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中文摘要
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描述(由申请人提供):结构生物学,特别是蛋白质结构计划,旨在了解大分子及其复合物和家族的结构和功能,为进一步探索丰富的生物医学应用创造知识。x射线晶体学通过提供感兴趣的生物分子的详细原子模型,已成为协助研究生物现象的最常用方法。为了最大限度地提高x射线晶体学的效率,蛋白质结构测定中劳动密集型重复性任务的自动化是至关重要的。因此,在电子密度图中建立原子模型的步骤必须快速、可靠和高度自动化。ARP/wARP软件开创了这一自动化步骤,并帮助获得大量新的大分子结构。在过去三年中,ARP/wARP的科学发展主要由NIH资助,标志着整个软件包的显著进步。已开发的算法和科学概念允许构建更完整的模型,并扩展对低分辨率电子密度图的解释。通过图形用户界面和基于www的远程提交任务的执行,该软件对非专业研究人员来说变得更容易使用。在速度和收敛性方面,ARP/wARP软件的整体性能得到了提高。在申请续期的过程中,我们将把项目的目标扩展到大分子3-D结构测定的无缝自动化,同时我们将提供更完整、更有效的模型,并降低实验衍射数据的分辨率。我们将通过进一步发展基于模式识别的算法来实现我们的目标;加强结构确定各步骤之间的联系,重点是大型和多聚体结构;提供真正完整的模型,包括无序的表面区域,特别强调构建结合配体;开发一个“专家控制系统”,能够根据积累的历史进行基本决策;并通过社区继续改进软件的可访问性。
英文摘要
DESCRIPTION (provided by applicant): Structural Biology in general and the Protein Structure Initiative in particular, aim to understand the structure and function of macromolecules, their complexes and families, creating a knowledge that is further explored for a wealth of biomedical applications. X-ray crystallography has become the most commonly used method to assist the investigation into biological phenomena by providing detailed atomic models of the bio- molecules of interest. To maximize the efficiency of X-ray crystallography, automation of labor intensive, repetitive tasks in protein structure determination is crucial. As such, the step of building an atomic model in the electron density map has to be made fast, reliable and highly automated. The ARP/wARP software has pioneered this automation step and helped to obtain a large number of novel structures of macromolecules. Scientific developments in ARP/wARP, mostly funded by the NIH over the last three years, landmarked considerable advancement of the overall software package. The developed algorithms and scientific concepts allow construction of more complete models and to extend the interpretation of lower resolution electron density maps. The software became easier to use for non-expert researchers via graphical user interfaces and WWW-based execution of remotely submitted tasks. The overall performance of the ARP/wARP software in terms of speed and convergence was improved. In the course of the requested renewal of the grant we will extend the aims of the project towards seamless automation of macromolecular 3-D structure determination, while we will deliver more complete and validated models with lower resolution of the experimental diffraction data. We will achieve our goals by developing further the pattern recognition-based algorithms; improving interlinks between different steps of structure determination with emphasis to large and multimeric structures; delivering truly complete models including poorly ordered surface regions, with special emphasis to building bound ligands; developing an 'expert control system' that would be capable of basic decision making based on the accumulated history; and by continuing to improve the accessibility of the software by the community.
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Automatic model building & refinement in crystallography
Unified automated model building & refinement for biological crystallography
Automatic model building & refinement in crystallography
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