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Computer-aided molecular design: improved ligand docking using electronic structure and molecular dynamics simulations


Project Description

In structure-based drug design, computational modelling techniques are frequently used to predict the orientation and affinity with which a ligand binds to its protein receptor. However there are problems in the accuracy of these docking methods. With the ability to capture the subtle physics governing diverse chemical structures and interactions, quantum mechanics (QM) approaches are poised to impact computational molecular design. This project aims at developing a predictive quality approach to ligand-protein docking based on QM methods and molecular dynamics simulations.

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.

Funding Notes

This project has a Band 1 fee. Details of our different fee bands can be found on our website (View Website). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (View Website).

Informal enquiries may be made directly to the primary supervisor.

References

The application of quantum mechanics in structure-based drug design. D. Mucs, R. A. Bryce. Expert Opin. Drug Discovery 2013, 8, 263–276.
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.

How good is research at University of Manchester in Allied Health Professions, Dentistry, Nursing and Pharmacy?

FTE Category A staff submitted: 112.65

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

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