期刊
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
卷 11, 期 5, 页码 1636-1643出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jpclett.9b03486
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资金
- National Science Foundation [CHE-1800505]
- Department of Energy, Office of Basic Energy Sciences [DE-SC0018239]
- Academy of Finland [285481]
- U.S. Department of Energy (DOE) [DE-SC0018239] Funding Source: U.S. Department of Energy (DOE)
- Academy of Finland (AKA) [285481, 285481] Funding Source: Academy of Finland (AKA)
High efficiency of light harvesting in photosynthetic pigment-protein complexes is governed by evolutionary-perfected protein-assisted tuning of individual pigment properties and interpigment interactions. Due to the large number of spectrally overlapping pigments in a typical photosynthetic complex, experimental methods often fail to unambiguously identify individual chromophore properties. Here, we report a first-principles-based modeling protocol capable of predicting properties of pigments in protein environment to a high precision. The technique was applied to successfully uncover electronic properties of the Fenna - Matthews - Olson (FMO) pigment-protein complex. Each of the three subunits of the FMO complex contains eight strongly coupled bacteriochlorophyll a (BChl a) pigments. The excitonic structure of FMO can be described by an electronic Hamiltonian containing excitation (site) energies of BChl a pigments and electronic couplings between them. Several such Hamiltonians have been developed in the past based on the information from various spectroscopic measurements of FMO; however, fine details of the excitonic structure and energy transfer in FMO, especially assignments of short-lived high-energy sites, remain elusive. Utilizing polarizable embedding quantum mechanics/molecular mechanics with the effective fragment potentials, we computed the electronic Hamiltonian of FMO that is in general agreement with previously reported empirical Hamiltonians and quantitatively reproduces experimental absorption and circular dichroism spectra of the FMO protein. The developed computational protocol is sufficiently simple and can be utilized for predictive modeling of other wild-type and mutated photosynthetic pigment-protein complexes.
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