For a number of years I have been working on methods for validating computational models of structures [see ‘Model validation‘ on September 18th 2012] using the full potential of measurements made with modern techniques such as digital image correlation [see ‘256 shades of grey‘ on January 22nd 2014] and thermoelastic stress analysis [see ‘Counting photons to measure stress‘ on November 18th 2015].  Usually the focus of our interest is at the macroscale, for example the research on aircraft structures in the MOTIVATE project; however, in a new PhD project with colleagues at the National Tsing Hua University in Taiwan, we are planning to explore using our validation procedures and metrics [1] in structural biology.

The size and timescale of protein-structure thermal fluctuations are essential to the regulation of cellular functions. Measurement techniques such as x-ray crystallography and transmission electron cryomicroscopy (Cryo-EM) provide data on electron density distribution from which protein structures can be deduced using molecular dynamics models. Our aim is to develop our validation metrics to help identify, with a defined level of confidence, the most appropriate structural ensemble for a given set of electron densities. To make the problem more interesting and challenging the structure observed by x-ray crystallography is an average or equilibrium state because a folded protein is constantly in motion undergoing harmonic oscillations, each with different frequencies and amplitude [2].

The PhD project is part of the dual PhD programme of the University of Liverpool and National Tsing Hua University.  Funding is available in form of a fee waiver and contribution to living expenses for four years of study involving significant periods (perferably two years) at each university.  For more information follow this link.

References:

[1] 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.

[2] 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.

Image: A diffraction pattern and protein structure from http://xray.bmc.uu.se/xtal/