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一种用于从头相位确定的片段化和重组方法。

A fragmentation and reassembly method for ab initio phasing.

作者信息

Shrestha Rojan, Zhang Kam Y J

机构信息

Structural Bioinformatics Team, Division of Structural and Synthetic Biology, Center for Life Science Technologies, RIKEN, Yokohama, Kanagawa 230-0045, Japan.

出版信息

Acta Crystallogr D Biol Crystallogr. 2015 Feb;71(Pt 2):304-12. doi: 10.1107/S1399004714025449. Epub 2015 Jan 23.

Abstract

Ab initio phasing with de novo models has become a viable approach for structural solution from protein crystallographic diffraction data. This approach takes advantage of the known protein sequence information, predicts de novo models and uses them for structure determination by molecular replacement. However, even the current state-of-the-art de novo modelling method has a limit as to the accuracy of the model predicted, which is sometimes insufficient to be used as a template for successful molecular replacement. A fragment-assembly phasing method has been developed that starts from an ensemble of low-accuracy de novo models, disassembles them into fragments, places them independently in the crystallographic unit cell by molecular replacement and then reassembles them into a whole structure that can provide sufficient phase information to enable complete structure determination by automated model building. Tests on ten protein targets showed that the method could solve structures for eight of these targets, although the predicted de novo models cannot be used as templates for successful molecular replacement since the best model for each target is on average more than 4.0 Å away from the native structure. The method has extended the applicability of the ab initio phasing by de novo models approach. The method can be used to solve structures when the best de novo models are still of low accuracy.

摘要

使用从头算模型进行从头算相位确定已成为从蛋白质晶体学衍射数据解析结构的一种可行方法。这种方法利用已知的蛋白质序列信息,预测从头算模型,并将其用于通过分子置换确定结构。然而,即使是当前最先进的从头算建模方法,其预测模型的准确性也存在局限性,有时不足以用作成功进行分子置换的模板。已经开发出一种片段组装相位确定方法,该方法从一组低准确性的从头算模型开始,将它们拆解成片段,通过分子置换将它们独立放置在晶体学晶胞中,然后将它们重新组装成一个完整的结构,该结构可以提供足够的相位信息,以便通过自动模型构建来完成结构解析。对十个蛋白质靶点的测试表明,该方法可以解析其中八个靶点的结构,尽管预测的从头算模型不能用作成功进行分子置换的模板,因为每个靶点的最佳模型与天然结构的平均距离超过4.0 Å。该方法扩展了使用从头算模型进行从头算相位确定方法的适用性。当最佳的从头算模型仍然准确性较低时,该方法可用于解析结构。

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