Project 1 Improved algorithms for structure refinement at multiple resolution

项目 1 多分辨率结构细化的改进算法

• 批准号: 8915197
• 负责人: PAUL David ADAMS
• 金额: $ 92.95万
• 依托单位: UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8915197
• 关键词: Accounting; Address; Algorithms; Automation; Biological; Biological Models; Biological Process; Collaborations; Computer software; Crystallography; Data; Data Quality; Detection; Development; Disease; Environment; Fostering; Free Will; Freedom; Geometry; Goals; Hour; Knowledge; Lead; Length; Libraries; Life; Location; Manuals; Maps; Methods; Modeling; Molecular; Molecular Conformation; Molecular Models; Molecular Structure; Pharmaceutical Preparations; Positioning Attribute; Procedures; Reporting; Research; Research Personnel; Resolution; Ribosomes; Solutions; Solvents; Staging; Structural Biologist; Structure; System; Techniques; Time; Validation; Work; X-Ray Crystallography; abstracting; base; biological systems; data modeling; design; flexibility; graphical user interface; human disease; improved; insight; macromolecule; member; method development; model building; molecular modeling; novel strategies; novel therapeutics; open source; physical property; programs; prototype; restraint; software development; success; tool

Project Summary/Abstract X-ray crystallography is a critical tool in the study of biological systems. It is able to provide atomic resolution information that has been a prerequisite to understanding the fundamentals of life, from the structure of the double helix to the structure of the intact 70S ribosome. It is also a method that is central to the development of new therapeutics for human disease, both in commercial and academic settings. Our goal is to enable researchers to generate better atomic models than is possible with current methods. This will lead to more insightful biological interpretation and better drugs against human diseases. The development of automated methods will free researchers from time consuming manual interpretation of data and models. Collectively, these advancements will save thousands of researcher hours and make the crystallographic technique more accessible to biologists with less specialized expertise. The final stages of a crystallographic structure solution require the optimization of an atomic model with respect to the experimental diffraction data. The goal is to generate a model that best describes the contents of the crystal, principally modeled by the identity, position and mean square displacement of atoms. It is these atomic models that are interpreted to understand biological function, and are the basis for the design of novel therapeutics. The development of methods that generate improved models will positively impact both of these important research tasks. By introducing new ways to parameterize models it will be possible to generate robust and accurate models at data resolution limits that thwart current methods. By using additional information in model optimization, including energy functions from the Rosetta structure-modeling system, it will be possible to generate more accurate models that provide a better basis for subsequent interpretation. All of these algorithms will be developed in the context of the Phenix system for integrated and automated crystallography. The foundational components of Phenix will be extended to support new approaches to structure solution, refinement and validation. Working with the other researchers in the Phenix team is crucial to the success of the entire project. Collaboration, enabled by a modern software development environment, fosters a tight integration of algorithms, which can then be applied to solve a common problem. In addition, the availability of a wide range of methods in a consistent environment promotes their reuse to solve new problems. As a result the Phenix team is collectively able to very rapidly prototype and make available new methods to researchers.

项目总结/摘要 X射线晶体学是研究生物系统的重要工具。它能够提供原子分辨率信息，这是理解生命基本原理的先决条件，从双螺旋结构到完整的70 S核糖体结构。这也是一种方法，是核心的新疗法，为人类疾病的发展，无论是在商业和学术环境。我们的目标是使研究人员能够生成比现有方法更好的原子模型。这将导致更有洞察力的生物学解释和更好的药物对抗人类疾病。自动化方法的发展将使研究人员从耗时的手动解释数据和模型中解放出来。总的来说，这些进步将节省数千名研究人员的时间，并使晶体学技术更加先进。 不太专业的生物学家也能接触到。 晶体结构解的最后阶段需要根据实验衍射数据优化原子模型。我们的目标是生成一个模型，最好地描述了晶体的内容，主要是由身份，位置和原子的均方位移建模。正是这些原子模型被解释为理解生物功能，并且是设计新疗法的基础。开发产生改进模型的方法将对这两项重要的研究任务产生积极影响。通过引入参数化模型的新方法，将有可能在阻碍当前方法的数据分辨率限制下生成鲁棒和准确的模型。通过在模型优化中使用额外的信息，包括来自Rosetta结构建模系统的能量函数，将有可能生成更准确的模型，为随后的解释提供更好的基础。 所有这些算法都将在Phenix系统的背景下开发，用于集成和自动化晶体学。Phenix的基础组件将得到扩展，以支持新的结构解决方案，改进和验证方法。与Phenix团队的其他研究人员合作对整个项目的成功至关重要。由现代软件开发环境支持的协作促进了算法的紧密集成，然后可以应用这些算法来解决常见问题。此外，在一致的环境中提供各种方法，可以促进它们的重用，以解决新问题。因此，Phenix团队能够共同非常快速地制作原型，并为研究人员提供新方法。