A fast method for electronic couplings in embedded multichromophoric systems

A Simple Expression for the Screening of Excitonic Couplings between Chlorophylls as Inferred for Photosystem I Trimers

The Coulomb coupling between transition densities of the pigments in photosynthetic pigment-protein complexes, termed excitonic coupling, is a key factor for the description of optical spectra and energy transfer. A challenging question is the quantification of the screening of the excitonic coupling by the optical polarizability of the environment. We use the equivalence between the sophisticated quantum chemical polarizable continuum (PCM) model and the simple electrostatic Poisson-TrEsp approach to analyze the distance and orientation dependence of the dielectric screening between chlorophylls in photosystem I trimers. On the basis of these calculations we find that the vacuum couplings Vmn(0) and the couplings in the dielectric medium Vmn=fmnVmn(0) are related by the empirical screening factor fmn=0.60+39.6θ(|κmn|-1.17)exp(-0.56Rmn/Å), where κmn is the usual orientational factor of the dipole-dipole coupling between the pigments, Rmn is the center-to-center distance, and the Heaviside-function θ(|κmn|-1.17) ensures that the exponential distance dependence only contributes for in-line type dipole geometries. We are confident that the present expression can be applied also to other pigment-protein complexes with chlorophyll or related pigments of similar shape. The variance between the Poisson-TrEsp and the approximate coupling values is found to decrease by a factor of 8 and 3-4 using the present expression, instead of an exponential distance dependent or constant screening factor, respectively, assumed previously in the literature.

Insights into Energy Transfer in Light-Harvesting Complex II Through Machine-Learning Assisted Simulations

Light-harvesting complex II (LHCII) is the major antenna of higher plants. Energy transfer processes taking place inside its aggregate of chlorophylls have been experimentally investigated with time-resolved techniques, but a complete understanding of the most relevant energy transfer pathways and relative characteristic times remains elusive. Theoretical models to disentangle experimental data in LHCII have long been challenged by the large size and complex nature of the system. Here, we show that a fully first-principles approach combining molecular dynamics and machine learning can be successfully used to reproduce transient absorption spectra and characterize the EET pathways and the involved times.

Excitation Energy Transfer between Higher Excited States of Photosynthetic Pigments: 2. Chlorophyll b is a B Band Excitation Trap

Chlorophylls (Chls) are known for fast, subpicosecond internal conversion (IC) from ultraviolet/blue absorbing ("B" or "Soret" states) to the energetically lower, red light-absorbing Q states. Consequently, excitation energy transfer (EET) in photosynthetic pigment-protein complexes involving the B states has so far not been considered. We present, for the first time, a theoretical framework for the existence of B-B EET in tightly coupled Chl aggregates such as photosynthetic pigment-protein complexes. We show that according to a Förster resonance energy transport (FRET) scheme, unmodulated B-B EET has an unexpectedly high range. Unsuppressed, it could pose an existential threat-the damage potential of blue light for photochemical reaction centers (RCs) is well-known. This insight reveals so-far undescribed roles for carotenoids (Crts, cf. previous article in this series) and Chl b (this article) of possibly vital importance. Our model system is the photosynthetic antenna pigment-protein complex (CP29). The focus of the study is on the role of Chl b for EET in the Q and B bands. Further, the initial excited pigment distribution in the B band is computed for relevant solar irradiation and wavelength-centered laser pulses. It is found that both accessory pigment classes compete efficiently with Chl a absorption in the B band, leaving only 40% of B band excitations for Chl a. B state population is preferentially relocated to Chl b after excitation of any Chls, due to a near-perfect match of Chl b B band absorption with Chl a B state emission spectra. This results in an efficient depletion of the Chl a population (0.66 per IC/EET step, as compared to 0.21 in a Chl a-only system). Since Chl b only occurs in the peripheral antenna complexes of plants and algae, and RCs contain only Chl a, this would automatically trap potentially dangerous B state population in the antennae, preventing forwarding to the RCs.

Hybrid Quantum Mechanical/Molecular Mechanical Methods For Studying Energy Transduction in Biomolecular Machines

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods have become indispensable tools for the study of biomolecules. In this article, we briefly review the basic methodological details of QM/MM approaches and discuss their applications to various energy transduction problems in biomolecular machines, such as long-range proton transports, fast electron transfers, and mechanochemical coupling. We highlight the particular importance for these applications of balancing computational efficiency and accuracy. Using several recent examples, we illustrate the value and limitations of QM/MM methodologies for both ground and excited states, as well as strategies for calibrating them in specific applications. We conclude with brief comments on several areas that can benefit from further efforts to make QM/MM analyses more quantitative and applicable to increasingly complex biological problems.

Machine Learning Exciton Hamiltonians in Light-Harvesting Complexes

We propose a machine learning (ML)-based strategy for an inexpensive calculation of excitonic properties of light-harvesting complexes (LHCs). The strategy uses classical molecular dynamics simulations of LHCs in their natural environment in combination with ML prediction of the excitonic Hamiltonian of the embedded aggregate of pigments. The proposed ML model can reproduce the effects of geometrical fluctuations together with those due to electrostatic and polarization interactions between the pigments and the protein. The training is performed on the chlorophylls of the major LHC of plants, but we demonstrate that the model is able to extrapolate well beyond the initial training set. Moreover, the accuracy in predicting the effects of the environment is tested on the simulation of the small changes observed in the absorption spectra of the wild-type and a mutant of a minor LHC.