Multivariate Analysis of Spectral Data with Frequency Shifts: Application to Temperature Dependent Infrared Spectra of Peptides and Proteins

作者：Kubelka Jan^*

来源：Analytical Chemistry, 2013, 85(20): 9588-9595.

DOI：10.1021/ac402083p

Changes in the amide I%26apos; IR band with temperature are widely used for elucidation of peptide and protein conformational transitions and folding equilibria. Since amide I%26apos; exhibits inherent temperature dependent frequency shifts, standard mixture analysis methods are not applicable. To reliably extract the true thermodynamic states, frequency shifts of the component spectra must be explicitly taken into account. For this purpose, new methods termed shifted multivariate spectra analysis (SMSA) and parametric SMSA (pSMSA) are developed and tested on sets of synthetic data as well as real experimental amide I%26apos; spectra for thermal unfolding of an a-helical peptide. SMSA uses no specific functional form for the transition (soft modeling), while the parametric variant (pSMSA) assumes a thermodynamic model (hard modeling). The implementation is optimized specifically for amide I%26apos; IR in that it takes advantage of known, linear dependence of the frequencies as well as intensities on temperature. The synthetic data tests demonstrate the robustness of the methods; the initial test parameters are recovered with a high degree of reliability, although the nonparameteric SMSA is subject to the rotational ambiguity. Application to the peptide experimental amide I%26apos; data illustrates additional complications encountered with the analysis of real systems, such as correction for the side-chain spectra and interference of spectral shape changes. Nevertheless, the results are in excellent agreement with the independent control using circular dichroism (CD) data. The general applicability and limitations of the methods are discussed along with potential extensions.

• 出版日期2013-10-15