Lee Gyu Rie, Heo Lim, Seok Chaok
Department of Chemistry, Seoul National University, Seoul, Republic of Korea.
Proteins. 2018 Mar;86 Suppl 1:168-176. doi: 10.1002/prot.25404. Epub 2017 Oct 26.
Advances in protein model refinement techniques are required as diverse sources of protein structure information are available from low-resolution experiments or informatics-based computations such as cryo-EM, NMR, homology models, or predicted residue contacts. Given semi-reliable or incomplete structural information, structure quality of a protein model has to be improved by ab initio methods such as energy-based simulation. In this study, we describe a new automatic refinement server method designed to improve locally inaccurate regions and overall structure simultaneously. Locally inaccurate regions may occur in protein structures due to non-convergent or missing information in template structures used in homology modeling or due to intrinsic structural flexibilities not resolved by experimental techniques. However, such variable or dynamic regions often play important functional roles by participating in interactions with other biomolecules or in transitions between different functional states. The new refinement method introduced here utilizes diverse types of geometric operators which drive both local and global changes, and the effect of structure changes and relaxations are accumulated. This resulted in consistent refinement of both local and global structural features. Performance of this method in CASP12 is discussed.
由于可从低分辨率实验或基于信息学的计算(如冷冻电镜、核磁共振、同源模型或预测的残基接触)中获得多种蛋白质结构信息源,因此需要改进蛋白质模型优化技术。鉴于结构信息半可靠或不完整,蛋白质模型的结构质量必须通过基于能量模拟等从头算方法来提高。在本研究中,我们描述了一种新的自动优化服务器方法,旨在同时改善局部不准确区域和整体结构。局部不准确区域可能由于同源建模中使用的模板结构信息不收敛或缺失,或者由于实验技术未解决的内在结构灵活性而出现在蛋白质结构中。然而,这些可变或动态区域通常通过参与与其他生物分子的相互作用或不同功能状态之间的转变而发挥重要的功能作用。这里介绍的新优化方法利用了驱动局部和全局变化的多种几何算子,并且结构变化和松弛的效果会累积起来。这导致局部和全局结构特征都得到一致的优化。讨论了该方法在CASP12中的性能。