IMP: Software for Hybrid Determination of Macromolecular Assembly Structures

描述（由申请人提供）：广泛的目标是开发和应用计算方法，用于构建蛋白质及其组装体的结构和动力学的数据衍生模型。这些模型可以深入了解组件如何工作，如何演变，如何控制以及如何设计类似的功能。一个成功的方法，综合结构建模，铸造的建设，这样的模型作为一个计算优化问题，所有的知识组装编码到用于评估候选模型的评分函数。本文提出扩展和增强开源集成建模平台（IMP; http：//integrativemodeling.org/），该平台为开发和分发集成结构建模协议提供编程支持。IMP允许以各种分辨率表示分子，使用基于多种类型数据的评分函数，并通过各种采样算法搜索解决方案。此外，IMP易于扩展以添加对新数据源和算法的支持，并在开源许可证下分发，自2010年3月以来已有300多个独特的下载。到目前为止，它主要应用于电子显微镜，小角X射线散射和各种蛋白质组学方法的数据。这套资料将加以扩充，以便能够处理更多的生物问题，并使其对科学界更为普遍有用。具体而言，IMP使用的传统评分功能将补充以基于推理的评分功能，从数据中提取最大可能的信息。这些函数的制定将遵循贝叶斯方法，采用最少的假设和近似值，以解释数据中的错误和不完整性以及异质样本。评分函数景观的采样将通过一种方法来改进，该方法有效地将完整的自由度集划分为潜在重叠的子集，通过传统的优化器或枚举独立地找到子集的最优和次优解，然后组合兼容的解以获得整个系统的保证最佳评分解。还将扩大国际监测方案的范围，以便充分利用质谱法提供的丰富信息。为了最大限度地发挥IMP的影响及其对社区的效用，它将与其他软件包连接，包括结构查看器如Chimera，结构预测和设计程序如Rosetta，以及门户网站如Protein Model Portal。最后，该软件将得到良好的测试和记录，不断增长的IMP社区将得到邮件列表，示例，研讨会演示和UCSF精选用户的托管支持。 公共卫生相关性：项目叙述我们建议扩展IMP，一个计算机程序，可以描述的三维形状的大分子机器，不适合解决方案与一个单一的实验技术。这些结构将使我们能够更好地了解细胞在正常和疾病条件下的运作。

DESCRIPTION (provided by applicant): The broad goal is to develop and apply computational methods for building data-derived models of the structure and dynamics of proteins and their assemblies. These models can give insights into how the assemblies work, how they evolved, how they can be controlled, and how similar functionality can be designed. One successful approach, integrative structure modeling, casts the building of such models as a computational optimization problem where all knowledge about the assembly is encoded into the scoring function used to evaluate candidate models. It is proposed here to extend and enhance the open source Integrative Modeling Platform (IMP; http://integrativemodeling.org/) that provides programmatic support for developing and distributing integrative structure modeling protocols. IMP allows representation of molecules at a variety of resolutions, use of scoring functions based on many types of data, and searches for solutions by a variety of sampling algorithms. In addition, IMP is easily extensible to add support for new data sources and algorithms, and is distributed under an open source license, with more than 300 unique downloads since March 2010. So far, it has been applied mostly to data from electron microscopy, small angle X-ray scattering, and various proteomics methods. The package will be extended to allow addressing a greater range of biological problems and to make it more generally useful to the scientific community. Specifically, the traditional scoring functions used by IMP will be supplemented with inference-based scoring functions that extract the maximum possible information from the data. The formulation of these functions will follow a Bayesian approach with minimal assumptions and approximations, to account for errors and incompleteness in the data as well as a heterogeneous sample. Sampling of the scoring function landscape will be improved by a method that efficiently divides the complete set of degrees of freedom into potentially overlapping subsets, finds optimal and suboptimal solutions for the subsets independently by traditional optimizers or enumeration, and then combines compatible solutions to obtain guaranteed best-scoring solutions for the whole system. IMP will also be extended to make best use of the wealth of information provided by mass spectrometry. To maximize the impact of IMP and its utility to the community, it will be interfaced with other packages, including structure viewers such as Chimera, structure prediction and design programs such as Rosetta, and web portals such as the Protein Model Portal. Finally, the software will be well-tested and documented, and the growing IMP community will be supported with mailing lists, examples, demonstrations at workshops, and hosting of select users at UCSF. PUBLIC HEALTH RELEVANCE: Project Narrative We propose to extend IMP, a computer program that can describe the three-dimensional shapes of large macromolecular machines that are not amenable to solution with a single experimental technique. These structures will allow us to better understand the workings of the cell, both under normal and disease conditions.