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首页> 外文期刊>Proteins: Structure, Function, and Genetics >Present and future challenges and limitations in protein-protein docking.
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Present and future challenges and limitations in protein-protein docking.

机译:蛋白质对接的当前和未来挑战与局限性。

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The study of protein-protein interactions that are involved in essential life processes can largely benefit from the recent upraising of computational docking approaches. Predicting the structure of a protein-protein complex from their separate components is still a highly challenging task, but the field is rapidly improving. Recent advances in sampling algorithms and rigid-body scoring functions allow to produce, at least for some cases, high quality docking models that are perfectly suitable for biological and functional annotations, as it has been shown in the CAPRI blind tests. However, important challenges still remain in docking prediction. For example, in cases with significant mobility, such as multidomain proteins, fully unrestricted rigid-body docking approaches are clearly insufficient so they need to be combined with restraints derived from domain-domain linker residues, evolutionary information, or binding site predictions. Other challenging cases are weak or transient interactions, such as those between proteins involved in electron transfer, where the existence of alternative bound orientations and encounter complexes complicates the binding energy landscape. Docking methods also struggle when using in silico structural models for the interacting subunits. Bringing these challenges to a practical point of view, we have studied here the limitations of our docking and energy-based scoring approach, and have analyzed different parameters to overcome the limitations and improve the docking performance. For that, we have used the standard benchmark and some practical cases from CAPRI. Based on these results, we have devised a protocol to estimate the success of a given docking run.
机译:生命过程中涉及的蛋白质-蛋白质相互作用的研究可以极大地受益于最近计算对接方法的提高。从它们各自的组分预测蛋白质-蛋白质复合物的结构仍然是一项艰巨的任务,但是这一领域正在迅速发展。采样算法和刚体评分功能的最新进展使得至少在某些情况下可以生成高质量的对接模型,该模型非常适合于生物学和功能注释,如CAPRI盲测所示。但是,对接预测仍然面临重要挑战。例如,在具有显着移动性的情况下(例如多域蛋白),完全不受限制的刚体对接方法显然不足,因此需要将它们与源自域域接头残基,进化信息或结合位点预测的限制结合起来。其他具有挑战性的情况是弱的或短暂的相互作用,例如参与电子转移的蛋白质之间的相互作用,其中存在替代的结合方向并遇到复合物,使结合能格局复杂化。当将计算机结构模型用于相互作用的亚基时,对接方法也很困难。为了将这些挑战付诸实践,我们在这里研究了对接和基于能量的评分方法的局限性,并分析了各种参数来克服这些局限性并提高对接性能。为此,我们使用了CAPRI的标准基准和一些实际案例。基于这些结果,我们设计了一种协议来估计给定对接运行的成功。

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