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Geometrical eigen-subspace framework based molecular conformation representation for efficient structure recognition and comparison

机译:基于几何特征 - 子空间框架的分子构象表示,以实现高效结构识别和比较

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We have developed an extended distance matrix approach to study the molecular geometric configuration through spectral decomposition. It is shown that the positions of all atoms in the eigen-space can be specified precisely by their eigen-coordinates, while the refined atomic eigen-subspace projection array adopted in our approach is demonstrated to be a competent invariant in structure comparison. Furthermore, a visual eigen-subspace projection function (EPF) is derived to characterize the surrounding configuration of an atom naturally. A complete set of atomic EPFs constitute an intrinsic representation of molecular conformation, based on which the interatomic EPF distance and intermolecular EPF distance can be reasonably defined. Exemplified with a few cases, the intermolecular EPF distance shows exceptional rationality and efficiency in structure recognition and comparison. Published by AIP Publishing.
机译:我们开发了一种扩展距离矩阵方法来研究通过光谱分解来研究分子几何构型。 结果表明,可以通过其特征坐标精确地指定特征空间中的所有原子的位置,而我们方法采用的精制原子特征 - 子空间投影阵列被证明是结构比较中的主管不变。 此外,导出了一种视觉eIGen-subspace投影功能(EPF)以使自然的原子的周围配置表征。 一组完整的原子EPFS构成了分子构象的内在表示,基于该分子构象的内在表示,基于该分子构型和分子间距离可以合理地定义。 举例说明了少数情况,分子间EPF距离显示了结构识别和比较的特殊合理性和效率。 通过AIP发布发布。

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