Constraint Based Algorithms for Protein Folding

技术摘要：材料研究司和数学科学司为该奖项提供资金，该奖项属于国家科学基金会范围内的数学科学优先领域，并对网络基础设施作出贡献。该奖项支持蛋白质折叠和反问题解决领域的理论和计算研究。PI计划将一种成功的解决方案搜索策略应用于蛋白质折叠问题的相恢复领域。这种方法的关键元素是欧氏空间中的约束投影，它以最小的努力将特定的约束恢复到任意输入点。许多问题都可以用它们的解点在两个约束集的交点上来表示。对于这类问题，动力系统可以用相应的约束投影来定义，集合相交问题的解编码在它的固定点上。在蛋白质结构预测中，基于约束的算法是可供选择的方法，与主流采样算法相比，在蛋白质结构预测中具有显著的优势。在相位检索中，由于超定的约束集赋予了显著的计算优势，当折叠设计良好的序列时，期望获得类似的收益。用简单的蛋白质杂聚模型进行的实验表明，这种方法可以扩展到现实的模型，其中两个约束对应于链几何和单体堆积。该项目还将开发一种新的分布式计算形式，使基于约束的搜索的混沌动力学成为可能。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名为“半蛋白世界”的工作环境的微型实现。半蛋白质是具有高度简化性质的模型蛋白质，但它们构成了许多与真实蛋白质相同的挑战。通过一系列软件工具，包括基于网络的半蛋白质数据库，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质，然后将他们的发现存储在数据库中。半蛋白质世界的设计将让伊萨卡地区的高中生和本科生现场参与康奈尔材料研究中心的NSF-REU计划。非技术概述：材料研究司和数学科学司为该奖项提供资金，该奖项属于NSF范围内的数学科学优先领域，并对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组成部分，在生物体的结构和功能中发挥着重要作用。为了实现它们的生物学功能，蛋白质经历了一种自组装，呈现出特定的形状或折叠。折叠蛋白质的形状，它是如何折叠的，以及它是如何如此快速地折叠的，是理解其功能的关键基础问题。目前，现有的计算机模拟方法计算量很大。在这里，PI将利用蛋白质折叠问题与显微镜之间的基本联系，这些显微镜试图从不完美的数据(如X射线衍射)中生成图像，以进一步开发一种强大的蛋白质折叠新算法，以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目前的方法。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名为“半蛋白世界”的工作环境的微型实现。半蛋白质是具有高度简化性质的模型蛋白质，但它们构成了许多与真实蛋白质相同的挑战。通过一系列软件工具，包括基于网络的半蛋白质数据库，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质，然后将他们的发现存储在数据库中。半蛋白质世界的设计将让伊萨卡地区的高中生和本科生现场参与康奈尔材料研究中心的NSF-REU计划。

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.