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Dead-End Elimination with Backbone Flexibility

机译:具有骨干灵活性的死角消除

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摘要

Motivation: Dead-End Elimination (DEE) is a powerful algorithm capable of reducing the search space for structure-based protein design by a combinatorial factor. By using a fixed backbone template, a rotamer library, and a potential energy function, DEE identifies and prunes rotamer choices that are provably not part of the Global Minimum Energy Conformation (GMEC), effectively eliminating the majority of the conformations that must be subsequently enumerated to obtain the GMEC. Since a fixed-backbone model biases the algorithm predictions against protein sequences for which even small backbone movements may result in a significantly enhanced stability, the incorporation of backbone flexibility can improve the accuracy of the design predictions. If explicit backbone flexibility is incorporated into the model, however, the traditional DEE criteria can no longer guarantee that the flexible-backbone GMEC, the lowest-energy conformation when the backbone is allowed to flex, will not be pruned.
机译:动机:末端消除法(DEE)是一种功能强大的算法,能够通过组合因素来减少基于结构的蛋白质设计的搜索空间。通过使用固定的主干模板,旋转异构体库和势能函数,DEE可以识别和修剪旋转异构体选择,这些选择被证明不是全球最低能量构象(GMEC)的一部分,从而有效消除了随后必须枚举的大多数构象获得GMEC。由于固定骨干模型将算法预测与蛋白质序列相抵触,对于蛋白质序列而言,即使很小的骨架移动也可能导致稳定性显着提高,因此引入骨架弹性可以提高设计预测的准确性。但是,如果将显式的主干灵活性纳入模型中,则传统的DEE标准将无法再保证不会修剪柔性骨干GMEC(允许主干弯曲时能量最低的构象)。

著录项

  • 来源
    《Bioinformatics》 |2007年第13期|i185-i194|共10页
  • 作者单位

    Department of Computer Science Duke University and;

    Department of Biochemistry Duke University Medical Center Durham NC 27708 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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