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Algorithms for analysis of NMR projections: Design, implementation and applications

机译:用于分析核磁共振预测的算法:设计,实施和应用

摘要

With an increasing rate of protein expressions the need for fast protein characterization has become more important. Protein NMR has long been an important contributor for protein characterization; being one of a few techniques that can study proteins at atomic resolution in their native state. Whitin recent years faster experimental and processing methods have emerged that are now becoming routine. This thesis describes algorithms for automatic backbone assignment and validation of structure information by using projection experiments together with a decomposition method. Projection experiments reduce measurement time for multidimensional spectra thus making it possible to obtain very high dimensional spectral information in a fraction of the time required for a conventional experiment. By combining different experiments backbone, side chain and NOE information can be obtained. A set of software tools for automatic backbone characterization where developed from the implementation of different algorithms in conjunction with different proteins and projection experiments. Testing and refinement of the different tools resulted in a robust characterization method well suited for different proteins. Possible future projects are expanding the methods to side chain and structure determination making the characterization more complete.
机译:随着蛋白质表达速率的增加,对快速蛋白质表征的需求变得越来越重要。长期以来,蛋白质NMR一直是蛋白质表征的重要因素。是可以在天然状态下以原子分辨率研究蛋白质的少数技术之一。 Whitin近年来出现了越来越快的实验和处理方法,如今已成为常规方法。本文介绍了通过投影实验和分解方法来进行自动骨干分配和结构信息验证的算法。投影实验减少了多维光谱的测量时间,因此有可能在传统实验所需时间的一小部分中获得非常高维的光谱信息。通过组合不同的实验骨架,可以获得侧链和NOE信息。一组用于自动骨干特征分析的软件工具,是通过实施不同算法并结合不同蛋白质和投影实验而开发的。对不同工具的测试和完善导致了非常适合不同蛋白质的强大表征方法。可能的未来项目正在将方法扩展到侧链和结构确定,从而使表征更加完整。

著录项

  • 作者

    Fredriksson Jonas;

  • 作者单位
  • 年度 2011
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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