Kashif-Khan, Naail (2025) Design and discovery of novel bacterial nanocompartment proteins using deep learning tools. PhD thesis, Birkbeck, University of London.
![[img]](https://eprints.bbk.ac.uk/style/images/fileicons/text.png) |
Text
Kashif-Khan N, final thesis for library.pdf Download (9MB) |
Abstract
Encapsulins are prokaryotic protein-based organelles. These icosahedral protein compartments display diverse natural functions, including mineral storage and stress responses. Encapsulins also have applications in synthetic biology, drug delivery, vaccines, and metabolic engineering. There are over 6000 known encapsulins, but only a small sample have been characterised experimentally. The work presented probes the limits of current knowledge of encapsulins via two avenues of interrogation: (1) A dataset of over 1000 novel encapsulin candidates is presented, discovered from metagenomics data using bioinformatics and deep learning tools. These novel encapsulins may display new structural features or biological functions. Three of these novel encapsulin candidates were recombinantly expressed in E. coli and one of the recombinant proteins was purified for biophysical characterisation. (2) Deep learning tools for protein structure prediction and design were applied to encapsulin proteins, to design putative encapsulins with promising physicochemical properties. A computational pipeline was used to select 48 encapsulin candidates from thousands of initial designs. The resulting recombinant proteins were investigated experimentally using laboratory automation techniques. One chimeric variant of an encapsulin from Quasibacillus thermotolerans was characterised biophysically. Overall, this work presents an account of the opportunities for the discovery or design of self-assembling protein particles and offers a synopsis of the challenges this task presents.
Metadata
| Item Type: | Thesis |
|---|---|
| Copyright Holders: | The copyright of this thesis rests with the author, who asserts his/her right to be known as such according to the Copyright Designs and Patents Act 1988. No dealing with the thesis contrary to the copyright or moral rights of the author is permitted. |
| Depositing User: | Acquisitions And Metadata |
| Date Deposited: | 13 Mar 2025 10:29 |
| Last Modified: | 05 Sep 2025 15:02 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/55153 |
| DOI: | https://doi.org/10.18743/PUB.00055153 |
Statistics
Additional statistics are available via IRStats2.
Archive Staff Only (login required)
