Protein-protein docking using region-based 3D Zernike descriptors.
Protein-protein docking using region-based 3D Zernike descriptors.
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DOI：
10.1186/1471-2105-10-407
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发表时间：
2009-12-09
影响因子：
3
通讯作者：
Kihara D
中科院分区：
文献类型：
--
作者：
Venkatraman V;Yang YD;Sael L;Kihara D
蛋白质-蛋白质相互作用是许多生物过程的关键组成部分，并介导多种功能。因此，了解蛋白质复合体的三级结构对于理解相互作用机制至关重要。然而，用实验技术来解决络合物的结构往往是困难的。为此，计算蛋白质-蛋白质对接方法可以提供一个有用的替代方案来解决这个问题。对接构象的预测依赖于有效捕获参与蛋白质形状特征的方法，同时适当考虑可能发生的构象变化。我们提出了一种基于使用三维泽尼克描述符作为分子形状区域特征的新型蛋白质对接算法。使用这些描述符的主要动机是它们对变换的不变性，以及局部表面形状特征的紧凑表示。对接诱饵使用几何散列生成，然后通过评分函数进行排序，该评分函数包含埋藏表面积和基于与3D Zernike形状描述相关的法线的新型几何互补项。我们的对接算法在ZDOCK基准2.0数据集中对绑定和未绑定的情况进行了测试。在74%的定界对接预测中，我们的方法能够在前1000名中找到接近原生的解（界面C-αRMSD≤2.5 Å）。对于非绑定对接，在我们算法返回至少一次命中的60个复合体中，60%的案例排在前2000名之内。与现有的基于形状的对接算法比较表明，该方法在非绑定对接情况下具有更好的性能，而在绑定对接情况下仍具有竞争力。我们首次证明了三维Zernike描述符善于捕捉蛋白质-蛋白质界面的形状互补性，并有助于蛋白质对接预测。严格的基准研究表明，与现有方法相比，我们的对接方法具有优越的性能。
Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.
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影响因子：
3
作者：
Eyal, E;Najmanovich, R;Sobolev, V
通讯作者：
Sobolev, V
影响因子：
5.6
作者：
Gabb, HA;Jackson, RM;Sternberg, MJE
通讯作者：
Sternberg, MJE
DOI：
10.1002/prot.10390
发表时间：
2003-07-01
期刊：
PROTEINS-STRUCTURE FUNCTION AND GENETICS
影响因子：
--
作者：
Chen, R;Mintseris, J;Weng, ZP
通讯作者：
Weng, ZP
影响因子：
2.9
作者：
Andrusier, Nelly;Mashiach, Efrat;Nussinov, Ruth;Wolfson, Haim J.
通讯作者：
Wolfson, Haim J.
影响因子：
2.9
作者：
Chen, R;Li, L;Weng, ZP
通讯作者：
Weng, ZP