On the comparison between differential vibrational spectroscopy spectra and theoretical data in the carboxyl region of photosystem II

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

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.

A Vision for the Future of Multiscale Modeling

The rise of modern computer science enabled physical chemistry to make enormous progresses in understanding and harnessing natural and artificial phenomena. Nevertheless, despite the advances achieved over past decades, computational resources are still insufficient to thoroughly simulate extended systems from first principles. Indeed, countless biological, catalytic and photophysical processes require ab initio treatments to be properly described, but the breadth of length and time scales involved makes it practically unfeasible. A way to address these issues is to couple theories and algorithms working at different scales by dividing the system into domains treated at different levels of approximation, ranging from quantum mechanics to classical molecular dynamics, even including continuum electrodynamics. This approach is known as multiscale modeling and its use over the past 60 years has led to remarkable results. Considering the rapid advances in theory, algorithm design, and computing power, we believe multiscale modeling will massively grow into a dominant research methodology in the forthcoming years. Hereby we describe the main approaches developed within its realm, highlighting their achievements and current drawbacks, eventually proposing a plausible direction for future developments considering also the emergence of new computational techniques such as machine learning and quantum computing. We then discuss how advanced multiscale modeling methods could be exploited to address critical scientific challenges, focusing on the simulation of complex light-harvesting processes, such as natural photosynthesis. While doing so, we suggest a cutting-edge computational paradigm consisting in performing simultaneous multiscale calculations on a system allowing the various domains, treated with appropriate accuracy, to move and extend while they properly interact with each other. Although this vision is very ambitious, we believe the quick development of computer science will lead to both massive improvements and widespread use of these techniques, resulting in enormous progresses in physical chemistry and, eventually, in our society.

Protonation structure of the photosynthetic water oxidizing complex in the S0 state as revealed by normal mode analysis using quantum mechanics/molecular mechanics calculations

Protonation structure of the first intermediate of the water oxidizing complex was determined by QM/MM calculations of molecular vibrations.

Molecular Vibrations of an Oxygen-Evolving Complex and Its Synthetic Mimic

Bio-inspired catalysis for artificial photosynthesis has been widely studied for decades, in particular, with the purpose of using bio-disposable and non-toxic metals as building blocks. The characterisation of such catalysts has been achieved by using different kinds of spectroscopic methods, from X-ray crystallography to NMR spectroscopy. An artificial Mn₄ CaO₄ cubane cluster with dangling Mn₄ was synthesised in 2015 [Zhang et al. Science 2015, 348, 690-693]; this cluster showed many structural similarities to that of the natural oxygen-evolving complex. An accurate structural and spectroscopic comparison between the natural and artificial systems is highly relevant to understand the catalytic mechanism. Among data from different techniques, the differential FTIR spectra (S_n+1 -S_n ) of photosystem II are still lacking a complete interpretation. The availability of IR data of the artificial cluster offers a unique opportunity to assign absolute absorption spectra on a well-defined and easier to interpret analogous moiety. The present work aims to investigate the novel inorganic compound as a model system for an oxygen-evolving complex through measurement of its spectroscopic properties. The experimental results are compared with calculations by using a variety of theoretical methods (normal mode analysis, effective normal mode analysis) in the S₁ state. We underline the similarities and the differences in the computational spectra based on atomistic models of Mn₄ CaO₅ and Mn₄ CaO₄ complexes.