arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv physics/0207039physics.bio-phcond-mat.softq-bio.BM
收藏

模式蛋白质的结构空间--主成分分析

Structure Space of Model Proteins --A Principle Component Analysis

Mehdi Yahyanejad, Mehran Kardar, Chao Tang

摘要:

本文研究二维正方形格点上所有紧结构的空间,格点大小为$N=6\times6$。根据疏水模型,将每个结构映射到$N$维度的载体上。以前的工作表明,结构的可设计性是密切相关的分布在$N$维空间中的结构矢量,与高度可设计的结构主要发现在低密度区域。我们使用主成分分析来探测和表征结构向量的分布,并发现一个不均匀的单峰密度。有趣的是,该峰的主轴几乎与傅立叶本征向量对齐,并且对应的傅立叶本征值在交替模式($q=π$)的波数处连续地变为零。这些观察提供了一个垫脚石的结构点的分布的分析描述,并打开了通过简单的傅立叶变换的疏水性相应的序列的可能性,估计现实结构的可设计性。

英文摘要:

We study the space of all compact structures on a two-dimensional square lattice of size $N=6\times6$. Each structure is mapped onto a vector in $N$-dimensions according to a hydrophobic model. Previous work has shown that the designabilities of structures are closely related to the distribution of the structure vectors in the $N$-dimensional space, with highly designable structures predominantly found in low density regions. We use principal component analysis to probe and characterize the distribution of structure vectors, and find a non-uniform density with a single peak. Interestingly, the principal axes of this peak are almost aligned with Fourier eigenvectors, and the corresponding Fourier eigenvalues go to zero continuously at the wave-number for alternating patterns ($q=π$). These observations provide a stepping stone for an analytic description of the distribution of structural points, and open the possibility of estimating designabilities of realistic structures by simply Fourier transforming the hydrophobicities of the corresponding sequences.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑