Automated prediction of domain boundaries in CASP6 targets using Ginzu and RosettaDOM
Automated prediction of domain boundaries in CASP6 targets using Ginzu and RosettaDOM
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DOI：
10.1002/prot.20737
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发表时间：
2005-01-01
影响因子：
2.9
通讯作者：
Baker, D
中科院分区：
文献类型：
--
作者：
Kim, DE;Chivian, D;Baker, D
结构域边界预测是实验和计算蛋白质结构表征的重要步骤。我们开发了两种完全自动化的域解析方法：第一种是我们之前描述过的Ginzu，它利用同源序列和结构的信息；第二种是我们之前没有描述过的RosettaDOM，它只使用查询序列中的信息。Ginzu采用先后不太确定的方法，通过同源性对结构和序列族进行迭代分配域。RosettaDOM采用Rosetta de novo结构预测方法建立三维模型，然后采用Taylor基于结构的域分配方法将模型解析为域。在模型中反复观察到的结构域边界被预测为蛋白质的结构域边界。有趣的是，RosettaDOM对通常被认为超出从头结构预测方法范围的大小的蛋白质产生了相当好的结构域预测。对于远程褶皱识别目标和新褶皱，Ginzu和RosettaDOM都取得了令人满意的结果，并且在某些情况下，一种方法无法检测到正确的区域边界，另一种方法可以正确识别。我们在这里描述了使用这两种方法的成功和失败，并讨论了将这两种协议合并到改进的混合方法中的可能性。
Domain boundary prediction is an important step in both experimental and computational protein structure characterization. We have developed two fully automated domain parsing methods: the first, Ginzu, which we have described previously, utilizes information from homologous sequences and structures, while the second, RosettaDOM, which has not been described previously, uses only information in the query sequence. Ginzu iteratively assigns domains by homology to structures and sequence families using successively less confident methods. RosettaDOM uses the Rosetta de novo structure prediction method to build three-dimensional models, and then applies Taylor's structure based domain assignment method to parse the models into domains. Domain boundaries observed repeatedly in the models are predicted to be domain boundaries for the protein. Interestingly, RosettaDOM produced quite good domain predictions for proteins of a size typically considered to be beyond the reach of de novo structure prediction methods. For remote fold recognition targets and new folds, both Ginzu and RosettaDOM produced promising results, and in some cases where one method failed to detect the correct domain boundary, it was correctly identified by the other method. We describe here the successes and failures using both methods, and address the possibility of incorporating both protocols into an improved hybrid method.