Comparison of quantitative spectral similarity analysis methods for protein higher-order structure confirmation.

ABSTRACT

Optical and vibrational spectroscopic techniques are important tools for evaluating secondary and tertiary structures of proteins. These spectroscopic techniques are routinely applied in biopharmaceutical development to elucidate structural characteristics of protein products, to evaluate the impact of processing and storage conditions on product quality, and to assess comparability of a protein product before and after manufacturing changes. Conventionally, the degree of similarity between two spectra has been determined visually. In addition to requiring a significant amount of analyst training and experience, visual inspection of spectra is inherently subjective, and any determination of comparability based on visual analysis of spectra is therefore arbitrary. Here, we discuss a general methodology for evaluating the suitability of numerical methods to calculate spectral similarity, and then we apply the methodology to compare four quantitative spectral similarity methods: the correlation coefficient, area of spectral overlap, derivative correlation algorithm, and spectral difference methods. While the most effective spectral similarity method may depend on the particular application, all four approaches are superior to visual evaluation, and each is suitable for assessing the degree of similarity between spectra.