Constraint Based Algorithms for Protein Folding

基于约束的蛋白质折叠算法

• 批准号: 0539041
• 负责人: Veit Elser
• 金额: $ 30万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-15 至 2011-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0539041&HistoricalAwards=false
• 关键词: Constraint; Based; Algorithms; Protein; Folding

TECHNICAL SUMMARY:The Division of Materials Research and the Division of Mathematical Sciences contribute funding to this award which falls under the NSF-wide Mathematical Sciences Priority Area and contributes to cyberinfrastructure. This award supports theoretical and computational research in the area of protein folding and the solution of inverse problems. The PI plans to apply a successful solution search strategy in the area of phase retrieval to the problem of protein folding. The key elements of this method are constraint projections in a Euclidean space that with minimal effort restore a particular constraint to an arbitrary input point. Many problems can be formulated in terms of their solution points being in the intersection of just two constraint sets. For such problems a dynamical system can be defined in terms of the corresponding constraint projections with the solution to the set intersection problem encoded in its fixed points. Constraint based algorithms are the method of choice in phase retrieval and may offer significant advantages, over mainstream sampling algorithms, in protein structure prediction.As in phase retrieval, where a significant computational advantage is conferred by overdetermined constraint sets, a similar gain is expected when folding sequences that are well designed. Experiments with simple heteropolymer models of proteins, where the two constraints correspond to chain geometry and monomer packing, show promise that this approach can be extended to realistic models. This project will also develop a novel form of distributed computing made possible by the chaotic dynamics of the constraint based search.The next generation of scientists and engineers will increasingly rely on shared data bases and standardized computing protocols in the conduct of their work. A significant component of this project is the development of a miniature realization of such a work environment called "semiprotein world". Semiproteins are model proteins with highly simplified properties, but which pose many of the same challenges posed by real proteins. Through a collection of software tools, including a web-based semiprotein data bank, semiprofessional researchers with web access will be able to design and fold semiproteins, and then deposit their findings in the data base. The design of semiprotein world will involve on-site participation of Ithaca area high school students and undergraduates in the Cornell Center for Materials Research NSF-REU program.NON-TECHNICAL SUMMARY:The Division of Materials Research and the Division of Mathematical Sciences contribute funding to this award which falls under the NSF-wide Mathematical Sciences Priority Area and contributes to cyberinfrastructure. This award supports theoretical and computational research in the area of protein folding. Proteins are major constituents of biological cells and play important roles in structure and function in living organisms. In order to carry out their biological function, the protein undergoes a kind of self-assemble to assume a particular shape or fold. The shape of a folded protein, how it folds and how it does it so quickly are key fundamental questions in understanding its function. Currently exiting computer simulation methods are very computationally intense. Here the PI will exploit fundamental connections between the problem of protein folding and microscopies that seek to develop an image from imperfect data, e.g. x-ray diffraction, to further develop a powerful new algorithm for protein folding to overcome the barrier of long simulation time. Preliminary results suggest that the algorithm will be far more computationally efficient than current methods.The next generation of scientists and engineers will increasingly rely on shared data bases and standardized computing protocols in the conduct of their work. A significant component of this project is the development of a miniature realization of such a work environment called "semiprotein world". Semiproteins are model proteins with highly simplified properties, but which pose many of the same challenges posed by real proteins. Through a collection of software tools, including a web-based semiprotein data bank, semiprofessional researchers with web access will be able to design and fold semiproteins, and then deposit their findings in the data base. The design of semiprotein world will involve on-site participation of Ithaca area high school students and undergraduates in the Cornell Center for Materials Research NSF-REU program.

技术摘要：材料研究部和数学科学部为该奖项提供资金，该奖项属于 NSF 范围内的数学科学优先领域，并为网络基础设施做出了贡献。该奖项支持蛋白质折叠领域的理论和计算研究以及反问题的解决。 PI 计划将相检索领域的成功解决方案搜索策略应用于蛋白质折叠问题。该方法的关键要素是欧几里德空间中的约束投影，它可以用最小的努力将特定约束恢复到任意输入点。许多问题可以根据其解点位于两个约束集的交集中来表述。对于此类问题，可以根据相应的约束投影来定义动态系统，并将集合交集问题的解编码在其固定点中。基于约束的算法是相位检索中的首选方法，在蛋白质结构预测方面，与主流采样算法相比，它可以提供显着的优势。与相位检索一样，超定约束集赋予了显着的计算优势，当折叠设计良好的序列时，预计会获得类似的增益。使用简单的蛋白质杂聚物模型进行的实验（其中两个约束对应于链几何形状和单体堆积）表明这种方法可以扩展到现实模型。该项目还将开发一种新颖的分布式计算形式，通过基于约束的搜索的混沌动力学使之成为可能。下一代科学家和工程师在工作中将越来越依赖共享数据库和标准化计算协议。该项目的一个重要组成部分是开发一种称为“半蛋白世界”的工作环境的微型实现。半蛋白是具有高度简化特性的模型蛋白，但它提出了许多与真实蛋白相同的挑战。通过一系列软件工具，包括基于网络的半蛋白数据库，具有网络访问权限的半专业研究人员将能够设计和折叠半蛋白，然后将他们的发现存入数据库。半蛋白世界的设计将涉及康奈尔材料研究中心 NSF-REU 计划的伊萨卡地区高中生和本科生的现场参与。 非技术摘要：材料研究部和数学科学部为该奖项提供资金，该奖项属于 NSF 数学科学优先领域，并为网络基础设施做出贡献。该奖项支持蛋白质折叠领域的理论和计算研究。蛋白质是生物细胞的主要成分，在生物体的结构和功能中发挥着重要作用。为了执行其生物学功能，蛋白质经历一种自组装以呈现特定的形状或折叠。折叠蛋白质的形状、它如何折叠以及它如何如此快速地折叠是理解其功能的关键基本问题。目前现有的计算机模拟方法计算量非常大。在这里，PI 将利用蛋白质折叠问题和显微镜之间的基本联系，寻求从不完美的数据中开发图像，例如X射线衍射，进一步开发强大的蛋白质折叠新算法，克服模拟时间长的障碍。初步结果表明，该算法的计算效率将远远高于当前方法。下一代科学家和工程师在工作中将越来越依赖共享数据库和标准化计算协议。该项目的一个重要组成部分是开发一种称为“半蛋白世界”的工作环境的微型实现。半蛋白是具有高度简化特性的模型蛋白，但它提出了许多与真实蛋白相同的挑战。通过一系列软件工具，包括基于网络的半蛋白数据库，具有网络访问权限的半专业研究人员将能够设计和折叠半蛋白，然后将他们的发现存入数据库。半蛋白世界的设计将邀请伊萨卡地区高中生和本科生现场参与康奈尔材料研究中心 NSF-REU 项目。