Development of the flexible comparative modeling toolkit

描述(申请人提供)：结构生物学为我们提供了数以万计的蛋白质三维结构的例子，这些结构给出了许多重要生物过程的分子水平信息。所有这些结构的坐标都存储在蛋白质数据库中，可以在那里下载和进一步分析。大多数PDB用户对与特定生物问题相关的特定蛋白质感兴趣，但相同的是 也可以分析数据，不是为了个别蛋白质的特定特征，而是为了识别描述蛋白质结构的经验规则，这些规则反过来可以用于蛋白质结构预测和 模拟。后一种方法被成功地用来推导出在Rosetta等程序中使用的经验势和规则。然而，PDB现有数据中包含的大量信息仍未得到利用，这主要是因为缺乏适当的软件工具。在这里，我们建议挖掘PDB，以寻找包含在密切相关甚至相同的蛋白质结构中的信息。我们认为，这种情况，在大多数现有的蛋白质结构分析中被排除为“多余的”，提供了关于蛋白质灵活性的独特的，甚至是间接的信息，特别是各种蛋白质折叠改变蛋白质结构的方式和方向。 结构对突变的反应(进化灵活性)，或对激活或配体结合的反应(功能灵活性)。作为我们分析的结果，我们预计会得出关于以下方面的经验规则 蛋白质结构变化，可用于加速和/或直接模拟，并可用于预测蛋白质在直接实验中无法实现的功能状态的构象的规则。这项提议的主要成果将是“灵活的比较建模”工具包，即一系列算法和协议，允许用户将蛋白质结构变化的经验规则应用于他们感兴趣的蛋白质。该工具包可从 项目网站作为服务器，也会作为开源软件包分发。

DESCRIPTION (provided by applicant): Structural biology provided us with tens of thousands of examples of protein three- dimensional structures, which gave molecular level information about many important biological processes. Coordinates of all these structures are deposited to a Protein Data Bank, where they are available for downloads and further analysis. Most of PDB users are interested in specific proteins relevant to a particular biological problem, but the same data can also be analyzed not for specific features of individual proteins, but to identify empiricl rules describing protein structures, which in turn can be used in protein structure predictions and simulations. The latter approach was used successfully to derive empirical potentials and rules that are used in programs such as Rosetta. However, a significant amount of information contained in the data available in the PDB is still untapped, mostly because of lack of adequate software tools. Here we propose to mine the PDB for information contained in structures of closely related or even identical proteins. We argue, that such cases, removed as "redundant" in most extant analyses of protein structures, provide unique, even that indirect, information about protein flexibility and specifically, ways and directions in which various protein folds change the structure in response to mutations (evolutionary flexibility), or to activation or ligand binding (functional flexibility). As a result of our analysis, we anticipate deriving empirical rules about protein structural changes, rules that can be applied to speed up and/or direct simulations and can be used to predict conformations of proteins in functional states unavailable from the direct experiment. The main deliverable of this proposal would be a "flexible comparative modeling" toolkit, a series of algorithms and protocols which would allow the users to apply empirical rules of protein structure changes to their protein of interest. This toolkit would be available from the project website as a server, but also would be distributed as an open source software package.