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Improved molecular replacement by density- and energy-guided protein structure optimization

机译:通过密度和能量引导的蛋白质结构优化改善分子置换

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摘要

Molecular replacement procedures, which search for placements of a starting model within the crystallographic unit cell that best account for the measured diffraction amplitudes, followed by automatic chain tracing methods, have allowed the rapid solution of large numbers of protein crystal structures. Despite extensive work, molecular replacement or the subsequent rebuilding usually fail with more divergent starting models based on remote homologues with less than 30% sequence identity. Here we show that this limitation can be substantially reduced by combining algorithms for protein structure modelling with those developed for crystallographic structure determination. An approach integrating Rosetta structure modelling with Autobuild chain tracing yielded high-resolution structures for 8 of 13 X-ray diffraction data sets that could not be solved in the laboratories of expert crystallographers and that remained unsolved after application of an extensive array of alternative approaches. We estimate that the new method should allow rapid structure determination without experimental phase information for over half the cases where current methods fail, given diffraction data sets of better than 3.2 A resolution, four or fewer copies in the asymmetric unit, and the availability of structures of homologous proteins with >20% sequence identity.
机译:分子置换程序在晶体学晶胞内寻找最能说明所测衍射幅度的起始模型的位置,然后采用自动链追踪方法,可以快速解决大量蛋白质晶体结构的问题。尽管进行了广泛的工作,但分子置换或随后的重建通常会因基于同源性低于30%的序列同源性更高的起始模型而失败。在这里,我们表明可以通过将蛋白质结构建模算法与为晶体结构确定开发的算法相结合,大大减少这种限制。将Rosetta结构建模与Autobuild链跟踪集成在一起的方法可为13个X射线衍射数据集中的8个提供高分辨率的结构,这些结构在专家晶体学家的实验室中无法解决,并且在应用了大量替代方法后仍未解​​决。我们估计,对于超过3.2 A分辨率的衍射数据集,不对称单元中有四个或更少的副本,在新方法失败的情况下,对于当前方法失败的一半以上情况,新方法应能够在没有实验阶段信息的情况下快速确定结构具有> 20%序列同一性的同源蛋白。

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  • 来源
    《Nature》 |2011年第7348期|p.540-543|共4页
  • 作者单位

    University of Washington, Department of Biochemistry and HHMI, Seattle, Washington 98195, USA;

    Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA;

    University of Cambridge,Department of Haematology, Cambridge Institute for Medical Research, Cambridge CB2 OXY, UK;

    Macromolecular Crystallography Laboratory, National Cancer Institute at Frederick, Frederick, Maryland 21702, USA;

    Institute of Molecular Biosciences, University of Graz, Humboldtstrasse 50/3,8010-Graz, Austria;

    Institute of Molecular Biosciences, University of Graz, Humboldtstrasse 50/3,8010-Graz, Austria;

    University of Cambridge, Department of Biochemistry, Cambridge CB2 1GA, UK;

    Weizmann Institute of Science, Department of Structural Biology, Rehovot 76100, Israel;

    Weizmann Institute of Science, Department of Structural Biology, Rehovot 76100, Israel;

    Joint Center for Structural Genomics and SSRL, SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA;

    Joint Center for Structural Genomics and SSRL, SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA;

    Northeast Structural Genomics Consortium, Columbia University, New York, New York 10027, USA;

    University of Helsinki, Institute of Biotechnology, FI-00014 Helsinki, Finland;

    Argonne National Laboratory, Biosciences Division, Argonne, Illinois 60439, USA;

    University of Washington, Department of Biochemistry and HHMI, Seattle, Washington 98195, USA;

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