About the Project
In the project, we will explore suitable QM, MM and solvent models for benchmark systems, comparing with current scoring methods. We will use our in-house software to dock ligands using QM/MM-based molecular dynamics simulations, and evaluate performance for a range of protein-ligand systems. The best protocol will then be used in guiding computational design of current protein targets within the Division of Pharmacy, with potential for experimental testing. This PhD project offers an excellent opportunity for pursuing computational chemistry research in a drug discovery context.
The successful applicant will be part of the Graduate School Training Programme (GSTP). Training will be provided in a range of computational chemistry approaches (protein-ligand docking, advanced molecular dynamics simulation techniques, QM/MM approaches), as well as related numerical methods, computer programming, statistical analysis and use of high performance computing.
This studentship offers an excellent opportunity for a gifted individual to work on a significant problem in drug discovery, supported by experts in molecular simulation and drug discovery. The candidate should have a first or upper second Bachelor of Science degree in biochemistry, chemistry, physics or a similar discipline. A familiarity with molecular modelling and computer programming ability would be useful additional experience.
Any enquiries relating to the project and/or suitability should be directed to Dr Bryce. Applications are invited on an on-going basis but early expression of interest is encouraged.
Informal enquiries may be made directly to the primary supervisor.
Free energy calculations using a swarm-enhanced sampling molecular dynamics approach. K. K. Burusco, N. J. Bruce, I. Alibay, R. A. Bryce. ChemPhysChem 2015, 16, 3233–3241.
Exploring protein kinase conformation using swarm-enhanced sampling molecular dynamics. A. Atzori, N. J. Bruce, K. K. Burusco, B. Wroblowski, P. Bonnet, R. A. Bryce. J. Chem. Inf. Model. 2014, 54, 2764–2775.
Assessment of QM/MM scoring functions for molecular docking to HIV-1 protease. P. Fong, J. P. McNamara, I. H. Hillier and R. A. Bryce J. Chem. Inf. Model. 2009, 49, 913-924.
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