Nicholls Robert A, Kovalevskiy Oleg, Murshudov Garib N
MRC Laboratory of Molecular Biology, Francis Crick Avenue, CB2 0QH, Cambridge, UK.
Methods Mol Biol. 2017;1607:565-593. doi: 10.1007/978-1-4939-7000-1_23.
This review describes some of the problems encountered during low-resolution refinement and map calculation. Refinement is considered as an application of Bayes' theorem, allowing combination of information from various sources including crystallographic experimental data and prior chemical and structural knowledge. The sources of prior knowledge relevant to macromolecules include basic chemical information such as bonds and angles, structural information from reference models of known homologs, knowledge about secondary structures, hydrogen bonding patterns, and similarity of non-crystallographically related copies of a molecule. Additionally, prior information encapsulating local conformational conservation is exploited, keeping local interatomic distances similar to those in the starting atomic model. The importance of designing an accurate likelihood function-the only link between model parameters and observed data-is emphasized. The review also reemphasizes the importance of phases, and describes how the use of raw observed amplitudes could give a better correlation between the calculated and "true" maps. It is shown that very noisy or absent observations can be replaced by calculated structure factors, weighted according to the accuracy of the atomic model. This approach helps to smoothen the map. However, such replacement should be used sparingly, as the bias toward errors in the model could be too much to avoid. It is in general recommended that, whenever a new map is calculated, map quality should be judged by inspection of the parts of the map where there is no atomic model. It is also noted that it is advisable to work with multiple blurred and sharpened maps, as different parts of a crystal may exhibit different degrees of mobility. Doing so can allow accurate building of atomic models, accounting for overall shape as well as finer structural details. Some of the results described in this review have been implemented in the programs REFMAC5, ProSMART and LORESTR, which are available as part of the CCP4 software suite.
本综述描述了低分辨率精修和图谱计算过程中遇到的一些问题。精修被视为贝叶斯定理的一种应用，它允许整合来自各种来源的信息，包括晶体学实验数据以及先前的化学和结构知识。与大分子相关的先验知识来源包括诸如键和角度等基本化学信息、来自已知同源物参考模型的结构信息、关于二级结构的知识、氢键模式以及分子非晶体学相关拷贝的相似性。此外，还利用了封装局部构象保守性的先验信息，使局部原子间距离与起始原子模型中的距离相似。文中强调了设计准确似然函数的重要性，似然函数是模型参数与观测数据之间的唯一联系。该综述还再次强调了相位的重要性，并描述了使用原始观测振幅如何能使计算图谱与“真实”图谱之间具有更好的相关性。结果表明，非常嘈杂或缺失的观测值可以用根据原子模型精度加权的计算结构因子来替代。这种方法有助于使图谱平滑。然而，这种替代应谨慎使用，因为模型中误差的偏差可能过大而难以避免。一般建议，每当计算新的图谱时，应通过检查没有原子模型的图谱部分来判断图谱质量。还指出，处理多个模糊和锐化的图谱是可取的，因为晶体的不同部分可能表现出不同程度的流动性。这样做可以准确构建原子模型，同时考虑整体形状以及更精细的结构细节。本综述中描述的一些结果已在REFMAC5、ProSMART和LORESTR程序中实现，这些程序可作为CCP4软件套件的一部分获取。
