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Published on: November 6, 2018
Modeling Diffusive Motion of Ferredoxin and Plastocyanin on the PSI Domain of Procholorococcus marinus MIT9313
Aaron Chan1,2, Emad Tajkhorshid1,2,3,4, Zaida Luthey-Schulten1,2,4
1Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Visualization, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana─Champaign, Urbana, Illinois 61801-3028, United States.
Abstract:
Diffusion of mobile charge carriers, such as ferredoxin and plastocyanin, often constitutes a rate-determining step in photosynthetic energy conversion. The diffusion time scales typically exceed that of other primary bioenergetic processes and remain beyond the reach of direct simulation at the molecular level. We characterize the diffusive kinetics of ferredoxin and plastocyanin upon the photosystem I-rich domain of Prochlorococcus, the most abundant phototroph on Earth by mass. A modeling approach for ferredoxin and plastocyanin diffusion is presented that uses ensembles of coarse-grained molecular dynamics simulations in Martini 2.2P with GROMACS 2021.2. The simulation ensembles are used to construct the diffusion coefficient and drift for ferredoxin and plastocyanin as spatial functions in the photosystem I domain of the MIT9313 ecotype. Four separate models are constructed, corresponding to ferredoxin and plastocyanin in reduced and oxidized states. A single scaling constant of 0.7 is found to be sufficient to adjust the diffusion coefficient obtained from the Martini simulation ensemble to match the in vitro values for both ferredoxin and plastocyanin. A comparison of Martini versions (2.2P, 2.2, 3) is presented with respect to diffusion scaling. The diffusion coefficient and drift together quantify the inhomogeneity of diffusive behavior. Notably, a funnel-like convergence toward the corresponding putative binding positions is observed for both ferredoxin and plastocyanin, even without such a priori foreknowledge supplied in the simulation protocol. The approach presented here is of relevance for studying diffusion kinetics in photosynthetic and other bioenergetic processes.
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