Vibrational asymmetry across heptad positions in coiled-coil IR spectra: A simulation study of isotope-labeled amide...

Isotope-edited infrared (IR) spectroscopy is a powerful tool for probing site-specific structures and dynamics within proteins. However, the interpretation is often complicated by spectral congestion and environmental heterogeneity. In this study, vibrational exciton models combined with molecular dynamics simulations are employed to examine the frequency distributions and IR spectra of isotope-labeled local modes (ILMs) in parallel coiled-coil dimers. Based on the difference spectra obtained by subtracting the unlabeled spectrum from the labeled one, a new method to estimate labeled local-mode frequencies is proposed. The IR peak positions predicted from both the ILMs and specific normal modes systematically deviate from their corresponding average frequencies, primarily owing to asymmetric broadening. This asymmetry, which is characterized by the skewness of the mode density of states, arises from heterogeneous fluctuations in the local environment. Time correlation analysis revealed that solvation-induced dynamics persist on timescales (0.22-3.30 ps) exceeding the vibrational lifetime, causing incomplete motional averaging and pronounced inhomogeneous broadening. These effects result in skewed frequency distributions and contribute to peak localization errors. The application of asymmetric Gaussian fitting models and perturbative corrections improved the accuracy of the ILM frequency estimates, with sub-wavenumber precision achieved when spectral separation was sufficient. The heptad-repeat architecture of coiled coils further introduced register-specific vibrational patterns, emphasizing the role of the local environment. Collectively, the results highlight the critical role of solvation-induced heterogeneity in shaping isotope-edited IR spectra and demonstrate the need to consider both dynamic and statistical spectral asymmetry when performing high-resolution vibrational analysis of proteins.