Distance geometry generates native-like folds for small helical proteins using the consensus distances of predicted protein structures
Distance geometry generates native-like folds for small helical proteins using the consensus distances of predicted protein structures
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DOI：
10.1002/pro.5560070916
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发表时间：
1998-09-01
期刊：
影响因子：
8
通讯作者：
Ponder, JW
中科院分区：
文献类型：
--
作者：
Huang, ES;Samudrala, R;Ponder, JW
为了成功地从头开始预测蛋白质结构，需要一种方法从包含天然和非天然蛋白质样构象的集合中识别天然样结构。在这方面，当精确的残差间距可用时，使用距离几何显示出希望。我们描述了一种方法，该方法从Simons等人（1997）的方法生成的四个小螺旋蛋白的500个蛋白质样构象中剔除距离几何约束。采用基于共识的方法，测量每个c α间距离，并使用最频繁发生的距离作为距离几何的输入约束。对每个蛋白质构建一个坐标均方根误差低于原集平均值的结构；在三种情况下，折叠的拓扑结构与天然蛋白质的拓扑结构相似。对于基于全原子知识的评分函数，当对折叠集进行过滤以获得最佳评分构象时，剩余的50个结构子集产生了更高精度的约束。使用这些约束进行的第二轮距离几何计算的平均坐标均方根误差为4.38埃。
For successful ab initio protein structure prediction, a method is needed to identify native-like structures from a set containing both native and non-native protein-like conformations. In this regard, the use of distance geometry has shown promise when accurate inter-residue distances are available. We describe a method by which distance geometry restraints are culled from sets of 500 protein-like conformations for four small helical proteins generated by the method of Simons et al. (1997). A consensus-based approach was applied in which every inter-C alpha distance was measured, and the most frequently occurring distances were used as input restraints for distance geometry. For each protein, a structure with lower coordinate root-mean-square (RMS) error than the mean of the original set was constructed; in three cases the topology of the fold resembled that of the native protein. When the fold sets were filtered for the best scoring conformations with respect to an all-atom knowledge-based scoring function, the remaining subset of 50 structures yielded restraints of higher accuracy. A second round of distance geometry using these restraints resulted in an average coordinate RMS error of 4.38 Angstrom.