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Secondary-structure prediction revisited: Theoretical β-sheet propensity and coil propensity represent structures of amyloids and aid in elucidating phenomena involved in interspecies transmission of prions

机译:再次对二级结构进行预测:理论上的β-折叠倾向和卷曲倾向代表淀粉样蛋白的结构并有助于阐明与inter病毒种间传播有关的现象

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摘要

Prions are unique infectious agents, consisting solely of abnormally-folded prion protein (PrPSc). However, they possess virus-like features, including strain diversity, the ability to adapt to new hosts and to be altered evolutionarily. Because prions lack genetic material (DNA and RNA), these biological phenomena have been attributed to the structural properties of PrPSc. Therefore, many structural models of the structure of PrPSc have been proposed based on the limited structural information available, regardless of the incompatibility with high-resolution structural analysis. Recently hypothesized models consist solely of β-sheets and intervening loops/kinks; i.e. parallel in-register β-sheet and β-solenoid models. Owing to the relative simplicity of these structural models of PrPSc, we hypothesized that numerical conversion of the primary structures with a relevant algorithm would enable quantitative comparison between PrPs of distinct primary structures. We therefore used the theoretical values of β-sheet (Pβ) and random-coil (Pc) propensity calculated by secondary structure prediction with a neural network, to analyze interspecies transmission of prions. By reviewing experiments in the literature, we ascertained the biological relevance of Pβ and Pc and found that these classical parameters surprisingly carry substantial information of amyloid structures. We also demonstrated how these parameters could aid in interpreting and explaining phenomena in interspecies transmissions. Our approach can lead to the development of a versatile tool for investigating not only prions but also other amyloids.
机译:ions病毒是独特的感染因子,仅由异常折叠的病毒蛋白(PrP Sc )组成。但是,它们具有类似于病毒的特征,包括菌株多样性,适应新宿主的能力以及可以进化改变的能力。由于病毒缺乏遗传物质(DNA和RNA),因此这些生物学现象归因于PrP Sc 的结构特性。因此,基于有限的可用结构信息,已经提出了许多PrP Sc 结构的结构模型,而与高分辨率结构分析不兼容。最近假设的模型仅由β-折叠和中间环/扭结组成。即平行配准的β-折叠和β-电磁位模型。由于这些PrP Sc 结构模型的相对简单性,我们假设采用相关算法对一级结构进行数值转换将能够对不同一级结构的PrP之间进行定量比较。因此,我们使用通过神经网络的二级结构预测所计算出的β-sheet(Pβ)和随机线圈(Pc)倾向的理论值来分析病毒的种间传播。通过回顾文献中的实验,我们确定了Pβ和Pc的生物学相关性,发现这些经典参数出人意料地携带了淀粉样蛋白结构的大量信息。我们还演示了这些参数如何帮助解释和解释种间传播中的现象。我们的方法可以导致开发一种多功能的工具,该工具不仅可以研究病毒,还可以研究其他淀粉样蛋白。

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  • 期刊名称 other
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  • 年(卷),期 -1(12),2
  • 年度 -1
  • 页码 e0171974
  • 总页数 18
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