Protein-RNA complexes and efficient automatic docking: expanding RosettaDock possibilities.
Protein-RNA complexes and efficient automatic docking: expanding RosettaDock possibilities.
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DOI：
10.1371/journal.pone.0108928
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Bernauer J
中科院分区：
文献类型：
--
作者：
Guilhot-Gaudeffroy A;Froidevaux C;Azé J;Bernauer J
蛋白质-RNA复合物在细胞中提供广泛的基本功能。他们的原子实验结构的解决，尽管至关重要的理解这些功能，往往是困难和昂贵的。已经开发的用于蛋白质的对接方法通常具有挑战性，以适应RNA，因为其固有的灵活性和可用的结构数据相对稀缺。在这项研究中，我们在核苷酸和原子水平上对蛋白质-RNA复合物采用了RosettaDock方案。使用基于遗传算法的策略和非冗余蛋白质-RNA数据集，我们推导出RosettaDock评分方案，该方案不仅能够区分而且能够有效地对对接诱饵进行评分。该方法被证明是有效的和强大的生成和识别合适的结构时，应用到两个蛋白质-RNA对接基准在绑定和未绑定的设置。它也与现有的战略相比较。这是目前第一种集成在完整对接套件中的多级优化评分方法，引领了自适应完全灵活的策略。
Protein-RNA complexes provide a wide range of essential functions in the cell. Their atomic experimental structure solving, despite essential to the understanding of these functions, is often difficult and expensive. Docking approaches that have been developed for proteins are often challenging to adapt for RNA because of its inherent flexibility and the structural data available being relatively scarce. In this study we adapted the RosettaDock protocol for protein-RNA complexes both at the nucleotide and atomic levels. Using a genetic algorithm-based strategy, and a non-redundant protein-RNA dataset, we derived a RosettaDock scoring scheme able not only to discriminate but also score efficiently docking decoys. The approach proved to be both efficient and robust for generating and identifying suitable structures when applied to two protein-RNA docking benchmarks in both bound and unbound settings. It also compares well to existing strategies. This is the first approach that currently offers a multi-level optimized scoring approach integrated in a full docking suite, leading the way to adaptive fully flexible strategies.
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