Relevant dynamics in macromolecular fluids is characterized by a broad range of time- (space-) scales that can exceed ten orders of magnitude: providing a complete theoretical, or computational, description of polymer dynamics is a challenging task. While atomically detailed simulations describe polymer dynamics on short-time scales (up to microseconds), many important dynamical processes, which can be investigated experimentally, happen on a longer timescale. To properly describe dynamics of macromolecular systems it is necessary to develop novel theoretical tools that bridge the different time- (length-) scales of interest.

We approached this problem from different angles:

Starting from integral equation approach we derived a theoretical coarse-graining procedure that is portable, analytical, and bridges information reversibly between different lengthscales (Phys. Rev. Lett. 93, 257803 (2004), J. Chem. Phys. 122, 054907 (2005)). Our theory provides the effective potential input to simulations of macromolecular aggregation and dynamics.

The effective mean-force potential so derived enters our Cooperative Dynamic Equation (Phys. Rev. Lett., 88, 25901 (2002), Macromolecules, 35, 2714 (2002), J. Chem. Phys. 119, 7568 (2003)), which provides the theoretical framework to describe cooperative (subdiffusive) dynamics of interacting macromolecules in melts.

To describe the dynamics of biological systems we developed a novel theoretical approach for protein dynamics, which correctly bridges short-time (compared with simulations) to long-time dynamics (compared with NMR data) of proteins in solution. The theory predicts with no fitting parameters experimental data of T1, T2 and NOE NMR relaxation for the signal transduction protein CheY.