Automated protein model building combined with iterative structure refinement
Automated protein model building combined with iterative structure refinement
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DOI：
10.1038/8263
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发表时间：
1999-05-01
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影响因子：
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通讯作者：
Lamzin, VS
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文献类型：
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作者：
Perrakis, A;Morris, R;Lamzin, VS
在蛋白质晶体学中，通常需要花费大量的时间和精力从可解释的电子密度图中追踪初始模型，并对其进行优化，直到它与晶体学数据最一致。在这里，我们提出了一种自动构建和改进蛋白质模型的方法，无需用户干预，从衍射数据开始扩展到分辨率高于2.3埃和合理的晶体相估计。该方法基于一个迭代过程，该过程将电子密度图描述为一组未连接的原子，然后搜索蛋白质样模式。自动模式识别（模型构建）与细化相结合，允许在几个CPU小时内可靠地获得结构模型。我们展示了一些最近解决的结构的例子的方法的力量。
In protein crystallography, much time and effort are often required to trace an initial model from an interpretable electron density map and to refine it until it best agrees with the crystallographic data. Here, we present a method to build and refine a protein model automatically and without user intervention, starting from diffraction data extending to resolution higher than 2.3 Angstrom and reasonable estimates of crystallographic phases. The method is based on an iterative procedure that describes the electron density map as a set of unconnected atoms and then searches for protein-like patterns. Automatic pattern recognition (model building) combined with refinement, allows a structural model to be obtained reliably within a few CPU hours. We demonstrate the power of the method with examples of a few recently solved structures.