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TASSER_2.0的基准测试:一种具有更准确预测接触限制的改进型蛋白质结构预测算法。

Benchmarking of TASSER_2.0: an improved protein structure prediction algorithm with more accurate predicted contact restraints.

作者信息

Lee Seung Yup, Skolnick Jeffrey

机构信息

Center for the Study of Systems Biology, Georgia Institute of Technology, Atlanta, Georgia 30318, USA.

出版信息

Biophys J. 2008 Aug;95(4):1956-64. doi: 10.1529/biophysj.108.129759. Epub 2008 May 16.

DOI:10.1529/biophysj.108.129759
PMID:18487301
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2483784/
Abstract

To improve tertiary structure predictions of more difficult targets, the next generation of TASSER, TASSER_2.0, has been developed. TASSER_2.0 incorporates more accurate side-chain contact restraint predictions from a new approach, the composite-sequence method, based on consensus restraints generated by an improved threading algorithm, PROSPECTOR_3.5, which uses computationally evolved and wild-type template sequences as input. TASSER_2.0 was tested on a large-scale, benchmark set of 2591 nonhomologous, single domain proteins < or =200 residues that cover the Protein Data Bank at 35% pairwise sequence identity. Compared with the average fraction of accurately predicted side-chain contacts of 0.37 using PROSPECTOR_3.5 with wild-type template sequences, the average accuracy of the composite-sequence method increases to 0.60. The resulting TASSER_2.0 models are closer to their native structures, with an average root mean-square deviation of 4.99 A compared to the 5.31 A result of TASSER. Defining a successful prediction as a model with a root mean-square deviation to native <6.5 A, the success rate of TASSER_2.0 (TASSER) for Medium targets (targets with good templates/poor alignments) is 74.3% (64.7%) and 40.8% (35.5%) for the Hard targets (incorrect templates/alignments). For Easy targets (good templates/alignments), the success rate slightly increases from 86.3% to 88.4%.

摘要

为了改进对更具挑战性目标的三级结构预测,已经开发了下一代TASSER,即TASSER_2.0。TASSER_2.0采用了一种新方法——复合序列法,纳入了更准确的侧链接触限制预测,该方法基于一种改进的穿线算法PROSPECTOR_3.5生成的一致性限制,PROSPECTOR_3.5使用经过计算进化的和野生型模板序列作为输入。TASSER_2.0在一组大规模的、由2591个非同源单结构域蛋白质组成的基准集上进行了测试,这些蛋白质的残基数量≤200个,它们以35%的成对序列同一性覆盖了蛋白质数据库。与使用野生型模板序列的PROSPECTOR_3.5准确预测侧链接触的平均比例0.37相比,复合序列法的平均准确率提高到了0.60。由此得到的TASSER_2.

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本文引用的文献

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