IMP: Software for Hybrid Determination of Macromolecular Assembly Structures

项目摘要 其主要目标是开发和应用计算方法来建立蛋白质和蛋白质的结构模型 他们的集会。一种成功的方法，即集成结构建模，将构建这样的模型 一种计算优化问题，其中关于程序集的知识被编码到评分函数中 用于评估候选模型。我们建议扩展和增强集成建模平台(IMP) 为开发和分发一体化结构建模程序提供编程支持的程序。 催产素。IMP已经允许以多个分辨率表示分子，使用来自多个 数据类型，并通过各种采样算法寻找解决方案。到目前为止，它已经得到了广泛的应用 从电子显微镜(EM)、质谱学、小角X射线散射、Förster共振 能量转移、交联、氢氚交换(HDX)和各种蛋白质组学方法。小鬼是 易于扩展以添加对新数据源和算法的支持，并在开放源码下分发 执照。在这里，我们建议扩展IMP以解决更广泛的生物问题，并使其 更广泛地说，它对科学界有用。具体地说，在目标1中，我们将开发集成线程 用于根据由EM或X确定的中等分辨率(4-8？)密度图计算原子模型- 射线结晶学。这一目标将通过同时采样丝线和构象来实现 根据密度图以及其他数据，如化学交联链和HDX保护系数。这 方法很重要，因为它将从确定的中分辨率地图生成原子分辨率模型 通过EM或X-射线结晶学。在目标2中，我们将开发一种贝叶斯综合建模方法 相似系统的合奏。来自不同样本、集合和/或变体的数据通常汇集在一起 对单一的代表性结构进行建模。这种合成是有问题的，因为实际的 样本、集合和变量的结构比数据的不确定性更大。我们将解决 通过开发一个通用和灵活的方案来表示和评分相关的结构工程，这一挑战 西布尔斯。这种方法具有重要的意义，因为它将提高模型的精度和估计其 不确定性。在目标3中，我们将最大限度地发挥IMP对社区的影响，通过提供经过充分测试和 维护的软件包，记录了本地和 外部研讨会，在加州大学旧金山分校接待精选用户，并寻求与其他软件更紧密的集成 包和社区资源，包括蛋白质数据库(PDB)、结构视图等数据库- 例如Chimera和VMD等ERS，以及NAMD和Readdy等其他建模程序。建议的目标 受到并将塑造新生的全球PDB在表示、验证、归档和 推广一体化结构模式。

Project Summary The broad goal is to develop and apply computational methods for building structural models of proteins and their assemblies. One successful approach, integrative structure modeling, casts the building of such models as a computational optimization problem where knowledge about the assembly is encoded into the scoring function used to evaluate candidate models. We propose to extend and enhance the Integrative Modeling Platform (IMP) program that provides programmatic support for developing and distributing integrative structure modeling pro- tocols. IMP already allows representing molecules at multiple resolutions, using spatial restraints from many types of data, and searching for solutions by a variety of sampling algorithms. So far, it has been applied mostly to data from electron microscopy (EM), mass spectrometry, small angle X-ray scattering, Förster resonance energy transfer, crosslinking, hydrogen deuterium exchange (HDX), and various proteomics methods. IMP is easily extensible to add support for new data sources and algorithms, and is distributed under an open source license. Here, we propose to extend IMP to address a greater range of biological problems and make it more generally useful to the scientific community. Specifically, in Aim 1, we will develop integrative threading for computing an atomic model based on a density map determined at medium resolution (4-8 Å) by EM or X- ray crystallography. This goal will be achieved by simultaneously sampling both threading and conformation based on the density map as well as other data, such as chemical cross-links and HDX protection factors. This method is significant because it will produce atomic resolution models from medium-resolution maps determined by either EM or X-ray crystallography. In Aim 2, we will develop a Bayesian integrative method for modeling ensembles of similar systems. Data from different samples, ensembles, and/or variants are often pooled together to model a single representative structure. This synthesis is problematic when the variation between the actual structures across the samples, ensembles, and variants is larger than the uncertainty of the data. We will address the challenge by developing a general and flexible scheme for representing and scoring related structural en- sembles. This method is significant because it will improve the accuracy of the model and the estimate of its uncertainty. In Aim 3, we will maximize the impact of IMP on the community, by delivering a well-tested and maintained software package that is documented with mailing lists, examples, and demonstrations at local and external workshops, by hosting select users at UCSF, and by pursuing closer integration with other software packages and community resources, including databases such as the Protein Data Bank (PDB), structure view- ers such as Chimera and VMD, and other modeling programs such as NAMD and ReaDDy. The proposed aims are informed by and will shape the nascent worldwide PDB effort on representing, validating, archiving, and disseminating integrative structure models.