Millán Claudia, Sammito Massimo, Garcia-Ferrer Irene, Goulas Theodoros, Sheldrick George M, Usón Isabel
Structural Biology, Instituto de Biologia Molecular de Barcelona, Carrer Baldiri Reixac 15, 3 A17, 08028 Barcelona, Spain.
Structural Chemistry, Institut für Anorganische Chemie, University of Göttingen, Tammannstrasse 4, 37077 Göttingen, Germany.
Acta Crystallogr D Biol Crystallogr. 2015 Sep;71(Pt 9):1931-45. doi: 10.1107/S1399004715013127. Epub 2015 Aug 25.
ARCIMBOLDO allows ab initio phasing of macromolecular structures below atomic resolution by exploiting the location of small model fragments combined with density modification in a multisolution frame. The model fragments can be either secondary-structure elements predicted from the sequence or tertiary-structure fragments. The latter can be derived from libraries of typical local folds or from related structures, such as a low-homology model that is unsuccessful in molecular replacement. In all ARCIMBOLDO applications, fragments are searched for sequentially. Correct partial solutions obtained after each fragment-search stage but lacking the necessary phasing power can, if combined, succeed. Here, an analysis is presented of the clustering of partial solutions in reciprocal space and of its application to a set of different cases. In practice, the task of combining model fragments from an ARCIMBOLDO run requires their referral to a common origin and is complicated by the presence of correct and incorrect solutions as well as by their not being independent. The F-weighted mean phase difference has been used as a figure of merit. Clustering perfect, non-overlapping fragments dismembered from test structures in polar and nonpolar space groups shows that density modification before determining the relative origin shift enhances its discrimination. In the case of nonpolar space groups, clustering of ARCIMBOLDO solutions from secondary-structure models is feasible. The use of partially overlapping search fragments provides a more favourable circumstance and was assessed on a test case. Applying the devised strategy, a previously unknown structure was solved from clustered correct partial solutions.
ARCIMBOLDO通过利用小模型片段的位置并结合多解框架中的密度修正,实现了低于原子分辨率的大分子结构从头相位确定。模型片段可以是从序列预测的二级结构元件或三级结构片段。后者可以源自典型局部折叠的文库或相关结构,例如在分子置换中不成功的低同源性模型。在所有ARCIMBOLDO应用中,片段是按顺序搜索的。在每个片段搜索阶段后获得的正确部分解,但缺乏必要的相位确定能力,如果组合起来可能会成功。这里,对倒易空间中部分解的聚类及其在一组不同案例中的应用进行了分析。实际上,将ARCIMBOLDO运行中的模型片段组合起来的任务需要将它们归到一个共同的原点,并且由于存在正确和不正确的解以及它们不是独立的而变得复杂。F加权平均相位差已被用作一个品质因数。对从极性和非极性空间群中的测试结构中拆分出的完美、不重叠片段进行聚类表明,在确定相对原点位移之前进行密度修正可提高其辨别力。在非极性空间群的情况下,对来自二级结构模型的ARCIMBOLDO解进行聚类是可行的。使用部分重叠的搜索片段提供了更有利的情况,并在一个测试案例中进行了评估。应用所设计的策略,从聚类的正确部分解中解析出了一个以前未知的结构。