IR Spectroscopy: From Experimental Spectra to High-Resolution Structural Analysis by Integrating Simulations and Machine Learning.

ABSTRACT: Understanding biomolecular function at the atomic scale requires detailed insight into the structural changes underlying dynamic processes. Vibrational infrared (IR) spectroscopy─when paired with biomolecular simulations and quantum-chemical calculations─determines bond length variations on the order of 0.01 Å, providing insights into these structural changes. Here, we address the forward problem in IR spectroscopy: predicting high-accuracy vibrational spectra from known molecular structures identified by biomolecular simulations. Solving this problem lays the groundwork for the inverse problem: inferring structural ensembles directly from experimental IR spectra. We evaluate two computational approaches, normal-mode analysis and Fourier-transformed dipole autocorrelation, against experime

SUBMITTER: Scherlo M 

PROVIDER: S-EPMC12621253 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature