Hoffmann Søren Vrønning, Jones Nykola C, Rodger Alison
ISA, Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark.
Research School of Chemistry, Australian National University, Canberra, Australia.
QRB Discov. 2025 Feb 3;6:e10. doi: 10.1017/qrd.2025.4. eCollection 2025.
Protein circular dichroism (CD) and infrared absorbance (IR) spectra are widely used to estimate the secondary structure content of proteins in solution. A range of algorithms have been used for CD analysis (SELCON, CONTIN, CDsstr, SOMSpec) and some of these have been applied to IR data, though IR is more commonly analysed by bandfitting or statistical approaches. In this work we provide a Python version of SELCON3 and explore how to combine CD and IR data to best effect. We used CD data in Δε/amino acid residue and scaled the IR spectra to similar magnitudes. Normalising the IR amide I spectra scaled to a maximum absorbance of 15 gives best general performance. Combining CD and IR improves predictions for both helix and sheet by ~2% and helps identify anomalously large errors for high helix proteins such as haemoglobin when using IR data alone and high sheet proteins when using CD data alone.
蛋白质圆二色性（CD）和红外吸收（IR）光谱被广泛用于估计溶液中蛋白质的二级结构含量。一系列算法已被用于CD分析（SELCON、CONTIN、CDsstr、SOMSpec），其中一些已应用于IR数据，不过IR更常通过谱带拟合或统计方法进行分析。在这项工作中，我们提供了SELCON3的Python版本，并探索如何将CD和IR数据进行最佳组合。我们使用了Δε/氨基酸残基中的CD数据，并将IR光谱缩放到相似的量级。将IR酰胺I光谱归一化到最大吸光度为15时，总体性能最佳。结合CD和IR可使螺旋和折叠结构的预测精度提高约2%，并有助于识别单独使用IR数据时对血红蛋白等高螺旋含量蛋白质以及单独使用CD数据时对高折叠含量蛋白质出现的异常大误差。
