• University of Southampton Featured PhD Programmes
  • University of Stirling Featured PhD Programmes
  • University of Manchester Featured PhD Programmes
  • Northumbria University Featured PhD Programmes
  • University of Bristol Featured PhD Programmes
  • Queen’s University Belfast Featured PhD Programmes
  • University of Surrey Featured PhD Programmes
  • University of Glasgow Featured PhD Programmes
University of Bristol Featured PhD Programmes
University of Liverpool Featured PhD Programmes
University of Leicester Featured PhD Programmes
ESPCI Paris Tech Featured PhD Programmes
University of Reading Featured PhD Programmes

Towards Fundamental Understanding Of Alzheimer’s Disease By Molecular Simulation

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Alzheimer’s disease1 challenges our society with an annual estimated cost of $1 trillion in the United States alone by 2050. This disease is a progressive irreversible neurological disorder with marked atrophy of the cerebral cortex. This disorder is pathologically characterized by accumulation of amyloid plaques. The major constituents of these plaques are amyloid β peptides of about 40 amino acids long. Dimers, trimers, and 12-mers of these peptides are the most critical players in the pathology of Alzheimer’s disease.

Only five drugs are available for Alzheimer’s disease but they only slow it down by 6-12 months and are only effective for half of the patients. Sustainable progress towards an effective cure can only happen if we fundamentally understand the nucleation-condensation polymerisation mechanism at the root of this disease.

Crucial progress on Alzheimer’s disease is hampered at the (i) experimental and (ii) computational front:
• First, kinetic experiments do not provide any information on the three-dimensional topology and size of the primary nucleus. Overall, probing of the conformational changes of the amyloid β aggregation is challenging because of the enormous heterogeneity of the aggregates and many other factors. Secondly, the standard tools of structural biology have failed to provide the three-dimensional structures of the monomers and the oligomers of amyloid β. Due to their heterogeneity and high propensity to aggregate, amyloid β oligomers are not amenable to NMR and X-ray crystallography. As a result, only low resolution structural data available from other techniques (CD, IM-MS, EM, TEM and AFM) can be used.

• Experimental studies alone are not sufficient because they generally give time- and space-averaged properties. Computer simulations must complement experiments by exploring different time and length scales. The inherent flexibility, heterogeneous ensemble of the amyloid β monomers and oligomers, and the impact of a crowded environment require improved sampling techniques. Secondly, the results obtained in simulations of intrinsically disordered proteins (i.e. amyloid β) strongly depend on the force field used to describe the energy of the peptide and their interactions with the aqueous solvent. Simulations with four different all-atom force fields were found to adopt substantially different hydrogen bonds, secondary structure tendencies, etc.

The experimental validation of the ensembles produced by classical force fields, for the unfolded states of intrinsically disordered proteins, remains essentially an unsolved problem. The proposed project has the long- term goal to solve this problem. The way forward comes from Quantum Chemical Topology (QCT)2, which partitions electron density into atoms, without parameters (see example of threonine in Figure). Each atom is a box with a particular shape that responds to environment. Atomic properties such as charge, dipole moment, volume and intra/inter-atomic energies can be computed. Over the last eight years, a novel and rigorous peptide force field3 called FFLUX has been developed in our lab from scratch, specifically aimed at peptides, and is now ready to be used in conjunction with experiment. FFLUX has a better prospect to make the right predictions, for the right reasons, because it perceives the structure of peptides as an interplay of four fundamental energy contributions at atomic level, captured by the machine learning method kriging.

Qualifications
Applicants should have or expect a good II(i) honours degree (or an equivalent degree) in Masters Chemistry or Physics. The project is purely computational without tapping into mathematical skills or programming. If you have those skills then that is a bonus but it is not necessary. If you wish to develop these skills then this can be taken care of. However, the project requires the efficient and correct running of existing computer programs and a systematic analysis of the data generated.

Contact for further Information
For general admission information, please email: .

Informal inquiries about the project should be sent to Prof. Paul Popelier by email (). Please note that to apply for this studentship you must submit the relevant information via the University’s online application form.

Funding Notes

Applications are invited from self-funded students or students who have funding in place and require an offer or to secure funding e.g. CONACyT require an offer. For UK/EU tuition fees are £8250 and International are £24,000 for 2017/18 academic year.

References

1. J. Nasica-Labouze, et al., Chem.Rev., 2015, 115, 3518−3563.
2. P. Popelier, in The Nature of the Chemical Bond Revisited, eds. Frenking & Shaik, Wiley-VCH, Ch. 8, 2014, p. 271-308.
3. P. L. A. Popelier, Int.J.Quant.Chem., 2015, 115, 1005–1011.

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully




Cookie Policy    X