Vibrational spectroscopy serves as a powerful tool for characterizing intermediate states within the Kok-Joliot cycle. In this study, we employ a QM/MM molecular dynamics framework to calculate the room temperature infrared absorption spectra of the S1, S2, and S3 states via the Fourier transform of the dipole time auto-correlation function. To better analyze the computational data and assign spectral peaks, we introduce an approach based on dipole-dipole correlation function of cluster moieties of the reaction center. Our analysis reveals variation in the infrared signature of the Mn4Ca cluster along the Kok-Joliot cycle, attributed to its increasing symmetry and rigidity resulting from the rising oxidation state of the Mn ions. Furthermore, we successfully assign the debated contributions in the frequency range around 600 cm−1. This computational methodology provides valuable insights for deciphering experimental infrared spectra and understanding the water oxidation process in both biological and artificial systems.

Unravelling Mn4Ca cluster vibrations in the S1, S2 and S3 states of the Kok–Joliot cycle of photosystem II

Capone, Matteo;Parisse, Gianluca;Narzi, Daniele;Guidoni, Leonardo
2024-01-01

Abstract

Vibrational spectroscopy serves as a powerful tool for characterizing intermediate states within the Kok-Joliot cycle. In this study, we employ a QM/MM molecular dynamics framework to calculate the room temperature infrared absorption spectra of the S1, S2, and S3 states via the Fourier transform of the dipole time auto-correlation function. To better analyze the computational data and assign spectral peaks, we introduce an approach based on dipole-dipole correlation function of cluster moieties of the reaction center. Our analysis reveals variation in the infrared signature of the Mn4Ca cluster along the Kok-Joliot cycle, attributed to its increasing symmetry and rigidity resulting from the rising oxidation state of the Mn ions. Furthermore, we successfully assign the debated contributions in the frequency range around 600 cm−1. This computational methodology provides valuable insights for deciphering experimental infrared spectra and understanding the water oxidation process in both biological and artificial systems.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/267822
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