Zhang Yang, Skolnick Jeffrey
Center of Excellence in Bioinformatics, University at Buffalo, Buffalo, New York 14203, USA.
Proteins. 2004 Dec 1;57(4):702-10. doi: 10.1002/prot.20264.
We have developed a new scoring function, the template modeling score (TM-score), to assess the quality of protein structure templates and predicted full-length models by extending the approaches used in Global Distance Test (GDT)1 and MaxSub.2 First, a protein size-dependent scale is exploited to eliminate the inherent protein size dependence of the previous scores and appropriately account for random protein structure pairs. Second, rather than setting specific distance cutoffs and calculating only the fractions with errors below the cutoff, all residue pairs in alignment/modeling are evaluated in the proposed score. For comparison of various scoring functions, we have constructed a large-scale benchmark set of structure templates for 1489 small to medium size proteins using the threading program PROSPECTOR_3 and built the full-length models using MODELLER and TASSER. The TM-score of the initial threading alignments, compared to the GDT and MaxSub scoring functions, shows a much stronger correlation to the quality of the final full-length models. The TM-score is further exploited as an assessment of all 'new fold' targets in the recent CASP5 experiment and shows a close coincidence with the results of human-expert visual assessment. These data suggest that the TM-score is a useful complement to the fully automated assessment of protein structure predictions. The executable program of TM-score is freely downloadable at http://bioinformatics.buffalo.edu/TM-score.
我们开发了一种新的评分函数——模板建模得分(TM-score),通过扩展全局距离测试(GDT)[1]和MaxSub[2]中使用的方法来评估蛋白质结构模板和预测的全长模型的质量。首先,利用一种依赖于蛋白质大小的量表来消除先前得分中固有的对蛋白质大小的依赖性,并适当考虑随机的蛋白质结构对。其次,在所提出的得分中,不是设置特定的距离截止值并仅计算误差低于截止值的部分,而是对比对/建模中的所有残基对进行评估。为了比较各种评分函数,我们使用穿线程序PROSPECTOR_3为1489个中小规模蛋白质构建了一个大规模的结构模板基准集,并使用MODELLER和TASSER构建了全长模型。与GDT和MaxSub评分函数相比,初始穿线比对的TM-score与最终全长模型的质量显示出更强的相关性。在最近的CASP5实验中,TM-score进一步被用作对所有“新折叠”目标的评估,并与人类专家的视觉评估结果显示出密切的一致性。这些数据表明,TM-score是对蛋白质结构预测的全自动评估的有用补充。TM-score的可执行程序可从http://bioinformatics.buffalo.edu/TM-score免费下载。