Thursday, July 1, 2010

Computing redox potentials

First-principles computations of redox potentials in solution is a difficult task due to the large number of solvent molecules that must be included. As the computational cost increases steeply with the number of basis functions, a common approach consists of performing a geometry optimization of the reduced and oxidized species in vacuo, and then computing the energy of these species with a larger basis set and a continuum method that represents the influence of the solvent on the solute electron distribution. Besides the error introduced by assuming that the geometry does not change upon solvation, this approach includes two main sources of errors:
a) the intrinsic error of the theoretical level used to compute the electronic energies
b) the error associated with the continuum method itself.

Whereas the first error may be rigorously quantified by comparison with experimental gas phase values and made very small with the choice of an appropriate basis set/theory level combination , most continuum methods yield less predictable errors (especially when the redox-active portion of the solute is present in a very heterogenous environment, like an enzyme active site).


Dejun Si and Hui Li have now improved the continuum solvation methods by including the possibility of assigning different dielectric constants to different parts of the solute cavity surface, thus improving the description of heterogeneous environments. These authors have also shown this approach to correctly predict the relative redox potentials of the type I copper centers (optimized in vacuo) in eleven different proteins with maximum errors < 0.1 V (provided that the systems include approximately 100 protein atoms around the Cu Center). The error can be minimized to < 0.05 V by optimizing the geometries using the newly-developed heterogenuous polarizable continuum.

This new continuum method is implemented in the latest release of GAMESS, a free and very powerful quantum chemistry package available from Mark Gordon's group, at Iowa State University.


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