EAGER: Visualization of Protein Folding for Nano-Machine Design

EAGER：纳米机器设计中蛋白质折叠的可视化

• 批准号: 1053077
• 负责人: Thomas Peters
• 金额: $ 4.99万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-15 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1053077&HistoricalAwards=false
• 关键词: EAGER; Visualization; Protein; Folding; Nano

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.

这一早期概念探索性研究拨款(AGUGER)奖的研究目标是对现有方法进行可视化改进，以支持虚拟蛋白质操作作为形成设计理论的实验框架。研究人员将整合对机制的已知限制的见解，以创造更有效的蛋白质折叠算法，从而实现纳米机器设计。在这个高风险、高回报的项目中，这一过程将在为蛋白质折叠设计的高性能计算平台上可视化。结的样条线模型-包括其多边形控制结构-将可视化。用户将能够快速地进行广泛的假设视觉实验，以了解不同蛋白质操作的3D设计分支。可视化能力将通过关注内在交叉点和自我交叉点产生的设计属性来激发新的直觉和新的猜想。设计师将能够有效地探索比现有算法方法所能实现的更丰富的设计空间。因此，可视化、工程设计和高性能计算构成了这次改进蛋白质折叠算法的实验的基础。如果取得成功，并且已经在小规模原型中表现出的性能改进可以转移到现实中复杂的模型，那么这项工作将在众多社区产生重大影响，并在工业中产生重大影响。这些算法目前是整个生物分子、医学和制药界广泛研究的主题。它还将在教育学生方面产生更广泛的影响，因为参与其中的学生将有机会使用来自工业合作伙伴IBM的实际复杂和海量的数据集。学生还将接触到最先进的高性能计算平台的复杂性，例如IBM正在提供的平台。