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

Thomas P. Vaid, Nathan S Lewis

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

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. (C) 2000 Elsevier Science Ltd.

Original languageEnglish
Pages (from-to)795-805
Number of pages11
JournalBioorganic and Medicinal Chemistry
Volume8
Issue number4
DOIs
Publication statusPublished - Apr 2000

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Electronic Nose
Hydroxylation
Cytochrome P-450 Enzyme System
Quantitative Structure-Activity Relationship
Alcohols
Sensors
Linear Models
Linear regression
Polymers
Conducting polymers
Chemical properties
aniline
Electronic nose
Genetic algorithms
Water
Composite materials

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Organic Chemistry
  • Drug Discovery
  • Pharmaceutical Science

Cite this

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abstract = "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. (C) 2000 Elsevier Science Ltd.",
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