Structure prediction for CABP7 targets using extensive all-atom refinement with Rosetta@home
Structure prediction for CABP7 targets using extensive all-atom refinement with Rosetta@home
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DOI：
10.1002/prot.21636
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发表时间：
2007-01-01
影响因子：
2.9
通讯作者：
Baker, David
中科院分区：
文献类型：
--
作者：
Das, Rhiju;Bin Qian;Baker, David
我们描述了使用Rosetta结构预测方法对基于模板的建模和自由建模类别进行的预测，这是对蛋白质结构预测技术的第七次批判性评估。首次可以针对大多数目标进行积极的采样和全原子改进，这是由Rosetta@ Home分布式计算网络启用的提前。使用迭代改进算法的基于模板的建模预测改善了大多数蛋白质少于200个残基的最佳现有模板。自由建模方法对所有二级结构类别的100个残基的几个靶标提供了几乎原子的准确性预测。这些结果表明，通过全原子能量函数的改进，尽管计算昂贵，但它是获得准确结构预测的有力方法。
We describe predictions made using the Rosetta structure prediction methodology for both template-based modeling and free modeling categories in the Seventh Critical Assessment Of Techniques for Protein Structure Prediction. For the first time, aggressive sampling and all-atom refinement could be carried out for the majority of targets, an advance enabled by the Rosetta@ home distributed computing network. Template-based modeling predictions using an iterative refinement algorithm improved over the best existing templates for the majority of proteins with less than 200 residues. Free modeling methods gave near-atomic accuracy predictions for several targets under 100 residues from all secondary structure classes. These results indicate that refinement with an all-atom energy function, although computationally expensive, is a powerful method for obtaining accurate structure predictions.