Rosetta predictions in CASP5: Successes, failures, and prospects for complete automation

Rosetta predictions in CASP5: Successes, failures, and prospects for complete automation
复制标题

DOI:
10.1002/prot.10552
复制
发表时间:
2003-01-01
影响因子:
2.9
通讯作者:
Baker, D
Baker, D
中科院分区:
生物学4区
文献类型:
--
作者:
Bradley, P;Chivian, D;Baker, D

文献摘要

被引文献

相似文献

我们使用Rosetta描述了对CASP5靶点结构的预测。Rosetta片段插入协议用于生成与已知结构的蛋白质没有可检测序列相似性的整个目标结构域的模型,并在结构模板可用的情况下构建长环插入(以及N和c端延伸)。对于从头预测和长环插入都获得了令人鼓舞的结果;我们在此描述当前改进罗塞塔方法的努力的成功和失败。特别是,对于被错误解析为结构域的大蛋白质和具有结构域之间片段交换的拓扑复杂(高接触阶)蛋白质,从头开始预测失败。然而,对于剩余的目标,五个提交的模型中至少有一个具有与天然结构显著相似的长片段。CASP5协议的全自动版本产生的结果与大多数靶标的人工辅助预测相当,这表明自动化的基因组尺度,从头开始的蛋白质结构预测可能很快是值得的。对于人类辅助预测明显更接近原生结构的三个目标,我们确定了仍然需要自动化的步骤。(C) 2003 Wiley-Liss, Inc。
We describe predictions of the structures of CASP5 targets using Rosetta. The Rosetta fragment insertion protocol was used to generate models for entire target domains without detectable sequence similarity to a protein of known structure and to build long loop insertions (and N- and C-terminal extensions) in cases where a structural template was available. Encouraging results were obtained both for the de novo predictions and for the long loop insertions; we describe here the successes as well as the failures in the context of current efforts to improve the Rosetta method. In particular, de novo predictions failed for large proteins that were incorrectly parsed into domains and for topologically complex (high contact order) proteins with swapping of segments between domains. However, for the remaining targets, at least one of the five submitted models had a long fragment with significant similarity to the native structure. A fully automated version of the CASP5 protocol produced results that were comparable to the human-assisted predictions for most of the targets, suggesting that automated genomic-scale, de novo protein structure prediction may soon be worthwhile. For the three targets where the human-assisted predictions were significantly closer to the native structure, we identify the steps that remain to be automated. (C) 2003 Wiley-Liss, Inc.