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A topological measurement of protein compressibility

机译:蛋白质可压缩性的拓扑测量

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In this paper we partially clarify the relation between the compressibility of a protein and its molecular geometric structure. To identify and understand the relevant topological features within a given protein, we model its molecule as an alpha filtration and hence obtain multi-scale insight into the structure of its tunnels and cavities. The persistence diagrams of this alpha filtration capture the sizes and robustness of such tunnels and cavities in a compact and meaningful manner. From these persistence diagrams, we extract a measure of compressibility derived from those topological features whose relevance is suggested by physical and chemical properties. Due to recent advances in combinatorial topology, this measure is efficiently and directly computable from information found in the Protein Data Bank (PDB). Our main result establishes a clear linear correlation between the topological measure and the experimentally-determined compressibility of most proteins for which both PDB information and experimental compressibility data are available. Finally, we establish that both the topological measurement and the linear correlation are stable with respect to small perturbations in the input data, such as those arising from experimental errors in compressibility and X-ray crystallography experiments.
机译:在本文中,我们部分阐明了蛋白质的可压缩性与其分子几何结构之间的关系。为了识别和了解给定蛋白质内的相关拓扑特征,我们将其分子建模为alpha过滤,从而获得对其隧道和空腔结构的多尺度洞察力。该alpha过滤的余辉图以紧凑且有意义的方式捕获了此类隧道和空腔的大小和鲁棒性。从这些持久性图中,我们提取了可压缩性的量度,这些可压缩性源自那些物理和化学性质暗示其相关性的拓扑特征。由于组合拓扑的最新进展,可以从蛋白质数据库(PDB)中找到的信息有效而直接地计算出此度量。我们的主要结果在大多数PDB信息和实验可压缩性数据均可用的大多数蛋白质的拓扑度量与实验确定的可压缩性之间建立了明确的线性相关性。最后,我们确定拓扑测量和线性相关性对于输入数据中的小扰动都是稳定的,例如由于压缩性和X射线晶体学实验中的实验误差引起的扰动。

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