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Global mapping and multivariate analysis of protein and nucleic acid conformational spaces.

机译:蛋白质和核酸构象空间的全局作图和多变量分析。

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摘要

In this thesis, multivariate analysis tools are used to analyze and intuitively understand the clustering behavior of the conformations of biological macromolecules, namely of nucleic acids and proteins. Each unit of these polymers, depending on the type of physical representation chosen to describe the molecular structure, (i.e. angles, Cartesian coordinates, etc.) must be described by many degrees of freedom (in multidimensional space). In order to study the conformations of all but the shortest segments of these linear polymers, techniques of multivariate analysis must be used to reduce the dimensions, to visualize, and to compare the features of available experimental structures.; We have developed a method for visualization and analysis which we describe as "global mapping" which employs multidimensional scaling (MDS). MDS has its origins in the field of psychology and belongs to a family of principal component analysis (PCA) methods which allow multivariate data to be represented by a reduced number of dimensions.; In the first portion of this thesis, the protein conformational space is mapped at the level of short peptides from high resolution protein structures. The initial goal was to create a Ramachandran-like map for short peptides, rather than single pairs of &phis;-psi angles. Hence we developed the concept of higher order (fragments several &phis;-psi pairs in length) the (&phis;-psi) n map. To accomplish this, angular distance information and MDS are used to cluster the peptide fragments in a three dimensional space.; In proteins the simplest conformational unit of structure is the single &phis;-psi pair represented by a tripeptide. A &phis;-psi plot can pictorially describe the conformation of an entire protein via the short tripeptide fragments. In nucleic acids the analogous unit is the dinucleoside monophosphate (DMP). As we will be describe later in further detail, the complete description of the DMP unit requires as many as ten torsion angles. To visualize the conformational space of DMP units, RNA and DNA (free and protein/drug bound) were mapped using high resolution crystal structures catalogued in the Nucleic Acid Database (NDB). The mapping of the conformational space reveals nine primary clusters which distinguish among the common A, B and Z forms and their various substates, plus seven secondary clusters for kinked or bent structures.
机译:本文使用多元分析工具来分析和直观理解生物大分子,即核酸和蛋白质构象的聚类行为。这些聚合物的每个单元,取决于选择用来描述分子结构的物理表示形式(即角度,笛卡尔坐标等),必须以许多自由度(在多维空间中)描述。为了研究这些线性聚合物中除最短链段以外的所有链段的构象,必须使用多元分析技术来减小尺寸,可视化并比较可用实验结构的特征。我们已经开发出一种可视化和分析的方法,我们将其描述为采用多维缩放(MDS)的“全局映射”。 MDS起源于心理学领域,属于主成分分析(PCA)方法系列,该方法允许用减少的维数表示多元数据。在本论文的第一部分中,蛋白质构象空间被映射到来自高分辨率蛋白质结构的短肽水平。最初的目标是为短肽而不是单对φ-psi角创建类似Ramachandran的图。因此,我们提出了高阶(φ-psi对长度为片段)(φ-psi)n图的概念。为此,使用角距离信息和MDS将肽片段聚类在三维空间中。在蛋白质中,最简单的结构构象单位是由三肽表示的单个φ-psi对。 φ-psi图可以通过短的三肽片段以图形方式描述整个蛋白质的构象。在核酸中,类似的单位是二磷酸核苷(DMP)。正如我们将在后面更详细地描述的那样,DMP单元的完整描述需要多达十个扭转角。为了可视化DMP单元的构象空间,使用在核酸数据库(NDB)中分类的高分辨率晶体结构绘制了RNA和DNA(游离的和结合了蛋白质/药物的图)。构象空间的映射揭示了九个主要簇,它们区分了常见的A,B和Z形式及其各种子状态,另外还有七个次要簇用于扭结或弯曲结构。

著录项

  • 作者

    Sims, Gregory Evan.;

  • 作者单位

    University of California, Berkeley.;

  • 授予单位 University of California, Berkeley.;
  • 学科 Biophysics General.; Chemistry Biochemistry.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 117 p.
  • 总页数 117
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物物理学;生物化学;
  • 关键词

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