Parameterizing out the complexity in multi-scale description of biomolecular systems

Eric Jakobsson (UIUC), Sagar Pandit (Purdue University), See-Wing Chiu (UIUC), and Larry Scott (IIT)

The key to understanding mechanism in biological systems is the ability to relate large scale phenomena to microscopic physics. The chain of inference to make that relationship requires describing the system at multiple levels of temporal and spatial resolution, with statistically valid coarse-graining connecting the levels. We present one example of such a chain of inference, namely domain formation and phase relationships in biological membranes. The chain of inference starts with electronic structure calculations to determine force fields for atomically detailed molecular dynamics simulations, which in turn are used to generate parameters for Mean Field Langevin Dynamics simulations that can accurately reproduce domain formation and phase transitions in membranes. The long-term goal of the work is a computing paradigm for the self-assembly of multimolecular complexes.