Mathematical modelling of epistasis in proteins using network analysis and statistical learning
Proteins are biopolymers composed of repetitive units (residues) from a set of 20 amino acids that form complex three-dimensional topologies. Protein topologies/structures undergo conformational changes over picosecond to millisecond timescales.
These changes are important for biological function and arise from inter and intra residue interactions and interactions with the solvent. These conformational changes can be modelled, using computer simulations and well-established software, generating millions of 3D structures that are saved as time-dependent trajectories.
To design proteins for novel functions or enhance their existing biological activity, advances in computational protocols for protein design are desired. Towards this goal, understanding the epistasis at the protein level, i.e. networks of synergistic interactions between residues that contribute to the function is the first step.
In this project, using the molecular dynamics simulations and sequence analysis data of a test protein system, the doctoral researcher will
develop a mathematical formalism to analyse the complex network of interactions between the protein residues using time series network analysis, which can handle multiple densities of states;
use graph convolutional networks to learn and predict effects of mutations on structural dynamics contributing to biological function
Integrate this method to select design sites into our computational protocol for the selection of design sites.
The ideal candidate will have BSc and/or MSc degree in mathematics and/or computer science. Knowledge of C/Python and R will be highly desirable.
How to apply
If you are interested in applying for the above PhD topic please follow the steps below:
- Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
- Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
- Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.
This is a self funded topic
Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.