EAGER: Visualization of Protein Folding for Nano-Machine Design

University Of Connecticut, Storrs CT

Investigators

Abstract

The research objective of this EArly-Concept Grants for Exploratory Research (EAGER) award is to create visualization refinements to an existing methodology that will support virtual protein manipulation as an experimental framework for formulating design theory. The investigators will integrate insights from known constraints on mechanisms to create more efficient protein folding algorithms so as to enable nano-machine design. In this high-risk, high-pay-off project, the process will be visualized on high performance computing platforms that have been designed for protein folding. Spline models of knots - inclusive of their polygon control structures - will be visualized. The user will be able to quickly conduct extensive 'what-if' visual experiments to understand the 3D design ramifications of differing protein manipulations. The visualization capabilities will prompt new intuition and novel conjectures by focusing attention on the design properties arising from the inherent crossings and self-intersections. The designer will be able to efficiently explore a much richer design space than can be achieved by existing algorithmic methods. Hence, visualization, engineering design, and high performance computing form the foundations for this experiment to improve protein folding algorithms. If successful and the performance improvements that have already been shown within small scale prototypes can be transferred to realistically complex models, then this work would have significant impact across numerous communities, with substantial impact in industry. These algorithms are currently the subject of extensive study throughout the bio-molecular, medical and pharmaceutical communities. There will also be a broader impact in educating students, as the students involved will have the opportunity to work with realistically complex and voluminous data sets from the industrial partner, IBM. Students will also be exposed to the complexity of the state of the art high performance computing platforms, such as IBM is providing.