Designing modular proteins by Dr. Fabio Parmeggiani
- Zoom link: https://oist.zoom.us/j/97836093052?pwd=REtPS1o1QStOUFppYng1QTVuU2RMZz09
- Meeting ID: 978 3609 3052
- Passcode: 319741
Speaker: Dr. Fabio Parmeggiani, University of Bristol
Title: Designing modular proteins
Advances in computational methods allow, nowadays, the design of novel proteins not observed in Nature. However, design methods are usually limited to small proteins and symmetric systems, without the possibility to define large-scale structures with custom shapes.
Therefore, we developed ELFIN1,2, a computational approach for design of custom proteins. It enables users to build protein structures with specific shapes, using experimentally validated repeat protein units3 as modular, compatible and rigid building blocks. Similar to DNA nanostructure design tools, we define a three-dimensional target shape and find the combination of building blocks that matches the target most closely.
We have used ELFIN to design custom structures and understand how building blocks properties can affect the overall structure and dynamics.
The goal is to provide a computational platform for rapid and reliable design of protein nanostructures that can self-assemble into signalling scaffolds, nanoparticles with custom shape and novel bio-materials.
(1) Yeh, C.-T.; 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. https://doi.org/10.1016/j.jsb.2017.09.001.
(2) Yeh, C.-T.; Obendorf, L.; Parmeggiani, F. Elfin UI: A Graphical Interface for Protein Design With Modular Building Blocks. Front. Bioeng. Biotechnol. 2020, 8. https://doi.org/10.3389/fbioe.2020.568318.
(3) Brunette, T. J.; Parmeggiani, F.; Huang, P.-S.; Bhabha, G.; Ekiert, D. C.; Tsutakawa, S. E.; Hura, G. L.; Tainer, J. A.; Baker, D. Exploring the Repeat Protein Universe through Computational Protein Design. Nature 2015, 528 (7583), 580–584. https://doi.org/10.1038/nature16162.