Postdoctoral Research Fellowships in Biology for FY 2009

2009财年生物学博士后研究奖学金

• 批准号: 0906026
• 负责人: Firas Khatib
• 金额: $ 12.3万
• 依托单位: Khatib Firas D
• 依托单位国家: 美国
• 项目类别: Fellowship
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-11-01 至 2011-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0906026&HistoricalAwards=false
• 关键词: Postdoctoral; Research; Fellowships; Biology; FY

This action funds an NSF Postdoctoral Research Fellowship for FY 2009. The fellowship supports a research and training plan entitled "Automating human intuition to improve protein structure prediction" for Firas Khatib. The host institution for this research is the University of Washington, and the sponsoring scientist is Dr. David Baker.This project uses the combined power of humans and computers to build accurate models of disease-related proteins. Determining the correct structure of a protein helps researchers successfully target them with drugs. Experimental methods for solving proteins are time consuming and expensive, making a computational solution to the protein-folding problem necessary. Even with the current supercomputing and distributed computing power available, new algorithms are needed to solve one of the main computational bottlenecks, conformational sampling. Because a protein chain can have so many different possible conformations, efficient exploration of the search space is crucial. A new approach to this problem is the use of human puzzle-solving intuition and pattern recognition skills combined with computers running Rosetta, the prediction algorithm developed in David Baker's research group. Foldit is an interactive Rosetta-based program allowing users around the world to directly manipulate protein structure models on their home computers in real-time. The ultimate goal of Foldit is to use the results from the computer program to improve structure prediction algorithms by capitalizing on natural human 3D problem-solving skills. The project determines what aspect of the structure prediction problem game-playing humans can improve and implement these new techniques into Rosetta's automated protocol. The successful automation of human intuition would be a remarkable achievement in computational science. Training objectives include development of programming and computational skills as well as teaching and mentoring abilities. Foldit users are able to share their solutions with others around the world, taking advantage of the strengths that different people have, in order to improve results globally. Presentations on Foldit are being given to children and parents at the local science and educational museum and at local high schools in the hope that Foldit could be used in chemistry courses around the world, creating the next generation of protein folders, and then in turn new structure prediction algorithms could be developed based on these new experts' protein-folding skills. This gives worldwide participants an immediate and relevant application for protein-folding knowledge, hopefully reinforcing the motivation to understand the underlying science. In addition, because anyone in the world can contribute to Foldit, this research establishes a global collaborative network. The algorithms and methods developed will be published, and the Rosetta software source code will be freely and openly available to the scientific community.

这项行动为2009财政年度的NSF博士后研究奖学金提供资金。该奖学金支持Firas Khatib的一项名为“自动化人类直觉以改善蛋白质结构预测”的研究和培训计划。这项研究的主办机构是华盛顿大学，赞助科学家是大卫贝克博士，这个项目利用人类和计算机的联合力量来建立疾病相关蛋白质的精确模型。确定蛋白质的正确结构有助于研究人员成功地用药物靶向它们。解决蛋白质的实验方法是耗时和昂贵的，使计算解决蛋白质折叠问题的必要。 即使有目前的超级计算和分布式计算能力，需要新的算法来解决主要的计算瓶颈之一，构象采样。由于蛋白质链可能有许多不同的可能构象，因此有效探索搜索空间至关重要。解决这个问题的一种新方法是利用人类解谜的直觉和模式识别技能，结合运行罗塞塔的计算机，罗塞塔是大卫贝克研究小组开发的预测算法。Foldit是一个基于Rosetta的交互式程序，允许世界各地的用户直接在家用计算机上实时操作蛋白质结构模型。Foldit的最终目标是利用计算机程序的结果，通过利用人类自然的3D问题解决能力来改进结构预测算法。该项目确定了玩游戏的人类可以改进结构预测问题的哪些方面，并将这些新技术应用到Rosetta的自动化协议中。人类直觉的成功自动化将是计算科学的一项非凡成就。培训目标包括开发编程和计算技能以及教学和指导能力。Foldit用户能够与世界各地的其他人分享他们的解决方案，利用不同人的优势，以改善全球的结果。 在当地的科学和教育博物馆以及当地的高中，正在向儿童和家长进行关于Foldit的演示，希望Foldit可以用于世界各地的化学课程，创造下一代蛋白质文件夹，然后可以根据这些新专家的蛋白质折叠技能开发新的结构预测算法。这为世界各地的参与者提供了蛋白质折叠知识的即时和相关应用，希望加强理解基础科学的动机。此外，由于世界上任何人都可以为Foldit做出贡献，这项研究建立了一个全球合作网络。所开发的算法和方法将被公布，Rosetta软件源代码将免费公开提供给科学界。