Petr Šulc’s research focuses on application of computational modeling and statistical physics approaches to complex systems. In particular, his group uses computational models to study problems in biology, and bio-inspired nanotechnology systems. He is mainly interested in nucleic acids modeling (DNA and RNA) using coarse-grained models, which allow for simulations of longer time-scales and larger systems than if fully-atomistic representation is used. Such an approach is allows for efficient studies of nanotechnology system, as well as biologically relevant interactions between nucleic acids...
The ideal construction method for nanotechnology is to get the components to assemble themselves on a molecular level, as opposed to building a device to assemble nanomachines. Nature does this all the time, but it is quite difficult and nature has had billions of years to design pieces that self assemble. RNA and DNA are useful self-assembling structures but lack simulation software for rapid design and testing.
Current leading software engines for nanotechnology design have several disadvantages including the inability to simulate very long timescales. His solution, OxDNA, creates coarsegrained simulations of DNA self-assembly to speed up simulations by many orders of magnitude. His software simulates large constructs of DNA nanocrystals and DNA origami, and is the only model that can reproduce strand displacement reactions on reasonable timescales.
Petr has developed an entire ecosystem around the simulation software to allow for viewing, designing, sharing, and simulation for proteins.
Self assembly of cubic diamond lattices is currently impossible but may have huge applications for light computation
Petr wants people to contribute to the development of OxDNA ecosystem and make it community driven