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来构建蛋白质及其组装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、如何演化、如何控制以及如何设计类似的功能。一种成功的方法是集成结构建模，它将这些模型的构建转换为计算优化问题，其中关于装配的所有知识都被编码到用于评估候选模型的评分函数中。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很容易扩展，可以添加对新数据源和算法的支持，并且在开源许可下发布，自2010年3月以来，已有300多个独立下载。到目前为止，它主要应用于电子显微镜、小角度x射线散射和各种蛋白质组学方法的数据。该方案将得到扩展，以便处理更广泛的生物学问题，并使其对科学界更普遍有用。具体而言，IMP使用的传统评分函数将被基于推理的评分函数所补充，以从数据中提取尽可能多的信息。这些函数的公式将遵循具有最小假设和近似的贝叶斯方法，以解释数据中的错误和不完整性以及异质样本。通过将自由度的完整集合有效地划分为潜在重叠的子集，通过传统的优化器或枚举方法独立地找到子集的最优解和次优解，然后将兼容解组合以获得整个系统的保证最优得分解，从而改进评分函数景观的采样。IMP还将得到扩展，以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，它将与其他软件包进行接口，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，软件将经过充分的测试和记录，并且将通过邮件列表、示例、研讨会演示和UCSF的精选用户托管来支持不断增长的IMP社区。

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.