Protein Structure Refinement Guided by Atomic Packing Frustration Analysis
Protein Structure Refinement Guided by Atomic Packing Frustration Analysis
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DOI：
10.1021/acs.jpcb.0c06719
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发表时间：
2020-12-03
影响因子：
3.3
通讯作者：
Wolynes, Peter G.
中科院分区：
文献类型：
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作者：
Chen, Mingchen;Chen, Xun;Wolynes, Peter G.
机器学习、生物信息学和对折叠问题的理解的最新进展使得能够以中等精度有效地预测蛋白质结构，即使对于从模板中获得的信息很少的目标也是如此。全原子分子动力学模拟提供了一种改进这种预测结构的方法，但无指导的原子模拟，即使时间很长，也往往无法消除不正确的结构特征，这些结构特征会阻止结构变得更具能量优势，因为需要进行大规模运动，并克服侧链重新堆积的能量障碍。在这项研究中，我们表明，通过检查当站点的本地环境改变时发生的能量变化的统计数据，在原子分辨率下定位包装挫折感，允许人们识别最可能的错误联系的位置。使用各种算法预测的结构中原子分辨率受挫的全球统计数据，在对先前CASP实验中的20个目标的数据库进行测试时，提供了结构质量的强有力指标。定位较正确的残基比定位较差的残基受挫程度更小。这些观测提供了对预测结构的全局和局部质量的诊断，因此可以作为对20个目标的全原子精细化模拟的指导。结果表明，原子堆积受挫引导的精细化模拟是非常有效的，并显著提高了结构的质量。
Recent advances in machine learning, bioinformatics, and the understanding of the folding problem have enabled efficient predictions of protein structures with moderate accuracy, even for targets where there is little information from templates. All-atom molecular dynamics simulations provide a route to refine such predicted structures, but unguided atomistic simulations, even when lengthy in time, often fail to eliminate incorrect structural features that would prevent the structure from becoming more energetically favorable owing to the necessity of making large scale motions and to overcoming energy barriers for side chain repacking. In this study, we show that localizing packing frustration at atomic resolution by examining the statistics of the energetic changes that occur when the local environment of a site is changed allows one to identify the most likely locations of incorrect contacts. The global statistics of atomic resolution frustration in structures that have been predicted using various algorithms provide strong indicators of structural quality when tested over a database of 20 targets from previous CASP experiments. Residues that are more correctly located turn out to be more minimally frustrated than more poorly positioned sites. These observations provide a diagnosis of both global and local quality of predicted structures and thus can be used as guidance in all-atom refinement simulations of the 20 targets. Refinement simulations guided by atomic packing frustration turn out to be quite efficient and significantly improve the quality of the structures.