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寻找蛋白质二级结构定义与蛋白质傅里叶变换红外光谱之间更好的匹配。

Searching for a Better Match between Protein Secondary Structure Definitions and Protein FTIR Spectra.

机构信息

Center for Structural Biology and Bioinformatics, Laboratory for the Structure and Function of Biological Membranes, Université Libre de Bruxelles, Campus Plaine CP206/2, B1050 Brussels, Belgium.

出版信息

Anal Chem. 2021 Jan 26;93(3):1561-1568. doi: 10.1021/acs.analchem.0c03943. Epub 2020 Dec 17.

Abstract

Obtaining protein secondary structure content from high-resolution structures requires definitions and thresholds for the various parameters involved, typically hydrogen bond energy or length/angle and backbone φ/ψ angles. Several definitions are currently used and can have a profound impact on secondary structure content. Fourier transform infrared (FTIR) spectroscopy has its own sensitivity to molecular geometry. It is, therefore, important to select a set of definitions that matches this sensitivity. Here, we used a new protein set consisting of 92 proteins designed for the calibration of spectroscopic methods. Spectra have been obtained from protein microarrays in a high throughput process. The potential for improving secondary structure predictions from FTIR spectra has been tested using 71 structures determined according to different definitions. The paper demonstrates that different secondary structure definitions result in large variations in secondary structure content that are not equivalent in view of the protein FTIR spectra. The prediction quality factor ζ can be improved by ca. 20-50% by selecting an adequate definition set. The results also indicate that the dictionary of secondary structure of proteins (DSSP) algorithm, which is currently widely used to evaluate protein secondary structure content, is a good choice when dealing with FTIR spectra.

摘要

从高分辨率结构中获取蛋白质二级结构含量需要定义和确定各种相关参数的阈值,通常是氢键能量或长度/角度以及主链 φ/ψ 角度。目前有几种定义方法,它们会对二级结构含量产生深远的影响。傅里叶变换红外(FTIR)光谱法对分子几何形状具有独特的敏感性。因此,选择一组与这种敏感性相匹配的定义非常重要。在这里,我们使用了一组由 92 种蛋白质组成的新蛋白质集,这些蛋白质是为光谱方法的校准而设计的。已经从高通量过程中的蛋白质微阵列中获得了光谱。使用根据不同定义确定的 71 个结构测试了从 FTIR 光谱提高二级结构预测的潜力。本文证明,不同的二级结构定义会导致二级结构含量的大幅变化,从蛋白质 FTIR 光谱的角度来看,这些变化并不等效。通过选择合适的定义集,预测质量因子 ζ 可以提高约 20-50%。结果还表明,目前广泛用于评估蛋白质二级结构含量的蛋白质二级结构词典(DSSP)算法是处理 FTIR 光谱的一个很好的选择。

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