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基于圆二色性的模型验证有多准确?

How accurate is circular dichroism-based model validation?

机构信息

Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077, Göttingen, Germany.

出版信息

Eur Biophys J. 2020 Sep;49(6):497-510. doi: 10.1007/s00249-020-01457-6. Epub 2020 Aug 26.

DOI:10.1007/s00249-020-01457-6
PMID:32844286
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7456416/
Abstract

Circular dichroism (CD) spectroscopy is highly sensitive to the secondary structure (SS) composition of proteins. Several methods exist to either estimate the SS composition of a protein or to validate existing structural models using its CD spectrum. The accuracy and precision of these methods depend on the quality of both the measured CD spectrum and the used reference structure. Using a large reference protein set with high-quality CD spectra and synthetic data derived from this set, we quantified deviations from both ideal spectra and reference structures due to experimental limitations. We also determined the impact of these deviations on SS estimation, CD prediction, and SS validation methods of the SESCA analysis package. With regard to the CD spectra, our results suggest intensity scaling errors and non-SS contributions as the main causes of inaccuracies. These factors also can lead to overestimated model errors during validation. The errors of the used reference structures combine non-additively with errors caused by the CD spectrum, which increases the uncertainty of model validation. We have further shown that the effects of scaling errors in the CD spectrum can be nearly eliminated by appropriate re-scaling, and that the accuracy of model validation methods can be improved by accounting for typical non-SS contributions. These improvements have now been implemented within the SESCA package and are available at: https://www.mpibpc.mpg.de/sesca .

摘要

圆二色性(CD)光谱对蛋白质的二级结构(SS)组成非常敏感。有几种方法可以估计蛋白质的 SS 组成,或者使用其 CD 光谱验证现有的结构模型。这些方法的准确性和精度取决于测量的 CD 光谱和使用的参考结构的质量。使用具有高质量 CD 光谱的大型参考蛋白质集和从该集中衍生的合成数据,我们量化了由于实验限制而导致的与理想光谱和参考结构的偏差。我们还确定了这些偏差对 SESCA 分析包中 SS 估计、CD 预测和 SS 验证方法的影响。就 CD 光谱而言,我们的结果表明,强度缩放误差和非 SS 贡献是不准确的主要原因。这些因素还可能导致验证过程中模型误差被高估。所使用的参考结构的误差与 CD 光谱引起的误差非加性组合,这增加了模型验证的不确定性。我们进一步表明,通过适当的重新缩放可以几乎消除 CD 光谱中的缩放误差的影响,并且通过考虑典型的非 SS 贡献可以提高模型验证方法的准确性。这些改进现在已经在 SESCA 包中实现,并可在以下网址获得:https://www.mpibpc.mpg.de/sesca 。

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