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不同无规卷曲蛋白质生物物理预测方法之间的固有关系。

Inherent relationships among different biophysical prediction methods for intrinsically disordered proteins.

机构信息

College of Chemistry and Molecular Engineering, Center for Quantitative Biology, and Beijing National Laboratory for Molecular Sciences, Peking University, Beijing, China.

出版信息

Biophys J. 2013 Jan 22;104(2):488-95. doi: 10.1016/j.bpj.2012.12.012.

Abstract

Intrinsically disordered proteins do not have stable secondary and/or tertiary structures but still function. More than 50 prediction methods have been developed and inherent relationships may be expected to exist among them. To investigate this, we conducted molecular simulations and algorithmic analyses on a minimal coarse-grained polypeptide model and discovered a common basis for the charge-hydropathy plot and packing-density algorithms that was verified by correlation analysis. The correlation analysis approach was applied to realistic datasets, which revealed correlations among some physical-chemical properties (charge-hydropathy plot, packing density, pairwise energy). The correlations indicated that these biophysical methods find a projected direction to discriminate ordered and disordered proteins. The optimized projection was determined and the ultimate accuracy limit of the existing algorithms is discussed.

摘要

无规蛋白没有稳定的二级和/或三级结构,但仍具有功能。已经开发了 50 多种预测方法,可以预期它们之间存在内在关系。为了研究这一点,我们对最小的粗粒多肽模型进行了分子模拟和算法分析,并通过相关分析验证了电荷 - 疏水性图和堆积密度算法之间存在共同基础。相关分析方法应用于实际数据集,揭示了一些物理化学性质(电荷 - 疏水性图、堆积密度、成对能量)之间的相关性。相关性表明,这些生物物理方法找到了一个投影方向来区分有序蛋白和无规蛋白。确定了优化的投影,并讨论了现有算法的最终精度极限。

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本文引用的文献

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