Yang Jianyi, Wang Yan, Zhang Yang
School of Mathematical Sciences, Nankai University, Tianjin 300071, China; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
J Mol Biol. 2016 Feb 22;428(4):693-701. doi: 10.1016/j.jmb.2015.09.024. Epub 2015 Oct 3.
Computer-based structure prediction becomes a major tool to provide large-scale structure models for annotating biological function of proteins. Information of residue-level accuracy and thermal mobility (or B-factor), which is critical to decide how biologists utilize the predicted models, is however missed in most structure prediction pipelines. We developed ResQ for unified residue-level model quality and B-factor estimations by combining local structure assembly variations with sequence-based and structure-based profiling. ResQ was tested on 635 non-redundant proteins with structure models generated by I-TASSER, where the average difference between estimated and observed distance errors is 1.4Å for the confidently modeled proteins. ResQ was further tested on structure decoys from CASP9-11 experiments, where the error of local structure quality prediction is consistently lower than or comparable to other state-of-the-art predictors. Finally, ResQ B-factor profile was used to assist molecular replacement, which resulted in successful solutions on several proteins that could not be solved from constant B-factor settings.
基于计算机的结构预测成为为注释蛋白质生物学功能提供大规模结构模型的主要工具。然而,在大多数结构预测流程中,缺少对决定生物学家如何利用预测模型至关重要的残基水平准确性和热迁移率(或B因子)信息。我们开发了ResQ,通过结合局部结构组装变异与基于序列和基于结构的分析,对残基水平的模型质量和B因子进行统一估计。ResQ在由I-TASSER生成结构模型的635个非冗余蛋白质上进行了测试,对于可靠建模的蛋白质,估计距离误差与观察距离误差之间的平均差异为1.4埃。ResQ在CASP9 - 11实验的结构诱饵上进一步测试,其中局部结构质量预测的误差始终低于或与其他最先进的预测器相当。最后,ResQ B因子分布图用于辅助分子置换,在几个无法从恒定B因子设置中解决的蛋白质上获得了成功的解决方案。