首页> 美国卫生研究院文献>PLoS Computational Biology >Prediction of Amyloidogenic and Disordered Regions in Protein Chains
【2h】

Prediction of Amyloidogenic and Disordered Regions in Protein Chains

机译:预测蛋白质链中淀粉样蛋白生成和无序区域

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

The determination of factors that influence protein conformational changes is very important for the identification of potentially amyloidogenic and disordered regions in polypeptide chains. In our work we introduce a new parameter, mean packing density, to detect both amyloidogenic and disordered regions in a protein sequence. It has been shown that regions with strong expected packing density are responsible for amyloid formation. Our predictions are consistent with known disease-related amyloidogenic regions for eight of 12 amyloid-forming proteins and peptides in which the positions of amyloidogenic regions have been revealed experimentally. Our findings support the concept that the mechanism of amyloid fibril formation is similar for different peptides and proteins. Moreover, we have demonstrated that regions with weak expected packing density are responsible for the appearance of disordered regions. Our method has been tested on datasets of globular proteins and long disordered protein segments, and it shows improved performance over other widely used methods. Thus, we demonstrate that the expected packing density is a useful value with which one can predict both intrinsically disordered and amyloidogenic regions of a protein based on sequence alone. Our results are important for understanding the structural characteristics of protein folding and misfolding.
机译:确定影响蛋白质构象变化的因素对于鉴定多肽链中潜在的淀粉样蛋白和无序区域非常重要。在我们的工作中,我们引入了一个新参数,即平均堆积密度,以检测蛋白质序列中的淀粉样蛋白生成区和无序区。已经显示具有强烈预期堆积密度的区域负责淀粉样蛋白的形成。我们的预测与已知的与疾病相关的淀粉样蛋白形成区域的12种淀粉样蛋白形成蛋白和肽中的8种一致,其中已经通过实验揭示了淀粉样蛋白形成区域的位置。我们的发现支持这样的概念,即淀粉样蛋白原纤维形成的机制对于不同的肽和蛋白质是相似的。此外,我们证明了预期堆积密度较弱的区域是造成无序区域的原因。我们的方法已经在球状蛋白和长期无序蛋白片段的数据集上进行了测试,与其他广泛使用的方法相比,它的性能有所提高。因此,我们证明了预期的堆积密度是一个有用的值,利用它可以仅基于序列来预测蛋白质的固有无序和淀粉样生成区域。我们的结果对于理解蛋白质折叠和错误折叠的结构特征很重要。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号