An easy-to-use and powerful tool for improved Rosetta comparative modeling of proteins

 描述(申请人提供)：在这个项目中，我们的目标是改进Rosetta软件包中最先进的同源建模管道，增强其建模大型蛋白质和利用近原子分辨率密度数据和稀疏核磁共振数据进行结构精细化的能力。我们还将开发一个图形用户界面(GUI)和一个易于使用的后端，允许用户轻松设置建模任务并访问大量计算。该项目的成功将促进药物设计和其他需要 精确的计算模型。它还将提供准确的估计，以告知用户对输出模型的信任。这里开发的软件建立了一个框架，在这个框架中，没有广泛的计算背景或没有时间学习复杂的新命令行工具的学术和商业用户可以通过图形用户界面与Rosetta建模软件包交互。这里要研究的三个重叠区域是：1.改进同源建模方法。我们将进一步开发RosettaCM中包含的断链运动学系统，并根据之前的CASP和客串实验收集的大数据集进行基准测试。将开发一个更具层次性的运动学系统，用于使用已知联系信息进行建模，并使用具有稀疏核磁共振数据的数据集进行测试。2.图形用户界面(GUI)。使用Rosetta这样的建模软件包面临的挑战之一是，它需要大量计算机科学方面的事先培训，包括基本的Linux技能、软件编译、简单的脚本编写和表格数据操作。我们将开发一个强大的图形用户界面，以使与Rosetta软件包的交互变得更加容易，而不会牺牲用户对建模关键方面的控制。3.云计算。在结构建模期间，需要大量的计算资源来实现海量采样，这通常会导致更准确的结果。然而，在当地部署这种计算资源是稀缺和昂贵的。通过开发既可在本地群集上交付也可通过云计算交付的部署机制，我们可以确保所有科学用户都可以轻松地访问需要大量采样的任务。

 DESCRIPTION (provided by applicant): In this project we aim to improve on the state-of-the-art homology modeling pipeline in the Rosetta software package, strengthen its capability in modeling large proteins and structure refinement with near-atomic resolution density data and sparse NMR data. We will also develop a graphical user interface (GUI) and an easy-to-use backend that will allow a user to easily set up modeling tasks and access large amounts of computing. The success of this project will facilitate drug design and other applications requiring accurate computational models. It will also provide accuracy estimations to inform the user's trust in the output model. The software developed here establishes a framework in which both academic and commercial users without an extensive computational background or the time to learn a complex new command-line tool can interact with the Rosetta modeling software package via a GUI. The three overlapping areas to be investigated here are: 1. Improving homology modeling methods. We will further develop the broken chain kinematics system incorporated in RosettaCM and benchmark against a large dataset collected from previous CASP and CAMEO experiments. A more hierarchical kinematics system will be developed for modeling with known contact information and tested using a dataset with sparse NMR data. 2. Graphical user interface (GUI). One of the challenges of using a modeling software package such as Rosetta is that it requires a large amount of prior training in computer science, including basic Linux skills, software compilation, simple scripting and tabular data manipulation. We will develop a powerful GUI so that interactions with the Rosetta software package become much easier, without sacrificing user control over key aspects of modeling. 3. Cloud computing. Large computing resources are necessary to achieve massive amounts of sampling during structure modeling, and this often leads to more accurate results. However to the access to such computing resources is scarce and expensive to deploy locally. By developing a deployment mechanism that is deliverable on both a local cluster or via cloud computing, we can ensure that tasks that require large amounts of sampling are easily accessible to all scientific users.