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首页> 外文期刊>Acta crystallographica. Section D, Biological crystallography. >Deformable complex network for refining low-resolution X-ray structures
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Deformable complex network for refining low-resolution X-ray structures

机译：可变形的复杂网络精炼低分辨率x射线结构

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摘要

In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the development of a new refinement algorithm called the deformable complex network (DCN) is reported that combines a novel angular network-based restraint with the DEN model in the target function. Testing of DCN on a wide range of low-resolution structures demonstrated that it constantly leads to significantly improved structural models as judged by multiple refinement criteria, thus representing a new effective refinement tool for low-resolution structural determination.
机译：在大分子x射线晶体学,建筑更精确的原子模型基于低分辨率衍射实验数据仍然存在一个巨大的挑战。可变形弹性网络(穴)模型来帮助低分辨率的结构改进。研究,开发新的细分算法称为变形复杂的网络(宽带)报道,结合了一个新颖的角度基于网络的约束与窝模型目标函数。低分辨率的结构表明,它经常导致显著提高根据多个结构模型细化标准,因此代表了一个新的低分辨率的有效改进工具结构的决心。

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