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Geometric and topological methods in protein structure analysis.

机译:蛋白质结构分析中的几何和拓扑方法。

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摘要

With the recent success of the Human Genome Project, one of the main challenges in molecular biology in this post-genomic era is the determination and exploitation of the three-dimensional structure of proteins and their function. The ability for proteins to perform their numerous functions is made possible by the diversity of their three-dimensional structures. Hence, to attack the key problems involved, such as protein folding and docking, geometry and topology become important tools. Despite their essential roles, geometric and topological methods are relatively uncommon in computational biology, partly due to a number of modeling and algorithmic challenges. This thesis describes efficient computational methods for describing and comparing molecular structures by combining both geometric and topological approaches.; In particular, in the first part of the thesis, we study three geometric descriptions: (i) the writhing number of protein backbones, which measures how many times a backbone coils around itself; (ii) the level-of-details representation of protein backbones via simplification, which helps to extract main features of backbones; and (iii) the elevation of molecular surfaces, which we propose to identify geometric features such as protrusions and cavities from protein surfaces. We develop efficient algorithms for computing these descriptions.; The second part of the thesis focuses on molecular shape matching algorithms. By modeling a molecule as the union of balls, we propose algorithms to compute the similarity between two such unions by (variants of) the widely used Hausdorff distance. We also study the protein docking problem, which, from a geometric perspective, can be considered as the problem of searching for configurations with maximum complementarity between two molecular surfaces. Using the feature information computed from the elevation function, we describe an efficient algorithm to find promising initial relative placements of the proteins.
机译:随着人类基因组计划的最新成功,这个后基因组时代分子生物学的主要挑战之一是蛋白质的三维结构及其功能的确定和利用。蛋白质三维结构的多样性使蛋白质具有执行多种功能的能力。因此,要解决涉及的关键问题,例如蛋白质折叠和对接,几何结构和拓扑就成为重要的工具。尽管几何和拓扑方法起着至关重要的作用,但它们在计算生物学中相对较少见,部分原因是许多建模和算法挑战。本文介绍了结合几何和拓扑方法描述和比较分子结构的有效计算方法。特别是,在论文的第一部分,我们研究了三种几何描述:(i)蛋白质骨架的数量,该数量测量骨架绕其自身缠绕的次数; (ii)通过简化来详细描述蛋白质骨架的细节水平,这有助于提取骨架的主要特征; (iii)分子表面的高度,我们建议识别分子表面的几何特征,例如蛋白质表面的凸起和空洞。我们开发了用于计算这些描述的有效算法。本文的第二部分着重于分子形状匹配算法。通过将分子建模为球的并集,我们提出了通过广泛使用的Hausdorff距离(的变数)来计算两个此类并集之间相似度的算法。我们还研究了蛋白质对接问题,从几何学的角度来看,可以将其视为寻找两个分子表面之间具有最大互补性的构型的问题。使用从高程函数计算的特征信息,我们描述了一种有效的算法,可以找到有希望的蛋白质初始相对位置。

著录项

  • 作者

    Wang, Yusu.;

  • 作者单位

    Duke University.;

  • 授予单位 Duke University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 161 p.
  • 总页数 161
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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