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In silico approaches to enable optimisation of small molecule binding by perturbing and interacting with water networks.

  • Full or part time
    Dr S Hoelder
    Dr M Meniconi
  • Application Deadline
    Sunday, November 17, 2019
  • Funded PhD Project (UK Students Only)
    Funded PhD Project (UK Students Only)

About This PhD Project

Project Description

The Institute of Cancer Research, London, is one of the world’s most influential cancer research institutes. We are committed to attracting and developing the best minds in the world to join us in our mission—to make the discoveries that defeat cancer.

In silico approaches to enable optimisation of small molecule binding by perturbing and interacting with water networks.

Project Description:
When small molecules bind to proteins they perturb a network of water molecules present in the unbound state of the protein. For example, some water molecules will be replaced, others will engage in interactions with the small molecule. This perturbance of the water network fundamentally affects the overall free binding energy of drug binding. Despite this fundamental effect, its contributions to and effect on the overall binding affinity of the small molecule remain incompletely understood. This incomplete understanding limits the predictive power of structure-based design approaches e.g. when designing ligands for unoccupied pockets and apo structures.
The overall aim of this PhD project is to make contributions to the understanding of how interfering with water networks affects the thermodynamics of small molecule binding. To achieve that, we will initially select a drug / target system where the water network in the apo as well as in the ligand bound form of the protein are well characterised through high-resolution crystal structures. We will use different in silico tools to calculate the binding free energy of key water molecules both in the apo and drug bound form to assess to which extend this change in the water network affects the overall binding energy. We will complement these predictions with isothermal calorimetry (ITC) measurements to determine thermodynamic footprint of key binders. We will then combine the small molecule SAR, the predictions of the binding free energy of key water molecules, crystal structure information and the ITC measurements to propose a quantitative model of drug binding to this particular protein that includes the perturbation of the water network.
After completing this first stage of the project, there are a number of alternative ways to continue the project. Which one we will select will depend on the results of the first stage but also on the preference and the research interests of the student. One option is to use the insights from the first stage to design new compounds that have the potential to interact with the water network in a different way. Another option is to apply more sophisticated (quantum mechanics) tools to deepen the understanding of the tightness of the water network and rationalise the experimental results. Finally, the analysis can be extended to additional proteins and the use to machine and deep learning algorithms.

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 and benefit from the significant experience in drug design and medicinal chemistry in both teams. In addition, the student will have an industrial supervisor at Astra Zeneca and will have the opportunity to do some of this research within the Astra-Zeneca computational chemistry group at their research site.
Learning outcome: The student will gain detailed expertise in many aspects of computational chemistry and drug design with a particular emphasis on structure based design and methods that allow the characterisation contribution of water molecules. In addition, the student will have the opportunity, gain insights and experience in some of the following areas: selected experimental methods to characterise drug-target binding, docking and pharmacophore modelling, more sophisticated computational chemistry techniques (e.g. molecular dynamics and Quantum mechanics), machine and deep learning techniques and organic syntheses.

Keywords /Subject Areas:
Drug design
Molecular Modelling
Computational chemistry
Medicinal chemistry
Cancer Therapy

Funding Notes

Stipend, currently £21,000 per annum, tuition fees and project costs paid for the four-year duration. To be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship. Please see the MRC residency requirements for further information.

See to apply
Applications close 11:55pm UK time on Sunday 17th November 2019
Candidates must have a first class or upper second class honours BSc Honours/MSc in chemistry or computational science.

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