Title: Viruses, polytopes and machine learning

Speaker: Pierre Dechant (York St John)

Time: 10:00-10:35 (GMT+0), 2021.08.10

Abstract:

Viruses are a prime example of symmetry in nature. Polyhedra and related concepts such as Hamiltonian paths are a useful framework for modelling various aspects of virus structure and assembly. I will give an overview of how these occur in the structure of viruses and fullerenes, and how similar design principles can be used for the artificial construction of nanocages. Recent research has shown an assembly mechanism by which RNA can be cooperatively involved in the assembly of the viral shell. A toy model of the underlying biophysical effects and RNA feature space has been exhaustively explored using supercomputer simulations. Yang-Hui He and I have recently shown that this assembly fitness space can be machine learnt very quickly, hinting at some deeper structure hidden in the simulations results.