PROJECT 1 - LAWRENCE BERKELEY LAB - PHENIX

项目 1 - 劳伦斯伯克利实验室 - 凤凰城

• 批准号: 7477053
• 负责人: PAUL Damien ADAMS
• 金额: $ 93.71万
• 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
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7477053
• 关键词: Address; Algorithms; Automation; Biological; Biology; Birth; Classification; Collaborations; Computational algorithm; Computer software; Crystallography; Custom; Data; Data Set; Data Storage and Retrieval; Decision Making; Deposition; Development; Diagnostic; Environment; Foundations; Health; Human; Intervention; Java; Libraries; Location; Manuals; Maps; Measures; Modeling; Nucleic Acids; Peptides; Play; Probability; Process; RNA library; Range; Refit; Reporting; Research Personnel; Resolution; Role; Score; Side; Signal Transduction; Solutions; Speed; Staging; Structure; Surface; System; Testing; Validation; Vertebral column; Visual; Work; Writing; base; graphical user interface; improved; macromolecule; member; open source; programs; tool development

Project I: During the first 5 years of the PHENIX project we have implemented a program for automated analysis of crystallographic data (mmtbx.xtriage), we have developed a highly automated program for anomalous substructure location (HySS), and we have created a new automated structure refinement program (phenix.refine). We have played an essential role in the birth of PHENIX by developing the open source C++ Computational Crystallography Toolbox (cctbx) and the PHENIX graphical user interface (GUI). We have worked closely with the other members of the PHENIX project to create an integrated system for automated structure determination that provides command-line interfaces, a visual programming interface, and the highly automated Wizard interface. We will use our strong foundation of computational algorithms and software to address some of the most challenging bottlenecks remaining in structure determination; classification of experimental data for decisionmaking, substructure location from weak signals, and productive and minimally-biased structure refinement at all resolution ranges. Our new algorithms which automatically assign a probability score to each dataset that describes the likelihood of successful structure solution will be used in subsequent decision-making by Projects II and IV. The result will be an increase in the efficiency of structure solution. The chances of successful substructure location will be improved by new algorithms for automated space group determination, optimal data cutoff calculation, and the application of improved likelihood scoring functions, developed in collaboration with Project III. This unique capability will make it possible for PHENIX to successfully-begin the process of structure solution, where other systems currently fail. We will develop new algorithms, including the use of normal models, for the refinement of models against experimental data at any resolution limit, by using automatic model parameterizations that maintain a reasonable ratio of parameters to observed data. We will also extend structure refinement to include algorithms for the local rebuilding of models, including peptide flips and rotamer refitting, in collaboration with Projects II and V. This approach will speed the convergence of refinement and reduce the need for manual intervention in many cases. Finally, we will enhance the PHENIX software by further development of our cctbx library, the PHENIX GUI, Project Data Storage, and the developer environment. Our new algorithms will enable researchers to determine the structures of challenging, high-value biological macromolecules which are important for understanding biology and ultimately improving human health.

项目I：在PHENIX项目的前5年，我们实施了一项自动化计划 为了分析晶体数据(Mmtbx.xtriage)，我们开发了一个高度自动化的程序 异常子结构定位(HySS)，我们创建了一种新的自动结构细化 程序(henix.finine)。我们在PHENIX的诞生中发挥了至关重要的作用，通过开发开放的 源C++计算晶体工具箱(Cctbx)和PHENIX图形用户界面(GUI)。 我们与PHENIX项目的其他成员密切合作，为 自动确定结构，提供命令行界面、可视化编程界面 以及高度自动化的向导界面。 我们将使用我们强大的计算算法和软件基础来解决一些最 解决结构确定中仍然存在的瓶颈问题；为决策对实验数据进行分类， 从弱信号中定位子结构，以及有效的和最小偏差的结构细化 在所有分辨率范围内。我们的新算法自动为每个数据集分配一个概率分数 这描述了成功的结构解决方案将被用于后续决策的可能性 项目II和IV。其结果将是提高结构解决方案的效率。有多少机会 自动化空间群的新算法将改进成功的子结构定位 确定、最佳数据截止值计算以及改进的似然评分函数的应用， 与Project III合作开发。这一独特的能力将使PHENIX有可能 成功-在其他系统当前失败的情况下，开始结构化解决方案的流程。我们将开发新的 算法，包括正常模型的使用，用于根据任何实验数据改进模型 分辨率限制，通过使用自动模型参数化来保持合理的参数比率 观察到的数据。我们还将扩展结构细化以包括用于局部重建的算法 与项目II和项目V合作，建立包括翻转多肽和改装旋转异构体在内的模型。 加快精细化的收敛速度，在许多情况下减少人工干预的需要。最后， 我们将通过进一步开发我们的cctbx库、PHENIX图形用户界面项目来增强PHENIX软件 数据存储和开发环境。 我们的新算法将使研究人员能够确定具有挑战性的高价值生物的结构 对于理解生物学和最终改善人类健康非常重要的大分子。