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Protein structure prediction and conformational transitions. I. Improvement of protein secondary structure prediction. II. Pathways of conformational transition originating in phosphorylation: A study of CDK2 using targeted molecular dynamics and coarse g

机译:蛋白质结构预测和构象转换。I. 蛋白质二级结构预测的改进。II. 起源于磷酸化的构象转换途径:使用靶向分子动力学和粗 g 的 CDK2 研究

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摘要

There is a critical need for protein structure and function prediction. Accurate protein secondary structure prediction is essential for many bioinformatics applications, including protein tertiary structure prediction. We developed an algorithm (Fragment Data Mining, FDM) for protein secondary structure prediction using fragments of known structures obtained by multiple sequence alignment (MSA). Its performance is excellent where high-score MSA matches are available. By combing it with GOR V, a new Consensus Database Mining (CDM) method was developed, which surpasses the performances of both FDM and GOR V. For each residue, it chooses to use either the result of FDM or GOR V depending upon the availability of high-score matches of MSA. A server has been set up to make CDM publicly accessible. It becomes more popular due to the reliability and efficiency of its performance, the simplicity of its use, and its potential for improvement with the rapidly growing number of determined structures. Phosphorylation is the most important post translational modifications for cellular regulation and signal transduction. Upon phosphorylation, proteins can undergo obvious conformational changes. It is challenging to characterize these changes because of the high flexibility of phosphorylation regions and the difficulties in obtaining diffraction quality crystals. In the current study, we focused on the conformational changes of CDK2 due to phosphorylation at Thr160. We use Cα-Cβ-side chain (CABS) modeling, Targeted Molecular Dynamics (TMD) and conventional molecular dynamics (MD) to simulate the structural transition and create transition pathways. Principal component analysis (PCA) of the trajectories and normal mode analysis (NMA) with anisotropic network model (ANM – an elastic network model) were used for trajectory analysis and performance comparisons. The CABS with appropriate constraint weights and TMD with proper force constants successfully simulated the conformational changes of CDK2 phosphorylation, including the formation of the arginine cluster, maintaining the geometrical relationships of the conserved residues, and the characteristic movement of the active loop (T loop). For conventional MD, we use the CABS modeling and energy optimization to contruct the missing segments lin the structure. CABS is, for the first time, used also to create transition pathways as well as to patch in the segment without determined coordinates. It proved especially valuable in the study of small localized conformational changes. The results show that CABS and TMD are both effective approaches for creating pathways of transitions due to phosphorylation. PCA showed significant overlaps with set of low frequency ANM normal modes. It is possible to explore the mechanisms of phosphorylation-induced conformational changes with these simulation methods and analysis methods.
机译:对蛋白质结构和功能预测的需求非常迫切。准确的蛋白质二级结构预测对于许多生物信息学应用至关重要,包括蛋白质三级结构预测。我们开发了一种算法 (Fragment Data Mining, FDM),用于使用通过多序列比对 (MSA) 获得的已知结构片段进行蛋白质二级结构预测。在高分 MSA 匹配可用的情况下,它的性能非常出色。通过将其与 GOR V 相结合,开发了一种新的共识数据库挖掘 (CDM) 方法,该方法的性能超越了 FDM 和 GOR V。对于每个残基,它选择使用 FDM 或 GOR V 的结果,具体取决于 MSA 的高分匹配的可用性。已设置服务器以使 CDM 可公开访问。由于其性能的可靠性和效率、使用的简单性以及随着确定结构数量的快速增长而改进的潜力,它变得越来越受欢迎。磷酸化是细胞调节和信号转导中最重要的翻译后修饰。磷酸化后,蛋白质会发生明显的构象变化。由于磷酸化区域的高度灵活性和难以获得衍射质量的晶体,表征这些变化具有挑战性。在目前的研究中,我们专注于 CDK2 在 Thr160 位点磷酸化引起的构象变化。我们使用 Cα-Cβ 侧链 (CABS) 建模、靶向分子动力学 (TMD) 和常规分子动力学 (MD) 来模拟结构转变并创建转变途径。轨迹的主成分分析 (PCA) 和各向异性网络模型 (ANM – 一种弹性网络模型) 的法则模式分析 (NMA) 用于轨迹分析和性能比较。具有适当约束权重的 CABS 和具有适当力常数的 TMD 成功模拟了 CDK2 磷酸化的构象变化,包括精氨酸簇的形成、维持保守残基的几何关系以及活性环 (T 环) 的特征运动。对于传统的 MD,我们使用 CABS 建模和能量优化来构建结构中缺失的段。CABS 还首次用于创建过渡路径以及在没有确定坐标的情况下修补线段。事实证明,它在研究微小的局部构象变化方面特别有价值。结果表明,CABS 和 TMD 都是由于磷酸化而产生转换途径的有效方法。PCA 显示与一组低频 ANM 正则模式有显著重叠。使用这些模拟方法和分析方法可以探索磷酸化诱导的构象变化的机制。

著录项

  • 作者

    Cheng, Haitao;

  • 作者单位

    Iowa State University;

  • 授予单位 Iowa State University;
  • 学科 Bioinformatics
  • 学位
  • 年度 2009
  • 页码 146
  • 总页数 146
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Bioinformatics;

    机译:生物信息学;

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