing to funding restrictions this position is only open to UK applicants

References

Application Deadline: no deadline, position will be filled as soon as possible

Applications for an MPhil/PhD in Chemistry should be submitted online:
https://studentrecords.soton.ac.uk/BNNRPROD/bzsksrch.P_Login?pos=4990&majr=4990&term=201617#_ga=1.54988136.2120898106.1412059827

Please place Prof Jon Essex in the field for proposed supervisor/project

General enquiries should be made to Prof Jon Essex at [email protected] Any queries on the application process should be made to [email protected]

Applications will be considered in the order that they are received, and the position will be considered filled when a suitable candidate has been identified

How good is research at University of Southampton in Chemistry?

FTE Category A staff submitted: 44.80

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.
Email Sent

Share this page:

Cookie Policy    X