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A molecular simulation and machine learning framework for the rational discovery of allosteric modulators of protein function

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

Project Description

Applications are invited for a PhD studentship in the Michel lab (http://www.julienmichel.net) in the area of biomolecular simulations and computer-aided drug design. The EaStCHEM school of Chemistry at the University of Edinburgh is among the top ranked departments within the EU.

This project will focus on developing a computational methodology that combines molecular simulation, information theory and machine learning methods for predicting how the binding of drug-like small molecules to different locations on the surface of a protein will modulate the biological function of the protein. Such so-called allosteric modulators are of particular interest to tackle challenging drug targets. The computational methodology will be applied to compounds binding to pharmaceutically important enzymes or protein-protein interactions. We are particularly interested in characterising the potential of ‘hit’ molecules, weak binders typically identified at the early stage of a drug discovery campaign by fragment screens, to be developed into potent allosteric modulators. The work will build on molecular dynamics simulation and free energy calculation methodologies the Michel lab has recently used to elucidate allosteric effects in proteins (Chem. Commun. 2019), and to guide rational drug design efforts (Chem. Sci. 2019). The project will be carried out in collaboration with the biopharmaceutical company UCB and involve placements at their R&D site. This is an exciting opportunity to develop, validate and apply next-generation computer-aided drug design software and methodologies. Upon completion of the studentship, the successful applicant will have gained strong technical expertise in molecular modelling and learned to work closely with the pharmaceutical industry sector. This will prepare him or her well for a future career in academia or industry.

Applicants with an excellent academic record in a chemistry/biochemistry/physics are encouraged to apply. The ideal candidate will have: interest in computer programming (Python) and evidence of strong programming abilities, strong knowledge in physical chemistry and/or biophysical chemistry; relevant research experience; excellent written and oral communication skills; enthusiasm for rational drug design, computational chemistry and scientific computing.

Applications will be considered until an excellent candidate has been identified. Candidates should normally be UK resident, with or about to obtain a 2.i or 1st class degree in a relevant discipline. EU candidates may be considered, provided they demonstrate an outstanding academic record (within top 5% of your class) and strong written/spoken English language skills.
To apply, please submit initially by email a CV, covering-letter describing your previous research experience, reasons to apply and justifying your eligibility, as well as the names and email address of two referees in pdf format to Dr. Julien Michel . Informal enquiries are encouraged.

The School of Chemistry holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. The University is a member of the Race Equality Charter and is a Stonewall Scotland Diversity Champion, actively promoting LGBT equality. The University has a range of initiatives to support a family friendly working environment. See our University Initiatives website for further information. University Initiatives website: https://www.ed.ac.uk/equality-diversity/help-advice/family-friendly.

Funding Notes

The studentship is fully funded for 42 months and covers tuition fees and an annual stipend (starting at £15,009 per annum) for a candidate satisfying EPSRC criteria:
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How good is research at University of Edinburgh in Chemistry?
(joint submission with University of St Andrews)

FTE Category A staff submitted: 43.30

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

Click here to see the results for all UK universities

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