I-TASSER server for protein 3D structure prediction
I-TASSER server for protein 3D structure prediction
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DOI：
10.1186/1471-2105-9-40
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发表时间：
2008-01-23
影响因子：
3
通讯作者：
Zhang, Yang
中科院分区：
文献类型：
--
作者：
Zhang, Yang
背景资料：从氨基酸序列预测蛋白质的三维结构是计算结构生物学中最重要的问题之一。社区范围内的结构预测关键评估（CASP）实验旨在对该领域的最新技术进行客观评估，其中I-TASSER被评为最近第七届CASP实验服务器部分的最佳方法。从那时起，我们的实验室已经收到了大量的请求有关的公共可用性的I-TASSER算法和使用的I-TASSER predictions.Results：一个在线版本的I-TASSER开发在KU中心的生物信息学已经产生的蛋白质结构预测数以千计的建模请求从超过35个国家。引入了基于多线程模板的相对聚类结构密度和共识显著性得分的评分函数（C-score）来估计I-TASSER预测的准确性。大规模的基准测试表明，第一个模型的C-分数和TM-分数（一种结构相似性测量，值在[0，1]中）之间具有很强的相关性，相关系数为0.91。当C-score> -1.5时，模型的假阳性率和假阴性率均小于0.1。结合C-score和蛋白质长度，I-TASSER模型的准确性可以预测，TM-score的平均误差为0.08，RMSD的平均误差为2埃。结论：I-TASSER服务器已开发用于生成自动化全长3D蛋白质结构预测，其中基准评分系统可帮助用户获得I-TASSER模型的定量评估。每个查询的I-TASSER服务器的输出包括多达五个全长模型、置信度分数、估计的TM分数和RMSD以及估计的标准差。I-TASSER服务器可在http://zhang.bioinformatics.ku.edu/I-TASSER上免费提供给学术界。
Background: Prediction of 3-dimensional protein structures from amino acid sequences represents one of the most important problems in computational structural biology. The community-wide Critical Assessment of Structure Prediction ( CASP) experiments have been designed to obtain an objective assessment of the state-of-the-art of the field, where I-TASSER was ranked as the best method in the server section of the recent 7th CASP experiment. Our laboratory has since then received numerous requests about the public availability of the I-TASSER algorithm and the usage of the I-TASSER predictions.Results: An on-line version of I-TASSER is developed at the KU Center for Bioinformatics which has generated protein structure predictions for thousands of modeling requests from more than 35 countries. A scoring function (C-score) based on the relative clustering structural density and the consensus significance score of multiple threading templates is introduced to estimate the accuracy of the I-TASSER predictions. A large-scale benchmark test demonstrates a strong correlation between the C-score and the TM-score ( a structural similarity measurement with values in [0, 1]) of the first models with a correlation coefficient of 0.91. Using a C-score cutoff > -1.5 for the models of correct topology, both false positive and false negative rates are below 0.1.Combining C-score and protein length, the accuracy of the I-TASSER models can be predicted with an average error of 0.08 for TM-score and 2 angstrom for RMSD. Conclusion: The I-TASSER server has been developed to generate automated full-length 3D protein structural predictions where the benchmarked scoring system helps users to obtain quantitative assessments of the I-TASSER models. The output of the I-TASSER server for each query includes up to five full-length models, the confidence score, the estimated TM-score and RMSD, and the standard deviation of the estimations. The I-TASSER server is freely available to the academic community at http://zhang.bioinformatics.ku.edu/I-TASSER.