About the Project
The overall aim of this project in collaboration with Astra Zeneca is to explore cutting edge computational chemistry techniques to 1) improve our understanding of how perturbing a water network affects the potency of small molecule binding and to 2) use these insights to improve our ability to design potent binders. The computational methods that we will explore include MD simulations, structure based design tools and deep learning algorithms. We will complement the computational methods with assay techniques such as biochemical assays and ITC to experimentally assess the effect of perturbing water networks and validate our predictions. There is also the opportunity to design and synthesise new ligands either as part of this project or in collaboration with other scientists at the ICR.
We will initially explore two approaches. In the first approach, we focus on a drug / target system where the water networks in the unbound as well as in the ligand bound form of the protein are well characterised through high-resolution crystal structures. We will use these crystal structures to observe the changes that drug binding causes to the network of water molecules in the binding site. We will then explore different computational methods to calculate the effect of this change on the overall binding energy and validate these predictions using experimental data. We will incorporate these findings into the design of alternative inhibitors.
In the second part of the project, we will establish a database of high-resolution structures of different proteins with binding site water networks and explore machine and deep learning techniques to derive predictive models for these perturbations.
Project environment: The student will be situated both in the Medicinal Chemistry Team 4 as well as in the in silico chemistry team at the CRUK Cancer Therapeutics Unit at The ICR and benefit from the extensive experience in drug design and medicinal chemistry in both teams and the collaborative environment. In addition, Dr Mike Bodnarchuk from Astra Zeneca will be part of the supervisory team and contribute his extensive expertise in water modelling to the project. Moreover, the student will spend time within the Astra-Zeneca computational chemistry group at their research site.
Learning outcome: The student will gain detailed expertise in many aspects of computational drug design and deep learning with a particular emphasis on structure based design and methods that allow the characterisation contribution of water molecules. The project is primarily computational but the student will have the opportunity to gain insights in experimental techniques such as biochemical assays and organic syntheses.
For details on how to apply using our online recruitment portal please see icr.ac.uk/phds. Please note we only accept applications via the online application system apply.icr.ac.uk
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