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EASTBIO Development of data-driven methods for de novo design of novel enzymes


   School of Biological Sciences

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  Dr C Wood, Dr A Jarvis  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

De novo protein design is quickly becoming a viable strategy for creating novel protein structures, especially given recent advances in structure prediction using deep-learning based methods such as AlphaFold [1]. However, it remains highly challenging to add complex functionality to these molecules [2]. While there has been some success in designing novel enzymes, their enzymatic activity falls short of most natural systems, making it necessary to perform directed evolution to improve activity [3]. In nature, cofactors are often incorporated into proteins to add a vast array of functionality, and so they offer an attractive route to create highly-active enzymes.

This project aims to develop novel methods for designing proteins that incorporate cofactors. These tools will build on existing technology developed in the Wood lab, that utilises structural analysis and machine learning to produce and evaluate novel-protein sequences [4,5], supported by the Jarvis Lab who are experts in the design of artificial enzymes [6]. Throughout the PhD, the student will develop data-driven methods to design and understand sequences that bind cofactors that have applications in photochemistry. If realised, these proteins will have a transformational impact in the field biocatalysis.

This project is primarily computational, although there may be some opportunity to perform experiments in the lab. While advantageous, experience in programming/machine learning and/or statistics is not required. We are adept at training people in these areas and the student will be well supported. All that is required is enthusiasm and determination to learn these skills.

The student that takes on this project will form part of a larger cross-institutional team with the Universities of Manchester and Bristol, and there will be opportunities to spend some time in these institutions during course of the PhD.

https://www.wellswoodresearchgroup.com/

https://twitter.com/ChrisWellsWood

https://www.amandajarvis.co.uk/

The School of Biological Sciences is committed to Equality & Diversity: https://www.ed.ac.uk/biology/equality-and-diversity

How to Apply 

The “Institution Website” button will take you to our online Application Checklist. From here you can formally apply online. This checklist also provides a link to EASTBIO - how to apply web page. You must follow the Application Checklist and EASTBIO guidance carefully, in particular ensuring you complete all the EASTBIO requirements, and use /upload relevant EASTBIO forms to your online application. 


Funding Notes

This 4 year PhD project is part of a competition funded by EASTBIO BBSRC Doctoral Training Partnership http://www.eastscotbiodtp.ac.uk/how-apply-0
This opportunity is open to UK and International students and provides funding to cover stipend at UKRI standard rate (£17,668 annually in 2022) and UK level tuition fees. The fee difference will be covered by the University of Edinburgh for successful international applicants, however any Visa or Health Insurance costs are not covered. UKRI eligibility guidance: Terms and Conditions: https://www.ukri.org/wp-content/uploads/2020/10/UKRI-291020-guidance-to-training-grant-terms-and-conditions.pdf International/EU: https://www.ukri.org/wp-content/uploads/2021/03/UKRI-170321-InternationalEligibilityImplementationGuidance.pdf

References

[1] Jumper J et al (2021) Highly accurate protein structure prediction with AlphaFold, Nature.
[2] Dawson WM et al (2019) Towards functional de novo designed proteins, Current Opinion in Chemical Biology.
[3] Obexer R et al (2017) Emergence of a catalytic tetrad during evolution of a highly active artificial aldolase, Nature Chemistry.
[4] Stam MJ and Wood CW (2021) DE-STRESS: A user-friendly web application for the evaluation of protein designs, Protein Engineering, Design and Selection, 34.
[5] O’Shea JM et al (2022) Generation of photocaged nanobodies for in vivo applications using genetic code expansion and computationally guided protein engineering, ChemBioChem.
[6] Jarvis SG (2020) Designer metalloenzymes for synthetic biology, Current Opinion in Chemical Biology.

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