Correlation studies of anodic peak potentials and ionization potentials for polycyclic aromatic hydrocarbons.
One-electron oxidation represents one of the major metabolic pathways of bioactivation of polycyclic aromatic hydrocarbons (PAH) to ultimate carcinogens capable of binding to cellular macromolecules, thereby initiating the cancer process. Since the ionization potential (IP) is related to the ease of removal of a pi electron from an aromatic molecule, a low IP is a necessary condition for the PAH to undergo one-electron oxidation. The principal aim of this study was to provide a general and simple technique suitable for obtaining IP of PAH with satisfactory accuracy. Anodic peak potentials (Eap) of 90 PAH were measured by cyclic voltammetry under irreversible oxidation conditions and correlated with the corresponding IP. This allowed determination of a least-squares regression line. From the corresponding equation, IP = 1.70Eap + 5.29, IP can be calculated with a narrow margin of error after a simple electrochemical measure. It was also found that PAH substituted with a methyl group on a position of appreciable electron density are best represented by a different line, corresponding to the equation IP = 1.65Eap + 5.27. The calculated IP were also compared to other tabulated values, determined by different experimental techniques, and our set of IP values proved to yield the most satisfactory correlation. For some PAH, further studies under reversible voltammetric conditions allowed determination of two additional parameters: formal oxidation potentials (Eo) and the number of electrons (n) involved in the redox process. IP is an important parameter in predicting the metabolic activation of carcinogenic PAH.
Cremonesi
P
P
Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha 68198-6805.
Rogan
E
E
Cavalieri
E
E
D055598:Chemical Phenomena; D002627:Chemistry, Physical; D004563:Electrochemistry; D010084:Oxidation-Reduction; D011083:Polycyclic Compounds / Q000737:chemistry*; D012044:Regression Analysis
D011083:Polycyclic Compounds