Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.
Bioinformatics. 2011 Dec 15;27(24):3371-8. doi: 10.1093/bioinformatics/btr572. Epub 2011 Oct 12.
Manual inspection has been applied to and is well accepted for assessing critical assessment of protein structure prediction (CASP) free modeling (FM) category predictions over the years. Such manual assessment requires expertise and significant time investment, yet has the problems of being subjective and unable to differentiate models of similar quality. It is beneficial to incorporate the ideas behind manual inspection to an automatic score system, which could provide objective and reproducible assessment of structure models.
Inspired by our experience in CASP9 FM category assessment, we developed an automatic superimposition independent method named Quality Control Score (QCS) for structure prediction assessment. QCS captures both global and local structural features, with emphasis on global topology. We applied this method to all FM targets from CASP9, and overall the results showed the best agreement with Manual Inspection Scores among automatic prediction assessment methods previously applied in CASPs, such as Global Distance Test Total Score (GDT_TS) and Contact Score (CS). As one of the important components to guide our assessment of CASP9 FM category predictions, this method correlates well with other scoring methods and yet is able to reveal good-quality models that are missed by GDT_TS.
The script for QCS calculation is available at http://prodata.swmed.edu/QCS/.
Supplementary data are available at Bioinformatics online.
多年来，手动检查一直被用于评估蛋白质结构预测的无模型（FM）类别预测，并得到了广泛认可。这种手动评估需要专业知识和大量的时间投入，但存在主观性和无法区分相似质量模型的问题。将手动检查背后的思想纳入自动评分系统是有益的，这可以为结构模型提供客观和可重复的评估。
受我们在 CASP9 FM 类别评估方面经验的启发，我们开发了一种名为质量控制评分（QCS）的自动叠加独立方法，用于结构预测评估。QCS 同时捕捉全局和局部结构特征，重点关注全局拓扑。我们将该方法应用于 CASP9 的所有 FM 目标，结果总体上与之前在 CASP 中应用的自动预测评估方法（如全局距离测试总得分（GDT_TS）和接触得分（CS））与手动检查得分的一致性最好。作为指导我们评估 CASP9 FM 类别预测的重要组成部分之一，该方法与其他评分方法相关性良好，但能够发现 GDT_TS 遗漏的高质量模型。
QCS 计算脚本可在 http://prodata.swmed.edu/QCS/ 获得。
补充数据可在“Bioinformatics”在线获取。
