PhD: Enhancing Protein and Ligand Sampling in Molecular Simulations by Fully Adaptive Simulated Temper

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PhD: Enhancing Protein and Ligand Sampling in Molecular Simulations by Fully Adaptive Simulated Tempering (FAST)
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Qualification Type:
PhD
Location:
Southampton
Funding for:
UK Students
Funding amount:
For UK students, Tuition Fees and a stipend of £15,609 tax-free per annum for up to 3.5 years
Hours:
Full Time
Placed On:
23rd February 2022
Closes:
31st August 2022
Supervisory Team:
   Prof J.W. Essex, Dr Michael Bodnarchuk (AZ), Dr Ian Wall (GSK)
Project description
Binding free energy calculations are a widely used technique in the pharmaceutical industry to identify molecules which may be usefully developed into drug candidates. However, these methods are not always successful, and it is not obvious
a priori
which systems will perform well, and on which systems the methods will struggle. In cases where inaccurate free energies are generated, the errors may be ascribed to either inadequate sampling, or a force field which does not adequately represent the molecular interactions in the system. In this project you will address the sampling problem
Through a collaboration with AstraZeneca and GSK, we have developed a new procedure, Fully Adaptive Simulated Tempering (FAST), to address the sampling problem. While preliminary data suggest that the approach has significant promise, further validation and optimisation are required for its true potential to be known. In this project you will work in close collaboration with scientists at AstraZeneca and GSK to explore the domain of applicability of FAST, and optimise its performance.
You will spend at least 3 months of this 3 ½ year studentship working at AstraZenenca, where you will learn how computer modelling is applied to drug discovery. At the **MEMBERS ONLY**SIGN UP NOW***. you will be supervised by Prof Jonathan Essex, an expert in the development and application of computer simulation methodology to biological systems. You will also be supervised by Dr Michael Bodnarchuk (AstraZeneca) and Dr Ian Wall (GSK), both of whom are leading industrial computational chemists.
You will have a first or upper second class degree in Chemistry, Biochemistry, Physics, Engineering or Computer Science. You will have a keen interest in working outside a single discipline, possess good communication and organisational skills, and be highly self-motivated and proactive.
If you wish to discuss any details of the project informally, please contact Jonathan Essex, Computational Systems Chemistry Research Group, Email: ****, ****.
Entry Requirements
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent) in Chemistry, Biochemistry, Physics, Engineering or Computer Science.
Closing date
: applications should be received no later than 31 August 2022 for standard admissions, but later applications may be considered depending on the funds remaining in place.
Funding:
For UK students, Tuition Fees and a stipend of £15,609 tax-free per annum for up to 3.5 years.
How To Apply
Applications should be made online. Select programme type (Research), 2022/23, Faculty of Physical Sciences and Engineering, next page select “PhD Chemistry (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Jonathan Essex
Applications should include
Research Proposal
Curriculum Vitae
Two reference letters
Degree Transcripts to date
Apply online: ****For further information please contact: ****
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