4.5 Article

Electrostatic models of electron-driven proton transfer across a lipid membrane

期刊

JOURNAL OF PHYSICS-CONDENSED MATTER
卷 23, 期 23, 页码 -

出版社

IOP PUBLISHING LTD
DOI: 10.1088/0953-8984/23/23/234101

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资金

  1. Laboratory of Physical Sciences
  2. National Security Agency
  3. Army Research Office
  4. National Science Foundation [0726909]
  5. JSPS-RFBR [09-02-92114]
  6. MEXT Kakenhi on Quantum Cybernetics
  7. Funding Program for Innovative R&D on ST (FIRST)
  8. NSF NIRT [ECS-0609146]
  9. PSC-CUNY [41-613]
  10. Grants-in-Aid for Scientific Research [22224007, 21102002] Funding Source: KAKEN

向作者/读者索取更多资源

We present two models for electron-driven uphill proton transport across lipid membranes, with the electron energy converted to the proton gradient via the electrostatic interaction. In the first model, associated with the cytochrome c oxidase complex in the inner mitochondria membranes, the electrostatic coupling to the site occupied by an electron lowers the energy level of the proton-binding site, making proton transfer possible. In the second model, roughly describing the redox loop in a nitrate respiration of E. coli bacteria, an electron displaces a proton from the negative side of the membrane to a shuttle, which subsequently diffuses across the membrane and unloads the proton to its positive side. We show that both models can be described by the same approach, which can be significantly simplified if the system is separated into several clusters, with strong Coulomb interaction inside each cluster and weak transfer couplings between them. We derive and solve the equations of motion for the electron and proton creation/annihilation operators, taking into account the appropriate Coulomb terms, tunnel couplings, and the interaction with the environment. For the second model, these equations of motion are solved jointly with a Langevin-type equation for the shuttle position. We obtain expressions for the electron and proton currents and determine their dependence on the electron and proton voltage build-ups, on-site charging energies, reorganization energies, temperature, and other system parameters. We show that the quantum yield in our models can be up to 100% and the power-conversion efficiency can reach 35%.

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