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在蛋白质结构预测技术评估第7轮(CASP7)中,I-TASSER基于模板的建模和自由建模。

Template-based modeling and free modeling by I-TASSER in CASP7.

作者信息

Zhang Yang

机构信息

Center for Bioinformatics, Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, USA.

出版信息

Proteins. 2007;69 Suppl 8:108-17. doi: 10.1002/prot.21702.

Abstract

We developed and tested the I-TASSER protein structure prediction algorithm in the CASP7 experiment, where targets are first threaded through the PDB library and continuous fragments in the threading alignments are exploited to assemble the global structure. The final models are obtained from the progressive refinements started from the last round structure clusters. A majority of the targets in the template-based modeling (TBM) category have the templates drawn closer to the native structure by more than 1 A within the aligned regions. For the free-modeling (FM) targets, I-TASSER builds correct topology for 7/19 cases with sequence up to 155 residues long. For the first time, the automated server prediction generates models as good as the human-expert does in all the categories, which shows the robustness of the method and the potential of the application to genome-wide structure prediction. Despite the success, the accuracy of I-TASSER modeling is still dominated by the similarity of the template and target structures with a strong correlation coefficient ( approximately 0.9) between the root-mean-squared deviation (RMSD) to native of the templates and the final models. Especially, there is no high-resolution model below 2 A for the FM targets. These problems highlight the issues that need to be addressed in the next generation of atomic-level I-TASSER development especially for the FM target modeling.

摘要

我们在蛋白质结构预测技术评估第7轮(CASP7)实验中开发并测试了I-TASSER蛋白质结构预测算法。在该实验中,首先将目标序列与蛋白质数据库(PDB)库进行穿线比对,然后利用比对结果中的连续片段来组装全局结构。最终模型是通过对上一轮结构聚类结果进行逐步优化得到的。在基于模板的建模(TBM)类别中,大多数目标在比对区域内的模板与天然结构的距离拉近超过1埃。对于自由建模(FM)目标,I-TASSER在19个序列长度达155个残基的案例中,为其中7个构建了正确的拓扑结构。自动化服务器预测首次在所有类别中生成了与人类专家预测效果相当的模型,这表明了该方法的稳健性以及在全基因组结构预测中的应用潜力。尽管取得了成功,但I-TASSER建模的准确性仍然主要取决于模板与目标结构的相似性,模板与天然结构的均方根偏差(RMSD)和最终模型之间的相关系数很高(约为0.9)。特别是,对于FM目标,没有低于2埃的高分辨率模型。这些问题凸显了在下一代原子水平的I-TASSER开发中,尤其是针对FM目标建模需要解决的问题。

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