Rosetta: An Integrated Macromolecular Modeling Suite

Rosetta:集成的大分子建模套件

基本信息

  • 批准号:
    7923881
  • 负责人:
  • 金额:
    $ 57.3万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2005
  • 资助国家:
    美国
  • 起止时间:
    2005-03-01 至 2013-08-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Rosetta is molecular modeling software that has been developed for the prediction and design of macromolecular structure. Rosetta has performed well in community wide assessments of protein structure prediction and docking, and it has been used to design new protein structures as well as design altered specificity protein-protein and protein-DNA interactions. Rosetta is developed and maintained by research groups at 11 separate universities, and over 2400 laboratories have obtained free licenses for the software. Until 2004, Rosetta was written in Fortran 77. Over the past three years we have used NIH support to create a new C++ object-oriented version of Rosetta. The new software is organized as a set of libraries that contain classes and routines for representing and scoring molecular systems, for holding move sets, and for performing optimization of macromolecular conformation and sequence. The primary goal of this proposal is to capitalize on this rewrite, and extend the Rosetta software in directions that were less feasible when the code was not modular and object-oriented. Currently, Rosetta runs through a command line interface that forces users to choose from a fixed set of modeling protocols, such as protein-protein docking or the design of protein monomers. We will create a framework within Rosetta that allows users to easily create custom protocols in either C++ or with the scripting language Python. The python binding will be used to create an interface with PyMOL, a widely used program for molecular visualization. This will provide a graphical interface for initiating and interacting with Rosetta simulations as well as rapidly evaluating the quality of Rosetta models. Most applications of Rosetta benefit significantly from increased sampling of conformational and/or sequence space, and therefore, benefit from faster algorithms. We will increase the speed of Rosetta calculations by taking advantage of new C++ objects for caching energies. This grant will also support developers and users by maintaining benchmarks that test the integrity of the code, maintaining the user's guide and supporting meetings between developers at the various institutions. PUBLIC HEALTH RELEVANCE: The function of a protein, RNA or DNA molecule is largely determined by its 3- dimensional structure. We aim to develop a state-of-the-art computer program for predicting and designing the structures of biological macromolecules. The program will be freely available to academic laboratories and its predictions will help investigators understand and fight human diseases such as cancer and AIDS.
描述(由申请人提供):Rosetta 是为大分子结构的预测和设计而开发的分子建模软件。 Rosetta 在蛋白质结构预测和对接的全社区评估中表现良好,它已被用于设计新的蛋白质结构以及设计改变特异性的蛋白质-蛋白质和蛋白质-DNA 相互作用。 Rosetta 由 11 所大学的研究小组开发和维护,超过 2400 个实验室已获得该软件的免费许可证。直到 2004 年,Rosetta 都是用 Fortran 77 编写的。在过去的三年里,我们使用 NIH 支持创建了新的 C++ 面向对象版本的 Rosetta。新软件被组织为一组库,其中包含用于表示和评分分子系统、用于保存移动集以及用于执行大分子构象和序列优化的类和例程。该提案的主要目标是利用这次重写,并将 Rosetta 软件扩展到当代码不是模块化和面向对象时不太可行的方向。目前,Rosetta 通过命令行界面运行,迫使用户从一组固定的建模协议中进行选择,例如蛋白质-蛋白质对接或蛋白质单体的设计。我们将在 Rosetta 中创建一个框架,允许用户使用 C++ 或脚本语言 Python 轻松创建自定义协议。 python 绑定将用于创建与 PyMOL 的接口,PyMOL 是一种广泛使用的分子可视化程序。这将提供一个图形界面,用于启动 Rosetta 模拟并与之交互,以及快速评估 Rosetta 模型的质量。 Rosetta 的大多数应用都显着受益于构象和/或序列空间采样的增加,因此受益于更快的算法。我们将通过利用新的 C++ 对象来缓存能量来提高 Rosetta 计算的速度。这笔赠款还将通过维护测试代码完整性的基准、维护用户指南以及支持各个机构的开发人员之间的会议来支持开发人员和用户。公共卫生相关性:蛋白质、RNA 或 DNA 分子的功能很大程度上取决于其 3 维结构。我们的目标是开发一种最先进的计算机程序来预测和设计生物大分子的结构。该项目将免费提供给学术实验室,其预测将帮助研究人员了解和对抗癌症和艾滋病等人类疾病。

项目成果

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BRIAN A KUHLMAN其他文献

BRIAN A KUHLMAN的其他文献

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{{ truncateString('BRIAN A KUHLMAN', 18)}}的其他基金

Computational Design of Protein Structures and Complexes
蛋白质结构和复合物的计算设计
  • 批准号:
    10433948
  • 财政年份:
    2019
  • 资助金额:
    $ 57.3万
  • 项目类别:
Computational Design of Protein Structures and Complexes
蛋白质结构和复合物的计算设计
  • 批准号:
    10415800
  • 财政年份:
    2019
  • 资助金额:
    $ 57.3万
  • 项目类别:
Computational Design of Protein Structures and Complexes
蛋白质结构和复合物的计算设计
  • 批准号:
    10119999
  • 财政年份:
    2019
  • 资助金额:
    $ 57.3万
  • 项目类别:
Computational Design of Protein Structures and Complexes
蛋白质结构和复合物的计算设计
  • 批准号:
    10389382
  • 财政年份:
    2019
  • 资助金额:
    $ 57.3万
  • 项目类别:
Computational Design of Protein Structures and Complexes
蛋白质结构和复合物的计算设计
  • 批准号:
    10647739
  • 财政年份:
    2019
  • 资助金额:
    $ 57.3万
  • 项目类别:
GPU workstation for deep learning-based protein design and cryo-EM data processing
GPU 工作站,用于基于深度学习的蛋白质设计和冷冻电镜数据处理
  • 批准号:
    10797767
  • 财政年份:
    2019
  • 资助金额:
    $ 57.3万
  • 项目类别:
Computational Design of Protein Structures and Complexes
蛋白质结构和复合物的计算设计
  • 批准号:
    10226832
  • 财政年份:
    2019
  • 资助金额:
    $ 57.3万
  • 项目类别:
Computational Methods for Requirement-Driven Protein Design
需求驱动的蛋白质设计的计算方法
  • 批准号:
    9315841
  • 财政年份:
    2015
  • 资助金额:
    $ 57.3万
  • 项目类别:
Computational Methods for Requirement-Driven Protein Design
需求驱动的蛋白质设计的计算方法
  • 批准号:
    9549177
  • 财政年份:
    2015
  • 资助金额:
    $ 57.3万
  • 项目类别:
Computational Methods for Requirement-Driven Protein Design
需求驱动的蛋白质设计的计算方法
  • 批准号:
    9056243
  • 财政年份:
    2015
  • 资助金额:
    $ 57.3万
  • 项目类别:

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