Molprobity's ultimate rotamer-library distributions for model validation.
Molprobity's ultimate rotamer-library distributions for model validation.
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DOI：
10.1002/prot.25039
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发表时间：
2016-09
期刊：
影响因子：
2.9
通讯作者：
Richardson DC
中科院分区：
文献类型：
--
作者：
Hintze BJ;Lewis SM;Richardson JS;Richardson DC
在这里，我们描述了更新的MolProbity旋转体库分布，这些分布来自于一个更大的数量级，更严格的质量过滤数据集，大约8000个（相对于500个）蛋白质链，我们解释了用户看到的模型验证的变化和改进。为了只包括对其给定构象有满意理由的侧链，我们为电子密度值和模型-密度拟合添加了残留物特定滤波器。合并后的新方案保留了100万个残差数据，同时清除了多χ数据点分布中的假阳性噪声。它使构象簇的明确表征比最常见的频率低近1000倍。我们描述了有利于这些罕见构象的局部相互作用的例子，包括真实的共价键角偏差在实现可能的张力侧链构象中的作用。此外，除了偏爱和离群值之外，还添加了一个允许的类别（在参考数据中出现0.3%至2.0%），类似于Ramachandran验证类别。新的旋转体分布用于当前的molprobity和PHENIX中的旋转体验证，以及PHENIX模型构建和改进中的旋转体选择。多维χ分布和Top8000参考数据集可以在GitHub上免费获得。这些旋转器被称为“终极”，因为数据采样和质量现在完全足以完成这项任务，也因为我们相信未来的构象验证应该将侧链与骨干标准集成在一起。
Here we describe the updated MolProbity rotamer-library distributions derived from an order-of-magnitude larger and more stringently quality-filtered dataset of about 8000 (vs. 500) protein chains, and we explain the resulting changes and improvements to model validation as seen by users. To include only sidechains with satisfactory justification for their given conformation, we added residue-specific filters for electron-density value and model-to-density fit. The combined new protocol retains a million residues of data, while cleaning up false-positive noise in the multi-χ datapoint distributions. It enables unambiguous characterization of conformational clusters nearly 1000-fold less frequent than the most common ones. We describe examples of local interactions that favor these rare conformations, including the role of authentic covalent bond-angle deviations in enabling presumably strained sidechain conformations. Further, along with favored and outlier, an allowed category (0.3% to 2.0% occurrence in reference data) has been added, analogous to Ramachandran validation categories. The new rotamer distributions are used for current rotamer validation in Mol-Probity and PHENIX, and for rotamer choice in PHENIX model-building and refinement. The multi-dimensional χ distributions and Top8000 reference dataset are freely available on GitHub. These rotamers are termed “ultimate” because data sampling and quality are now fully adequate for this task, and also because we believe the future of conformational validation should integrate sidechain with backbone criteria.