Pinto Corujo Marco, Olamoyesan Adewale, Tukova Anastasiia, Ang Dale, Goormaghtigh Erik, Peterson Jason, Sharov Victor, Chmel Nikola, Rodger Alison
Department of Chemistry, University of Warwick, Coventry, United Kingdom.
Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia.
Front Chem. 2022 Jan 27;9:784625. doi: 10.3389/fchem.2021.784625. eCollection 2021.
A protein's structure is the key to its function. As protein structure can vary with environment, it is important to be able to determine it over a wide range of concentrations, temperatures, formulation vehicles, and states. Robust reproducible validated methods are required for applications including batch-batch comparisons of biopharmaceutical products. Circular dichroism is widely used for this purpose, but an alternative is required for concentrations above 10 mg/mL or for solutions with chiral buffer components that absorb far UV light. Infrared (IR) protein absorbance spectra of the Amide I region (1,600-1700 cm) contain information about secondary structure and require higher concentrations than circular dichroism often with complementary spectral windows. In this paper, we consider a number of approaches to extract structural information from a protein infrared spectrum and determine their reliability for regulatory and research purpose. In particular, we compare direct and second derivative band-fitting with a self-organising map (SOM) approach applied to a number of different reference sets. The self-organising map (SOM) approach proved significantly more accurate than the band-fitting approaches for solution spectra. As there is no validated benchmark method available for infrared structure fitting, SOMSpec was implemented in a leave-one-out validation (LOOV) approach for solid-state transmission and thin-film attenuated total reflectance (ATR) reference sets. We then tested SOMSpec and the thin-film ATR reference set against 68 solution spectra and found the average prediction error for helix (α + 3) and -sheet was less than 6% for proteins with less than 40% helix. This is quantitatively better than other available approaches. The visual output format of SOMSpec aids identification of poor predictions. We also demonstrated how to convert aqueous ATR spectra to and from transmission spectra for structure fitting. Fourier self-deconvolution did not improve the average structure predictions.
蛋白质的结构是其功能的关键。由于蛋白质结构会随环境变化，因此能够在广泛的浓度、温度、制剂载体和状态下确定其结构非常重要。对于包括生物制药产品批次间比较在内的应用，需要稳健、可重复且经过验证的方法。圆二色性广泛用于此目的，但对于浓度高于10 mg/mL的溶液或含有吸收远紫外光的手性缓冲成分的溶液，则需要另一种方法。酰胺I区域（1600 - 1700 cm）的红外（IR）蛋白质吸收光谱包含有关二级结构的信息，并且与圆二色性相比需要更高的浓度，且通常具有互补的光谱窗口。在本文中，我们考虑了多种从蛋白质红外光谱中提取结构信息的方法，并确定它们在监管和研究目的方面的可靠性。特别是，我们将直接和二阶导数谱带拟合与应用于多个不同参考集的自组织映射（SOM）方法进行了比较。对于溶液光谱，自组织映射（SOM）方法被证明比谱带拟合方法准确得多。由于没有经过验证的红外结构拟合基准方法，因此在留一法验证（LOOV）方法中对固态透射和薄膜衰减全反射（ATR）参考集实施了SOMSpec。然后，我们针对68个溶液光谱测试了SOMSpec和薄膜ATR参考集，发现对于螺旋含量低于40%的蛋白质，螺旋（α + 3）和β - 折叠的平均预测误差小于6%。这在定量上比其他可用方法更好。SOMSpec的可视化输出格式有助于识别不良预测。我们还展示了如何将水性ATR光谱转换为透射光谱以及从透射光谱转换为水性ATR光谱以进行结构拟合。傅里叶自去卷积并没有改善平均结构预测。
