Computational Challenges in Multiscale Modeling and Simulation of Biological Systems

Biological molecules such as proteins are an integral part of the machinery of the cell. Understanding their dynamics, conformations, and interactions are essential steps in interpreting their behavior, annotating genomes, devising new medicinal drugs, and understanding cellular-level processes. At the same time, cells themselves interact to produce tissues and organs during development. The size of these systems, as well as the presence of multiple time and length scales makes systems biology modeling and simulation very challenging.

In the first part of this talk, I present my work on multiscale molecular dynamics integrators and propagators, which are based upon sampling of fast scales and construction of accurate and cheap representations of the slow scales. I discuss optimization of these methods in high-performance parallel and distributed implementations. Then I consider the application of these methods to model the docking of medicinal drugs to flexible proteins such as enzymes, integrating experimental Nuclear Magnetic Resonance (NMR) information, along with multiscale simulations.

For the second part, I will survey the interfacing of molecular modeling with the study of protein interaction networks at a genome-wide level, and the construction of cell-based models for biological development, particularly the skeletal formation in chicken limb. These models are implemented using hybrid discrete-continuum, stochastic-deterministic algorithms. I discuss computational and mathematical issues related to the integration of multiple scale simulations and experimental data in the context of advanced systems for parallel and distributed computing.