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SIMBAD SIMBAD : a sequence‐independent molecular‐replacement pipeline

机译:SIMBAD SIMBAD:一个序列无关的分子检测更换管道

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The conventional approach to finding structurally similar search models for use in molecular replacement (MR) is to use the sequence of the target to search against those of a set of known structures. Sequence similarity often correlates with structure similarity. Given sufficient similarity, a known structure correctly positioned in the target cell by the MR process can provide an approximation to the unknown phases of the target. An alternative approach to identifying homologous structures suitable for MR is to exploit the measured data directly, comparing the lattice parameters or the experimentally derived structure‐factor amplitudes with those of known structures. Here, SIMBAD , a new sequence‐independent MR pipeline which implements these approaches, is presented. SIMBAD can identify cases of contaminant crystallization and other mishaps such as mistaken identity (swapped crystallization trays), as well as solving unsequenced targets and providing a brute‐force approach where sequence‐dependent search‐model identification may be nontrivial, for example because of conformational diversity among identifiable homologues. The program implements a three‐step pipeline to efficiently identify a suitable search model in a database of known structures. The first step performs a lattice‐parameter search against the entire Protein Data Bank (PDB), rapidly determining whether or not a homologue exists in the same crystal form. The second step is designed to screen the target data for the presence of a crystallized contaminant, a not uncommon occurrence in macromolecular crystallography. Solving structures with MR in such cases can remain problematic for many years, since the search models, which are assumed to be similar to the structure of interest, are not necessarily related to the structures that have actually crystallized. To cater for this eventuality, SIMBAD rapidly screens the data against a database of known contaminant structures. Where the first two steps fail to yield a solution, a final step in SIMBAD can be invoked to perform a brute‐force search of a nonredundant PDB database provided by the MoRDa MR software. Through early‐access usage of SIMBAD , this approach has solved novel cases that have otherwise proved difficult to solve.
机译:传统的方法来寻找结构类似的搜索模型用于分子替换(先生)是使用的顺序目标对一组已知的搜索结构。与结构相似性。相似,一个已知的结构正确定位在先生的靶细胞的过程可以提供一个近似未知吗阶段的目标。识别同源结构适合先生是直接利用测量数据,比较或晶格参数实验衍生结构因素振幅与已知的结构。SIMBAD,一个新的序列独立管道先生实现这些方法,提出了。SIMBAD可以识别污染物的病例结晶和其他事故等错误的标识(交换结晶托盘),以及解决unsequenced目标并提供一个蛮力方法的地方序列相关的搜索量模式识别可能是重要的,例如,因为构象之间的多样性可识别的同系物。管道有效地确定一个合适的搜索模型在数据库中已知的结构。第一步执行一个晶格参数搜索对整个蛋白质数据银行(PDB),迅速决定是否同系物在同一晶体形式存在。第二步是为了屏幕目标数据对于结晶污染物的存在,经常发生在大分子晶体学。这种情况下可以保持多年的问题,自搜索模型,假定与感兴趣的结构相似,则不是一定的结构有关实际结晶。可能性,SIMBAD迅速屏幕数据对已知污染物的一个数据库结构。SIMBAD产生一个解决方案,最后一步调用来执行一个蛮力搜索的nonredundant PDB MoRDa提供的数据库先生的软件。小说,这种方法解决了案件否则很难解决。

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