Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan.
Proteins. 2019 Dec;87(12):1263-1275. doi: 10.1002/prot.25759. Epub 2019 Jun 24.
Protein model refinement has been an essential part of successful protein structure prediction. Molecular dynamics simulation-based refinement methods have shown consistent improvement of protein models. There had been progress in the extent of refinement for a few years since the idea of ensemble averaging of sampled conformations emerged. There was little progress in CASP12 because conformational sampling was not sufficiently diverse due to harmonic restraints. During CASP13, a new refinement method was tested that achieved significant improvements over CASP12. The new method intended to address previous bottlenecks in the refinement problem by introducing new features. Flat-bottom harmonic restraints replaced harmonic restraints, sampling was performed iteratively, and a new scoring function and selection criteria were used. The new protocol expanded conformational sampling at reduced computational costs. In addition to overall improvements, some models were refined significantly to near-experimental accuracy.
蛋白质模型的精修一直是成功进行蛋白质结构预测的重要环节。基于分子动力学模拟的精修方法已经证明可以持续改善蛋白质模型。自从出现采样构象的集合平均思想以来，几年来，在精修程度方面已经取得了进展。但是由于调和约束，构象采样不够多样化，在 CASP12 中几乎没有取得进展。在 CASP13 期间，测试了一种新的精修方法，该方法在 CASP12 基础上取得了显著的提高。该新方法旨在通过引入新的特征来解决精修问题中的先前瓶颈。平底调和约束取代了调和约束，迭代进行采样，并且使用了新的评分函数和选择标准。新协议以降低的计算成本扩展了构象采样。除了整体改进之外，一些模型还被显著精修至接近实验精度。
