University of Leeds Featured PhD Programmes
Newcastle University Featured PhD Programmes
University of Liverpool Featured PhD Programmes
University of Huddersfield Featured PhD Programmes
Birkbeck, University of London Featured PhD Programmes

Quantitative Characterisation and Validation for Spatial-Temporal Models of Protein Structures


Project Description

This project is a part of a 4-year dual PhD programme between National Tsing Hua University (NTHU) in Taiwan and the University of Liverpool in England. It is planned that students will spend the first 18months at NTHU, followed by 18months at The University of Liverpool, with the remaining 12 months to be decided following discussion with the supervisors and successful student.
The size and timescale of protein-structure thermal fluctuations are essential to precise the regulation of cellular functions. Protein structures can be resolved using NMR and determined from diffraction patterns, such as obtained by x-ray crystallography and cryo-EM, based on electron densities. The aim of this project is to identify appropriate metrics to determine a structural ensemble for given electron densities with a defined confidence and to estimate the associated timescales. Note that for a folded protein with a defined equilibrium state (the average structure observed by x-ray crystallography), its motions can be understood as a superimposition of harmonic oscillations, each with different frequencies and amplitude [1].

It is proposed explore the use of metric developed in engineering for evaluating the prediction of structural vibrations and strain fields. The metric and its associated methodology allow fields or volumes of data to be reduced to feature vectors which can be compared to evaluate the differences between predictions from different models or between predictions and measurements. These developments have been tackled in engineering through a series of EU-funded projects involving participants from the aerospace, automotive and nuclear power industries as well as national laboratories and universities. This has resulted in a guideline for the validation of computational solid mechanics models published by Comité Européen de Normalisation [2], which provides recommendations and techniques for utilising complete data fields in the comparison of measured and predicted data. Recent work, at the University of Liverpool, has extended this work to produce a generic and probabilistic validation metric [3] that is applicable across a wide range of sciences as well as engineering and provides a probability that the predictions and measurements belong to the same population taking account of the uncertainty in the measurement data. The majority of this research has been focussed on the macro and meso scale; however, the same pattern of utilising extracted data profiles rather the complete datasets is prevalent when validating molecular dynamic simulations, for example Chen & Hub [4] and Childers & Daggett [5]. Hence, in this project the aim will be to explore the extension of these concepts to molecular dynamics simulations employed in structural biology.

Aim: To explore equivalently good alternative structural models/ensembles and the time-scales of their distributions given experimentally determined 2D/3D electron density maps using engineering approaches to data comparison and validation.

Objectives:
i. To review existing approaches to comparing measurement and simulation data in structural biology and identify knowledge gaps, needs and potential case studies;
ii. To construct an ensemble of equivalently good alternative structural models to interpret a given electron density distribution, derived from x-ray crystallography and cryo-EM, using a molecular dynamics (MD)-based sampling technique and probabilistic validation metric;
iii. To explore the application of existing ‘engineering’ processes for quantitative comparison of measurement and simulation data, and
iv. To evaluate the time-scales required for a given set of electron density distributions.
This project is part of a 4-year Dual PhD degree programme between the National Tsing Hua University (NTHU) in Taiwan and the University of Liverpool in England. As part of the NTHU-UoL Dual PhD Award students are in the unique position of being able to gain 2 PhD awards at the end of their degree from two internationally recognised world-leading Universities. As well as benefiting from a rich cultural experience, students can draw on large-scale national facilities of both countries and create a worldwide network of contacts across two continents.

The latest set of projects approved for support within the NTHU-UoL Dual PhD programme resulted from a call for proposals that targeted Goal #9 of the UN’s Global Goals for Sustainable Development [6].

When applying please ensure you Quote the supervisor & project title you wish to apply for and note ‘NTHU-UoL Dual Scholarship’ when asked for details of how plan to finance your studies.

For academic enquires please contact Eann Patterson () or Lee-Wei Yang ()
For enquires on the application process or to find out more about the Dual programme please contact

Funding Notes

Both the University of Liverpool and NTHU have agreed to waive the tuition fees for the duration of the project and stipend of TWD 10,000/month will be provided as a contribution to living costs (the equivalent of £280 per month when in Liverpool).

References

[1] Justin Chan, Hong-Rui Lin, Kazuhiro Takemura, Kai-Chun Chang, Yuan-Yu Chang, Yasumasa Joti, Akio Kitao, Lee-Wei Yang. An efficient timer and sizer of protein motions reveals the time-scales of functional dynamics in the ribosome (2018) https://www.biorxiv.org/content/early/2018/08/03/384511.
[2] Comité Européen de Normalisation, Validation of computational solid mechanics models, CWA 16799, Brussels:CEN-CENELAC Management Centre, 2014.
[3] Dvurecenska, K., Graham, S., Patelli, E. & Patterson, E.A., A probabilistic metric for the validation of computational models, Royal Society Open Society, 5:180687, 2018.
[4] Chen, P-C. & Hub, J.S., 2014, Validating solution ensembles from molecular dynamics simulation by wide-angle x-ray scattering data, Biophysical J., 107:435-447.
[5] Childers, M.C. & Daggett, V., 2018, Validating molecular dynamics simulations against experimental observables in light of underlying conformational ensembles, J. Physical Chemistry B, 112:6673-6689.
[6] https://www.un.org/sustainabledevelopment/sustainable-development-goals/

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





FindAPhD. Copyright 2005-2019
All rights reserved.