The use of ‘electronic nose’ sensor responses to predict the inhibition activity of alcohols on the cytochrome P-450 catalyzed p-hydroxylation of aniline Original Research Article

A quantitative structure–activity relationship (QSAR) has been formulated to describe the inhibitory action of a series of alcohols on the cytochrome P-450 catalyzed p-hydroxylation of aniline. The descriptors used in the QSAR are the responses of individual sensors in a polymer-based electronic nose, and are all easily generated experimental values. If the various electronic nose sensor response patterns for the family of test alcohols reflect differences in the chemical properties that are involved in the cytochrome P-450 inhibition process, it ought to be possible to correlate the differences in the electronic nose signals of these analytes with the differences in the cytochrome P-450 inhibition by these species. To evaluate this possibility, multiple linear regression was performed on data obtained from exposure of a series of test alcohols to 19 sensors of a conducting polymer composite electronic nose array. A genetic algorithm was then used to select the optimal set of sensors that best described the inhibitory activity of these alcohols within a linear regression model. The regression equation fit the inhibition data of 20 of the alcohols with an R of 0.995. This fit compares favorably with previously published QSARs on this system that have used log P (Poctanol–water partition coefficient) along with steric parameters of the alcohols, and also compares favorably to QSARs formulated using theoretically calculated parameters.