Nugent Timothy, Cozzetto Domenico, Jones David T
Department of Computer Science Bioinformatics Group, University College London, London, WC1E 6BT, United Kingdom.
Proteins. 2014 Feb;82 Suppl 2(Suppl 2):98-111. doi: 10.1002/prot.24377. Epub 2014 Jan 3.
Here we report on the assessment results of the third experiment to evaluate the state of the art in protein model refinement, where participants were invited to improve the accuracy of initial protein models for 27 targets. Using an array of complementary evaluation measures, we find that five groups performed better than the naïve (null) method-a marked improvement over CASP9, although only three were significantly better. The leading groups also demonstrated the ability to consistently improve both backbone and side chain positioning, while other groups reliably enhanced other aspects of protein physicality. The top-ranked group succeeded in improving the backbone conformation in almost 90% of targets, suggesting a strategy that for the first time in CASP refinement is successful in a clear majority of cases. A number of issues remain unsolved: the majority of groups still fail to improve the quality of the starting models; even successful groups are only able to make modest improvements; and no prediction is more similar to the native structure than to the starting model. Successful refinement attempts also often go unrecognized, as suggested by the relatively larger improvements when predictions not submitted as model 1 are also considered.
在此,我们报告第三次实验的评估结果,该实验旨在评估蛋白质模型优化的当前技术水平,实验邀请参与者提高27个目标的初始蛋白质模型的准确性。通过一系列互补的评估方法,我们发现有五组的表现优于朴素(空值)方法——与CASP9相比有显著改进,尽管只有三组显著更好。领先的小组还展示了持续改进主链和侧链定位的能力,而其他小组可靠地增强了蛋白质物理性质的其他方面。排名第一的小组成功地在近90%的目标中改善了主链构象,这表明在CASP优化中首次有一种策略在绝大多数情况下取得了成功。仍有一些问题未得到解决:大多数小组仍未能提高起始模型的质量;即使是成功的小组也只能取得适度的改进;并且没有预测比起始模型更类似于天然结构。成功的优化尝试也常常未被认可,这从在考虑未作为模型1提交的预测时相对更大的改进中可以看出。