arXiv 1609.067432016-09-21q-bio.BM

5D旋转流形上基于广义傅立叶变换的蛋白质对接

Protein-protein docking by generalized Fourier transforms on 5D rotational manifolds

Dmitry Padhorny, Andrey Kazennov, Brandon S. Zerbe, Kathryn Porter, Bing Xia, Scott E. Mortadella, Yaroslav Kholodov, David W. Ritchie, Sandor Vajda, Dima Kozakov

发表信息：: Proc Natl Acad Sci U S A. 2016 Jul 26;113(30):E4286-93
DOI：: 10.1073/pnas.1603929113

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摘要：

使用快速傅立叶变换的能量评估能够对数十亿个假定的复杂结构进行采样，从而彻底改变了刚性蛋白质-蛋白质对接。然而，在当前的方法中，有效的加速仅在平移或旋转子空间中实现。开发一种将基于FFT的采样扩展到5个旋转坐标的高效且准确的对接方法是一个被广泛研究但仍未解决的问题。这里提出的算法保留了早期方法的准确性，但产生至少十倍的加速。这一改进得益于两项创新。首先，将搜索空间视为乘积流形$\mathbf{SO(3)x(SO(3)\setminus S^1)}$，其中$\mathbf{SO(3)}$是表示旋转配体空间的旋转群，而$\mathbf{(SO(3)\setminus S^1)}$是由两个欧拉角所跨越的空间，这两个欧拉角定义了从固定受体中心到配体中心的向量的方向。该表示使得能够使用为$\mathbf{SO(3)}$开发的高效FFT方法。其次，我们选择的中心高度密集的集群对接结构，而不是最低的能量构象，作为预测的复杂性，因此没有必要非常高的准确性，在能源评估。因此，在傅立叶空间中使用有限数量的球面基函数就足够了，这在保持对接结果的准确性的同时提高了采样效率。该方法的一个主要优点是，与经典方法相比，增加相关函数项的数量在计算上是便宜的，这使得能够使用复杂的能量函数进行评分。

英文摘要：

Energy evaluation using fast Fourier transforms enables sampling billions of putative complex structures and hence revolutionized rigid protein-protein docking. However, in current methods efficient acceleration is achieved only in either the translational or the rotational subspace. Developing an efficient and accurate docking method that expands FFT based sampling to 5 rotational coordinates is an extensively studied but still unsolved problem. The algorithm presented here retains the accuracy of earlier methods but yields at least tenfold speedup. The improvement is due to two innovations. First, the search space is treated as the product manifold $\mathbf{SO(3)x(SO(3)\setminus S^1)}$, where $\mathbf{SO(3)}$ is the rotation group representing the space of the rotating ligand, and $\mathbf{(SO(3)\setminus S^1)}$ is the space spanned by the two Euler angles that define the orientation of the vector from the center of the fixed receptor toward the center of the ligand. This representation enables the use of efficient FFT methods developed for $\mathbf{SO(3)}$. Second, we select the centers of highly populated clusters of docked structures, rather than the lowest energy conformations, as predictions of the complex, and hence there is no need for very high accuracy in energy evaluation. Therefore it is sufficient to use a limited number of spherical basis functions in the Fourier space, which increases the efficiency of sampling while retaining the accuracy of docking results. A major advantage of the method is that, in contrast to classical approaches, increasing the number of correlation function terms is computationally inexpensive, which enables using complex energy functions for scoring.

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。

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