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The three-dimensional profile method using residue preference as a continuous function of residue environment.

机译:使用残留优先级作为残留环境连续函数的三维轮廓方法。

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摘要

In the 3-dimensional profile method, the compatibility of an amino acid sequence for a given protein structure is scored as the sum of the preferences of the residues for their environments in the 3D structure. In the original method (Bowie JU, Lüthy R, Eisenberg D, 1991, Science 253:164-170), residue environments were quantized into 18 discrete environmental classes. Here, amino acid residue preferences are expressed as a continuous function of environmental variables (residue area buried and fractional area buried by polar atoms). This continuous representation of residue preferences, expressed as a Fourier series, avoids the abrupt change of preference of residues in slightly different environments, as encountered in the original method with its 18 discrete environmental classes. When compared with the discrete 18-class representation of residue environments, this continuous 3D profile is found to be more sensitive in identifying sequences that fold into the profiled structure but share with it little sequence identity. The continuous 3D profile is also less sensitive to errors in environmental variables than is the discrete 3D profile. The continuous 3D profile can also be used to detect wrong folds or incorrectly modeled segments in an otherwise correct structure, as could the discrete 3D profile (Lüthy R, Bowie JU, Eisenberg D, 1992, Nature 356:83-85). Moreover, the progress of structure improvement during atomic refinement can also be monitored by examining the profile scores in a moving-window scan. Finally, by defining a functional form for profile scores, we open the way to profile atomic refinement in which an atomic structure adjusts to produce residue environments more compatible with the protein side chains.
机译:在3维分布图方法中,给定蛋白质结构的氨基酸序列的相容性被评分为残基对3D结构中其环境的偏好的总和。在原始方法中(Bowie JU,LüthyR,Eisenberg D,1991,Science 253:164-170),残留物环境被量化为18个离散的环境类别。在此,氨基酸残基偏好表示为环境变量的连续函数(被极性原子掩埋的残基面积和被分数面积掩盖的面积)。以傅立叶级数表示的残基偏好的这种连续表示,避免了在稍有不同的环境中残基偏好的突然变化,这与原始方法的18种离散环境类别所遇到的情况一样。当与残基环境的离散18类表示形式进行比较时,发现该连续的3D轮廓在识别折叠成轮廓结构但几乎没有序列同一性的序列时更为敏感。连续3D轮廓也比离散3D轮廓对环境变量的错误敏感。连续的3D轮廓也可以用于检测错误折叠或在其他正确结构中建模不正确的片段,离散3D轮廓也可以使用(LüthyR,Bowie JU,Eisenberg D,1992,Nature 356:83-85)。此外,还可以通过在移动窗口扫描中检查轮廓分数来监视原子细化过程中结构改进的进度。最后,通过定义轮廓得分的功能形式,我们打开了轮廓原子细化的方法,其中原子结构进行调整以产生与蛋白质侧链更相容的残基环境。

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