Spectral Analysis and Deconvolution of the Amide I Band of Proteins Presenting with High-Frequency Noise and Baseline Shifts
Spectral Analysis and Deconvolution of the Amide I Band of Proteins Presenting with High-Frequency Noise and Baseline Shifts
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DOI：
10.1177/0003702819898536
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发表时间：
2020-02-10
影响因子：
3.5
通讯作者：
Davies, Paul B.
中科院分区：
文献类型：
--
作者：
Fellows, Alexander P.;Casford, Mike T. L.;Davies, Paul B.
从蛋白质的红外光谱中获取定量信息的挑战来自于大量的二级结构和氨基酸侧链官能团，它们都对光谱强度有贡献，例如在酰胺I谱带（1600-1700 cm（-1））内。该波段总是与重叠的光谱特征严重卷积，从而使得解释困难，因此通常需要去卷积。这项工作严格审查的方法，可去卷积的光谱和评估常用的方法和算法应用于振动光谱平滑和峰值识别。我们表明，除非他们的光谱具有非常高的信噪比，定量分析破译蛋白质成分是不可行的。使用相邻平均，Savitzky-Golay滤波器和快速傅立叶变换滤波器的频谱平滑的优点和缺点进行了详细研究。使用衍生光谱来识别峰的描述，特别是参考的影响和减少在酰胺I区域中的干扰水带。带窄化技术，如二阶导数分析或傅立叶反卷积，导致贡献蛋白质峰的识别的可靠性进行了研究。这两种方法被证明是有限的，在他们的能力，以解决具有非常相似的频率的功能。此外，由高频噪声引起的窄带的存在，无论是来自大气水蒸气、声振动还是电干扰，都导致这两种方法变得越来越不可用，因为窄带优先增强，而代价是宽带，例如酰胺I带。一个最佳的策略是严格的发展，以允许准确的测定和定量的蛋白质成分及其构象。此外，定量方法，提出了占基线偏移，否则会引入显着的错误相似性指数。
The challenge of deriving quantitative information from the infrared spectra of proteins arises from the large number of secondary structures and amino acid side-chain functional groups that all contribute to the spectral intensity, such as within the amide I band (1600-1700 cm(-1)). The band is invariably heavily convoluted from overlapping spectral features, thereby making interpretation difficult such that deconvolution is usually required. This work critically examines the methods available to deconvolute the spectra and assesses the commonly used methods and algorithms applied to vibrational spectra for smoothing and peak identification. We show that unless their spectra have very high signal-to-noise ratios, quantitative analysis to decipher protein constituents is not feasible. The advantages and disadvantages of spectral smoothing using adjacent averaging, the Savitzky-Golay filter and the fast Fourier transform filter are examined in detail. The use of derivative spectra to identify peaks is described with particular reference to the influence and reduction of interfering water bands in the amide I region. The reliability of band narrowing techniques such as second-derivative analysis or Fourier deconvolution that lead to the identification of the contributing protein peaks is investigated. Both methods are shown to be limited in their capacity to resolve features with very similar frequencies. Additionally, the presence of narrow bands arising from high-frequency noise whether from atmospheric water vapor, acoustic vibrations, or electrical interference results in both methods becoming increasingly unusable as narrow bands are preferentially enhanced at the expense of broad ones such as the amide I bands. An optimal strategy is critically developed to allow accurate determination and quantification of protein constituents and their conformations. Additionally, quantitative methods are proposed to account for baseline shifts, which would otherwise introduce significant errors in similarity indices.