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首页> 外文期刊>Acta crystallographica. Section D, Structural biology. >Molecular replacement using structure predictionsfrom databases
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Molecular replacement using structure predictionsfrom databases

机译：分子替换使用结构predictionsfrom数据库

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Molecular replacement (MR) is the predominant route to solution of the phaseproblem in macromolecular crystallography. Where the lack of a suitablehomologue precludes conventional MR, one option is to predict the targetstructure using bioinformatics. Such modelling, in the absence of homologoustemplates, is called ab initio or de novo modelling. Recently, the accuracy of suchmodels has improved significantly as a result of the availability, in many cases,of residue-contact predictions derived from evolutionary covariance analysis.Covariance-assisted ab initio models representing structurally uncharacterizedPfam families are now available on a large scale in databases, potentiallyrepresenting a valuable and easily accessible supplement to the PDB as a sourceof search models. Here, the unconventional MR pipeline AMPLE is employedto explore the value of structure predictions in the GREMLIN and PconsFamdatabases. It was tested whether these deposited predictions, processed invarious ways, could solve the structures of PDB entries that were subsequentlydeposited. The results were encouraging: nine of 27 GREMLIN cases weresolved, covering target lengths of 109-355 residues and a resolution range of1.4-2.9 A, and with target-model shared sequence identity as low as 20%. Thecluster-and-truncate approach in AMPLE proved to be essential for mostsuccesses. For the overall lower quality structure predictions in the PconsFamdatabase, remodelling with Rosetta within the AMPLE pipeline proved to be thebest approach, generating ensemble search models from single-structuredeposits. Finally, it is shown that the AMPLis-obtained search models derivingfrom GREMLIN deposits are of sufficiently high quality to be selected by thesequence-independent MR pipeline SIMBAD. Overall, the results help to pointthe way towards the optimal use of the expanding databases of ab initiostructure predictions.
机译：分子置换(先生)是主要的phaseproblem的解决方案大分子晶体学。suitablehomologue排除了传统先生,一种选择是预测targetstructure使用生物信息学。没有homologoustemplates,叫做ab在开头或新创造型。suchmodels精度有显著提高的可用性,在很多情况下,残余接触预测来自进化的协方差分析。代表结构uncharacterizedPfam大规模家庭现在可用数据库、potentiallyrepresenting有价值的和方便的PDB作为补充有机搜索模型。管道的先生employedto探索价值小鬼和结构的预测PconsFamdatabases。沉积的预测,以多种方式进行加工,可以解决PDB项的结构吗subsequentlydeposited。鼓励:九27个小鬼weresolved病例,覆盖目标长度109 - 355残留分辨率范围of1.4 - 2.9,目标模型共享序列低身份20%。对于mostsuccesses被证明是至关重要的。整体结构预测质量下降与罗塞塔PconsFamdatabase,改造在充足的管道被证明是最好的方法,生成整体搜索模型single-structuredeposits。AMPLis-obtained搜索模型derivingfrom小鬼存款是足够的高品质的选择thesequence-independent管道SIMBAD先生。总的来说,结果有助于根本程度上最优ab的扩大数据库的使用initiostructure预测。

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