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Computational challenges for modeling and simulating biomacromolecular assemblies

Understanding the structure and dynamics of large biomolecular assemblies requires the development of new computational methods for (i) accurate structure prediction, (ii) molecular docking and (iii) long time-frame molecular simulation, and implementation on massively parallel computing infrastructure. This paper reviews our progress in these areas and applications on important molecular systems. 1. Context and Outline A major next step in understanding and utilizing complex biological systems is a capability to rapidly model and simulate the structure, assembly and dynamics large assemblies of macromolecules. Molecular machines are the basis for life's chemistry. They malfunction in human disease, can be used to produce energy in microbes and from biomass, and provide the possibility of innovative new drug therapies at the interface of nanoscience and biology. The ORNL Computational Biology Program is focusing on the key steps necessary to build and simulate large molecular machines: (1) Computing Accurate Building Blocks: Building accurate models of molecular machines relies on a capability to build accurate component protein or nucleic acid structures. (2) Putting the pieces together: Given relatively accurate starting models, the components must be docked properly to create models for the molecular assembly. (3) Seeing how they work: Once models are built, simulating complex molecular machines at biologically meaningful time scales requires thoughtful problem design and current and next generation capability computers. These three key areas are addressed in the following sections. 2. Computing accurate starting protein models