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Automatic model building & refinement in crystallography

Automatic model building & refinement in crystallography
自动模型构建
批准号:
6625736
负责人:
Victor S. Lamzin
金额:
$15.88万
依托单位国家:
美国
项目类别:
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-05-01 至 2006-04-30

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中文摘要
翻译
描述(由申请人提供):蛋白质结构倡议 (结构基因组学)旨在了解蛋白质的结构和功能 和蛋白质家族,创造知识,将需要利用 丰富的生物医学应用。获得结构的主要方法 结构基因组学所必需的是大分子X射线晶体学。为 结构基因组学要取得成功,重要的是要拥有方法, 允许快速、大规模、自动的结构测定。本 一项研究提案旨在扩展阿普/wARP软件,以实现高质量 在大分子晶体学中的自动化模型构建和细化。这 将导致对自动化和高吞吐量的重大贡献, 是上述项目和目标所必需的。 传统上,研究科学家必须建立一个分子模型, 实验上可用的电子密度图( 分子),这项任务往往繁琐,时间要求高,主观和沉重 依靠经验。然后,初始大分子模型经历 细化过程,其中模型的参数被调整到最佳 符合实验数据和立体化学预期。为模型 改进,电子密度图也得到改进,并且可以得到更好的模型。 合身因此,模型构建和细化是相关的,并且是紧密相连的 相互联系,应视为一个统一的过程。阿普/WARP 我们希望进一步开发的软件可使上述程序完全自动化 从而产生更快、有效、客观和可靠的技术, 传统的程序。 我们计划开发改进的新算法,用于模型重新参数化, 三维空间模式识别,提高自动化程度 初始大分子模型的建立。遗传算法,蒙特卡罗 技术和半定规划将被利用,以帮助获得 一个更完整、更准确的模型。图形用户界面和数据库, 通过万维网提供的文件服务将有助于 生物学社区,更具体地说,结构基因组学中心, 更好地利用开发的软件。
英文摘要
DESCRIPTION (provided by applicant): The Protein Structure Initiative (Structural Genomics) aims to understand the structure and function of proteins and protein families, creating the knowledge that will need to be exploited for a wealth of biomedical applications. The main method to obtain the structures necessary for Structural Genomics is macromolecular X-ray crystallography. For Structural Genomics to succeed, it is important to possess methodology that allows rapid, large scale, automatic structure determination. The present research proposal aims to extend the ARP/wARP software for high-quality automated model building and refinement in macromolecular crystallography. This will lead to a major contribution towards automation and high-throughput which are necessary for the above projects and objectives. Traditionally, a research scientist has to build a molecular model into the experimentally available electron density map (the three-dimensional image of the molecule), a task often tedious, time demanding, subjective and heavily relying on experience. The initial macromolecular model then undergoes a refinement procedure in which the parameters of the model are adjusted to best fit the experimental data and stereochemical expectations. As the model improves, the electron density maps improve as well and a better model may be fitted. Model building and refinement are therefore related and tightly linked to each other, and should be regarded as one unified process. The ARP/wARP software, which we wish to further develop, fully automates the above procedure resulting in a faster, efficient, objective and reliable technique compared to traditional procedures. We plan to develop improved new algorithms for model re-parameterization and pattern recognition in three-dimensional space to improve the automated building of the initial macromolecular model. Genetic algorithms, Monte Carlo techniques and semi-definite programming will be exploited to aid in obtaining a more complete and accurate model. A graphical user interface and database and documentation service through the World Wide Web will help the structural biology community and more specifically the Structural Genomics centers to better exploit the developed software.
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