Electron Transfer Reactions in Multicopper Oxidases

  • Lilia Calabrese
Part of the Electronics and Biotechnology Advanced (EL.B.A.) Forum Series book series (ELBA, volume 3)


The copper ion is essential for all biological systems and, with the only exception of storage proteins, all copper proteins are involved in electron transfer (ET) processes. Electron transfer in proteins shares common features with that occurring in small molecules, however some features distinguish the two systems. Small molecules exchange electrons in solution at close proximity or direct contact to afford inner sphere mechanisms. In proteins redox partners are held in fixed positions and in case of long donor-acceptor distances for long range electron transfer, the intervening medium is the protein matrix. ET in proteins is characterized by a weak interaction between electron donors and acceptors, prevented from coming in contact by the polypeptide chain. Different evolutionary mechanisms have evolved to overcome this hindrance in the different classes of proteins. The blue multicopper oxidases use a structural motif of the polypeptide chain to provide efficient electronic coupling between two redox partners, a mononuclear copper site, referred to as the blue site, and a trinuclear copper site. Blue sites have evolved in blue copper proteins as fast one electron transfer device, while the trinuclear cluster is specially suited to oxygen binding and reduction. The efficient catalytic function of multicopper oxidases results from the synergistic use of these two sites in an intramolecular electron transfer process which couples one electron oxidation of substrates to four electron reduction of dioxygen. Therefore they are among the few enzymes that utilize the full oxidizing capacity of oxygen, which is reduced to two water molecules.


Copper Atom Reorganization Energy Copper Site Multicopper Oxidase Copper Binding Site 
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 Science+Business Media New York 1998

Authors and Affiliations

  • Lilia Calabrese
    • 1
  1. 1.Department of BiologyUniversity of Roma TRERomeItaly

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