Computational microbiology: Where is artificial intelligence addressing the barriers to large-scale simulations of
Robert Clark, Iain Peter Shand Smith, James Gebbie-Rayet1
1Scientific Computing Department, Science and Technology Facilities Council, Daresbury Laboratory, Warrington, UK.
Abstract:
Molecular dynamics simulations allow the investigation of the time-resolved mechanics of large, complex biological systems such as the Gram-negative bacterial cell envelope. Such simulations pose challenges due to their chemical diversity and crowded environments. We review artificial intelligence-based approaches that can support simulations of large biological systems, focussing on trajectory analysis and propagation whilst highlighting the difficulties of feature representation. Integrating trajectory analysis and propagation is powerful, but we also consider the serious data and resource requirements involved. In this context, we summarise the current state of cell envelope simulations and then ask a practical question: where can such approaches be applied to understand these crowded, chemically diverse environments?
