Methods for estimation of model accuracy in CASP12
Methods for estimation of model accuracy in CASP12
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DOI：
10.1002/prot.25395
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发表时间：
2018-03-01
影响因子：
2.9
通讯作者：
Wallner, Bjorn
中科院分区：
文献类型：
--
作者：
Elofsson, Arne;Joo, Keehyoung;Wallner, Bjorn
可靠地估计蛋白质3D模型质量的方法是生命科学家广泛采用和认真接受蛋白质结构预测的重要驱动力。在这篇文章中，CASP 12中最成功的小组描述了他们最新的模型准确度（EMA）估计方法。我们发现，自CASP 11以来，纯单模型精度估计方法已经显示出明显的进步; 3种顶级方法（MESHI，ProQ 3，SVMQA）都优于CASP 11的顶级方法（ProQ 2）。虽然纯单模型精度估计方法在模型选择方面优于准单模型（ModFOLD 6变体）和一致性方法（Pcons，ModFOLDclust 2，Pcomb-domain和Wallner），但在绝对模型质量估计和局部质量预测方面仍然不如这些方法。最后，我们表明，当使用基于接触的模型质量的措施（CAD，lDDT）的单一模型质量的方法执行相对更好。
Methods to reliably estimate the quality of 3D models of proteins are essential drivers for the wide adoption and serious acceptance of protein structure predictions by life scientists. In this article, the most successful groups in CASP12 describe their latest methods for estimates of model accuracy (EMA). We show that pure single model accuracy estimation methods have shown clear progress since CASP11; the 3 top methods (MESHI, ProQ3, SVMQA) all perform better than the top method of CASP11 (ProQ2). Although the pure single model accuracy estimation methods outperform quasi-single (ModFOLD6 variations) and consensus methods (Pcons, ModFOLDclust2, Pcomb-domain, and Wallner) in model selection, they are still not as good as those methods in absolute model quality estimation and predictions of local quality. Finally, we show that when using contact-based model quality measures (CAD, lDDT) the single model quality methods perform relatively better.