Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, United Kingdom.
Department of Clinical Biochemistry, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, United Kingdom.
Proc Natl Acad Sci U S A. 2017 Apr 4;114(14):3637-3641. doi: 10.1073/pnas.1701640114. Epub 2017 Mar 21.
The majority of macromolecular crystal structures are determined using the method of molecular replacement, in which known related structures are rotated and translated to provide an initial atomic model for the new structure. A theoretical understanding of the signal-to-noise ratio in likelihood-based molecular replacement searches has been developed to account for the influence of model quality and completeness, as well as the resolution of the diffraction data. Here we show that, contrary to current belief, molecular replacement need not be restricted to the use of models comprising a substantial fraction of the unknown structure. Instead, likelihood-based methods allow a continuum of applications depending predictably on the quality of the model and the resolution of the data. Unexpectedly, our understanding of the signal-to-noise ratio in molecular replacement leads to the finding that, with data to sufficiently high resolution, fragments as small as single atoms of elements usually found in proteins can yield ab initio solutions of macromolecular structures, including some that elude traditional direct methods.
大多数大分子晶体结构是通过分子置换法来确定的,该方法将已知相关结构进行旋转和移动,为新结构提供初始原子模型。已经开发出基于可能性的分子置换搜索信号与噪声比的理论理解,以解释模型质量和完整性以及衍射数据分辨率的影响。在这里,我们表明,与当前的观点相反,分子置换不一定局限于使用包含未知结构的很大一部分的模型。相反,基于可能性的方法可以根据模型的质量和数据的分辨率进行连续应用。出乎意料的是,我们对分子置换中信号与噪声比的理解导致了这样的发现,即使用足够高分辨率的数据,小至单个蛋白质中常见元素的原子碎片也可以产生大分子结构的从头解决方案,包括一些逃避传统直接方法的结构。