Blavatnik School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel.
Proteins. 2011 Sep;79(9):2607-23. doi: 10.1002/prot.23082. Epub 2011 Jun 30.
Symmetric protein complexes are abundant in the living cell. Predicting their atomic structure can shed light on the mechanism of many important biological processes. Symmetric docking methods aim to predict the structure of these complexes given the unbound structure of a single monomer, or its model. Symmetry constraints reduce the search-space of these methods and make the prediction easier compared to asymmetric protein-protein docking. However, the challenge of modeling the conformational changes that the monomer might undergo is a major obstacle. In this article, we present SymmRef, a novel method for refinement and reranking of symmetric docking solutions. The method models backbone and side-chain movements and optimizes the rigid-body orientations of the monomers. The backbone movements are modeled by normal modes minimization and the conformations of the side-chains are modeled by selecting optimal rotamers. Since solved structures of symmetric multimers show asymmetric side-chain conformations, we do not use symmetry constraints in the side-chain optimization procedure. The refined models are re-ranked according to an energy score. We tested the method on a benchmark of unbound docking challenges. The results show that the method significantly improves the accuracy and the ranking of symmetric rigid docking solutions. SymmRef is available for download at http:// bioinfo3d.cs.tau.ac.il/SymmRef/download.html.
对称蛋白质复合物在活细胞中大量存在。预测它们的原子结构可以揭示许多重要生物学过程的机制。对称对接方法旨在预测这些复合物的结构,给定单个单体的未结合结构,或其模型。对称约束减少了这些方法的搜索空间,使预测相对于不对称蛋白质-蛋白质对接更容易。然而,建模单体可能经历的构象变化的挑战是一个主要障碍。在本文中,我们提出了 SymmRef,这是一种用于对称对接解决方案的精化和重新排序的新方法。该方法对骨架和侧链运动进行建模,并优化单体的刚体取向。骨架运动通过标准模态最小化进行建模,侧链构象通过选择最佳的扭转异构体进行建模。由于对称多聚体的已解决结构显示出不对称的侧链构象,因此我们不在侧链优化过程中使用对称约束。经过优化的模型根据能量得分进行重新排序。我们在未结合对接挑战基准测试中测试了该方法。结果表明,该方法显著提高了对称刚性对接解决方案的准确性和排名。SymmRef 可在 http://bioinfo3d.cs.tau.ac.il/SymmRef/download.html 下载。