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Novel Computational Methods for Modeling Backbone Flexibility and Improving Side-Chain Prediction for Protein Design Applications.

机译:用于建模骨干柔韧性和改善蛋白质设计应用的侧链预测的新型计算方法。

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摘要

The primary objective of this work is to develop and validate a novel form of protein design, termed "Plastic protein design" or "Plasticity", to improve side-chain predictions for protein engineering efforts. Traditionally, computational protein design assumes that the protein backbone remains fixed during design. Ostensibly, this simplifies the computation significantly by removing the degrees of freedom associated with perturbing the backbone. However, since protein design necessarily involves considering alternate primary sequences, modeling backbone changes becomes necessary in order to sample realistic protein backbone conformations for these alternate primary sequences.;This manuscript presents several computational landmarks in the development of the Plastic protein design algorithm. First, the Plastic protein design methodology is discussed, implemented, and evaluated for so-called "global" and "local" scoring schemes. The limitations of these scoring approaches are discussed. Second, a study in the effectiveness of modeling proteins as structural ensembles is presented and discussed. Plasticity depends very heavily on the reliability of structural ensembles to sample backbone space that is compatible with real primary sequences, so this study has direct implications for Plastic protein design. Third, an application of multiple-template protein design involving redesigning green fluorescent protein (GFP) to function as a programmable biosensor against pathogens is discussed. One significant aim of computational research involves testing its applicability to real experimental problems. The biosensor project is an ideal candidate for this aim because preliminary data suggests that one source of error in the GFP biosensor design process concerns failure to model multiple states of the GFP chromophore maturation pathway. Lastly, a project involving the creation of a sophisticated graphical user interface (GUI) for the Rosetta modeling suite, named "InteractiveROSETTA", is presented. The final chapter discusses some future direction for both the Plastic protein design project and the InteractiveROSETTA project.
机译:这项工作的主要目的是开发和验证一种新型的蛋白质设计形式,称为“塑料蛋白质设计”或“可塑性”,以改善蛋白质工程工作的侧链预测。传统上,计算蛋白质设计假定蛋白质骨架在设计过程中保持固定。表面上,通过消除与干扰主干相关的自由度,这大大简化了计算。但是,由于蛋白质设计必然涉及考虑替代的主要序列,因此对骨架变化进行建模就很有必要,以便为这些替代的主要序列采样现实的蛋白质主链构象。该手稿提出了塑性蛋白质设计算法开发中的几个计算里程碑。首先,针对所谓的“全局”和“局部”评分方案,讨论,实施和评估了塑料蛋白质设计方法。讨论了这些评分方法的局限性。其次,提出并讨论了将蛋白质建模为结构集成体的有效性的研究。可塑性在很大程度上取决于结构整体对样本骨架空间的可靠性,该可靠性与真实的一级序列兼容,因此,本研究对塑性蛋白质设计具有直接的意义。第三,讨论了多模板蛋白设计的应用,其中涉及重新设计绿色荧光蛋白(GFP)以用作针对病原体的可编程生物传感器。计算研究的一个重要目标涉及测试其对实际实验问题的适用性。生物传感器项目是实现此目标的理想人选,因为初步数据表明,GFP生物传感器设计过程中的一个错误来源涉及对GFP生色团成熟途径的多个状态建模的失败。最后,介绍了一个项目,该项目涉及为Rosetta建模套件创建复杂的图形用户界面(GUI),名为“ InteractiveROSETTA”。最后一章讨论了塑料蛋白质设计项目和InteractiveROSETTA项目的未来方向。

著录项

  • 作者单位

    Rensselaer Polytechnic Institute.;

  • 授予单位 Rensselaer Polytechnic Institute.;
  • 学科 Bioinformatics.;Biomedical engineering.;Biochemistry.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 111 p.
  • 总页数 111
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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