Seminar

Since the beginning of the informatics revolution, major effort has been put in developing reliable mathematical and physical computational models of complex systems at different resolutions. In bottom-up approaches, the aim is to establish models based on sound physical principles that are able to predict the behaviour of the systems of interest. Even though, thanks to large-scale and optimized computational facilities, atomistic simulations can sometimes deal with systems as large as millions of atoms, and for simulation times reaching up to the millisecond, several biological processes involving large macromolecular complexes require description at time an sizes that go beyond even such dimensionalities. In this seminar, I will present Coarse-Grained [1] and multi-scale computational strategies [2] aimed at reducing the intrinsic complexity in modelling biological systems. Specifically, I will introduce recent advances in coarse-grained modelling for proteins, and their coupling with linear-scaling hybrid particle-field approaches. These models make it possible to simulate tens of millions of atoms or more for several milliseconds already on routinely accessible computational architectures, promising a critical contribution toward the direct in silico representation at the molecular scale of complex in vivo phenomena.

References
[1] M Neri et al. Phys. Rev. Lett. 2005, 95, 218102; M Cascella et al. J. Chem. Theory Comput. 2008, 4, 1378; D Alemani et al. J. Chem. Theory Comput. 2010, 6, 315; E Spiga et al. J. Chem. Theory Comput. 2013, 9, 3515.
[2] G Milano et al. Phys. Biol. 2013, 10, 045007.