Proteins perform most of the functions in biological systems, from structural support, to movement, communication and catalysis. Our goal is to use modular building blocks to quickly and precisely design novel protein nanomaterials and nanoparticles to control cell behaviour.
We focus on the development of computational and experimental methods for the rapid design of custom structures to be used as protein binders, functional nanomaterials and biosensors, and to become future research, diagnostic and therapeutic tools.
Our work relies on computational protein design, using mainly the Rosetta modelling suite (www.rosettacommons.org) and the Elfin package (https://github.com/joy13975/elfin
) that we have developed. With an approach similar to LEGO® blocks, we combine protein modelling with structural biology and functional assays, going from design concepts to experimental validation.
The student will have the opportunity to work in one or more of our research areas, in partnership with our collaborators, from engineering to cell biology:
- Development of computational design approaches
- Library design and assembly methods
- Automation and high throughput design
- Structural biology: crystallography, electron microscopy, small angle x-ray scattering, atomic force microscopy
- Designing scaffolds for receptor clustering and control of cell proliferation and differentiation
- Design of protein nanomaterials and composites
Candidates with an interest in protein design, either from a theoretical/computational background (no previous biochemistry knowledge required) or experimental background (no programming skill required, but helpful), are invited to apply or get in touch for more information.
e-mail: [email protected]
web page: http://www.bristol.ac.uk/brissynbio/people/fabio-parmeggiani/index.html
1) Parmeggiani F, Huang PS. Designing repeat proteins: a modular approach to protein design. Curr. Opin. Struct. Biol. 45 (2017) 116-123
2) Yeh CT, Brunette T, Baker D, McIntosh-Smith S, Parmeggiani F. Elfin: An algorithm for the computational design of custom three-dimensional structures from modular repeat protein building blocks. J. Struct. Biol. (2018) 201(2):100-107
3) Brunette T, Parmeggiani F, Huang PS, Bhabha G, Ekiert DC, Tsutakawa SE, Hura GL, Tainer JA, Baker D. Exploring the repeat protein universe through computational protein design. Nature (2015), 528, 580-584