The use of 'electronic nose' sensor responses to predict the inhibition activity of alcohols on the cytochrome P-450 catalyzed p-hydroxylation of aniline

A quantitative structure-activity relationship (QSAR) has been formulated t o describe the inhibitory action of a series of alcohols on the cytochrome P-450 catalyzed p-hydroxylation of aniline. The descriptors used in the QSA R are the responses of individual sensors in a polymer-based electronic nos e, and are all easily generated experimental values. If the various electro nic nose sensor response patterns for the family of test alcohols reflect d ifferences in the chemical properties that are involved in the cytochrome P -450 inhibition process, it ought to be possible to correlate the differenc es in the electronic nose signals of these analytes with the differences in the cytochrome P-450 inhibition by these species. To evaluate this possibi lity, multiple linear regression was performed on data obtained from exposu re of a series of test alcohols to 19 sensors of a conducting polymer compo site electronic nose array. A genetic algorithm was then used to select the optimal set of sensors that best described the inhibitory activity of thes e alcohols within a linear regression model. The regression equation fit th e inhibition data of 20 of the alcohols with an R of 0.995. This fit compar es 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 theo retically calculated parameters. (C) 2000 Elsevier Science Ltd. All rights reserved.