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Photosystem I pp 583-594 | Cite as

Application of Marcus Theory to Photosystem I Electron Transfer

  • Christopher C. Moser
  • P. Leslie Dutton
Part of the Advances in Photosynthesis and Respiration book series (AIPH, volume 24)

Abstract

To understand the engineering of light induced electron transfer and energy conversion, photosystem I (PS I) has been extensively reshaped by isolation, removal of protein subunits, and redox cofactors and in some cases reconstitution of exotic redox centers. Such manipulations together with Marcus theory and its biologically focused empirical derivations show that electron tunneling dominated electron transfer kinetics are established principally by the natural selection of distance between redox centers; the driving force and reorganization energy of each electron transfer step falls within a range that assures robust function, despite the repeated impact of mutation and change during evolution. Relatively simple empirical expressions for determining electron tunneling rates are more than adequate to understand the operation of PS I, especially since kinetic and preparative heterogeneity is common. Unlike other photosystems, the typical twofold symmetry of redox centers translates into a functionally relevant, near-symmetric two-branch pattern of electron transfer that culminates in the ability of the quinone on either branch to reduce the first redox center in the terminal iron–sulfur chain. Relatively small differences apparent in the kinetics of the two branches may reflect the tolerance of evolutionary drift in the thermodynamic properties of individual redox centers. Calculation suggests that productive charge separation, while slightly favoring the B chain chlorins, initially reduces both quinones roughly equally; long-term redox equilibration and short-circuiting charge recombination, however, tend to favor electron return through the A-branch.

Keywords

Electron Transfer Slow Phase Electron Tunneling Charge Recombination Reorganization Energy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2006

Authors and Affiliations

  • Christopher C. Moser
    • 1
  • P. Leslie Dutton
    • 1
  1. 1.Department of Biochemistry and BiophysicsUniversity of PennsylvaniaPhiladelphiaUSA

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