Computational Design of Complex Multi-Scale Systems: Design of Synthetic Muscle with Shape Grammars and Agent-Based Search

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

The research objective of this award is to explore the computational design of complex multi-scale systems, with a focus on the hierarchical design of synthetic muscles at the macro level via design of myosin (a molecular motor) and myosin-actin networks at the nanoscale level. Through a 5-level hierarchy, myosin is the major force component in a multi-scale macro structural muscle system. This research uses a novel computational method that combines multi-level, multi-scale agent-based search with shape grammar representations of myosin to configure new myosin-actin filament designs and potential new biomaterials (synthetic muscle) with desired macro-level functional properties. It is anticipated that through combinations of different types of myosin at the lowest scale, unique macro muscle properties will emerge, and potentially new protein discoveries can be identified based on computational exploration. If successful, this research will enable design across scales from nano to macro while adapting to the complexity of the resulting emergent behavior in a biologically assembled system. As well, the use of computers to effectively and rapidly search across these scales for meaningful designs will enable greater exploration than is currently available through the wet lab, and the potential for discovery of new proteins that exist or could potentially be made in nature. The created computational tool may lead to new nanomaterials with important biomedical properties - non-intuitive innovative designs from different combinations of myosin and actin or new protein discoveries may result.