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通过五自由度的快速傅里叶变换加速实现刚体的快速旋转匹配。

Fast rotational matching of rigid bodies by fast Fourier transform acceleration of five degrees of freedom.

作者信息

Kovacs Julio A, Chacón Pablo, Cong Yao, Metwally Essam, Wriggers Willy

机构信息

Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA.

出版信息

Acta Crystallogr D Biol Crystallogr. 2003 Aug;59(Pt 8):1371-6. doi: 10.1107/s0907444903011247. Epub 2003 Jul 23.

Abstract

The 'fast rotational matching' method (an approach to find the three rotational degrees of freedom in matching problems using just one three-dimensional FFT) is extended to the full six-dimensional (rotation and translation) matching scenario between two three-dimensional objects. By recasting this problem into a formulation involving five angles and just one translational parameter, it was possible to accelerate, by means of fast Fourier transforms, five of the six degrees of freedom of the problem. This method was successfully applied to the docking of atomic structures of components into three-dimensional low-resolution density maps. Timing comparisons performed with our method and with 'fast translational matching' (the standard way to accelerate the translational parameters utilizing fast Fourier transforms) demonstrates that the performance gain can reach several orders of magnitude, especially for large map sizes. This gain can be particularly advantageous for spherical- and toroidal-shaped maps, since the scanning range of the translational parameter would be significantly constrained in these cases. The method can also be harnessed to the complementary surface (or 'exterior docking') problem and to pattern recognition in image processing.

摘要

“快速旋转匹配”方法(一种仅使用一次三维快速傅里叶变换来求解匹配问题中三个旋转自由度的方法)被扩展到两个三维物体之间完整的六维(旋转和平移)匹配场景。通过将此问题重新表述为一个涉及五个角度和仅一个平移参数的公式,借助快速傅里叶变换,可以加速该问题六个自由度中的五个。该方法已成功应用于将组件的原子结构对接至三维低分辨率密度图。将我们的方法与“快速平移匹配”(利用快速傅里叶变换加速平移参数的标准方法)进行的计时比较表明,性能提升可达几个数量级,特别是对于大尺寸的图。这种提升对于球形和环形图尤为有利,因为在这些情况下,平移参数的扫描范围会受到显著限制。该方法还可用于互补表面(或“外部对接”)问题以及图像处理中的模式识别。

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