QSPR models for prediction of half wave potentials of some chlorinated organic compounds using SR-PLS and GA-PLS methods

Nasser Goudarzi, Mohammad Goodarzi, M. Mohammad Hosseini, M. Nekooei

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

The half-wave reduction potential is an important electrochemical property used for the characterization of organic compounds. This property, which is a characteristic constant for a reversible oxidation-reduction system, can be useful for predicting electrochemical properties of other organic compounds. In this work, quantitative structure-property relationship (QSPR) models have been introduced for estimating polarographic half-wave reduction potentials of 21 chlorinated organic compounds. Two QSPR models have been developed based on genetic algorithm-partial least squares (GA-PLS) and stepwise regression-partial least squares (SR-PLS) to predict half-wave potentials (E1/2) of some chlorinated organic compounds. Variable selection is very important for QSPR modelling. In the present study, two selection variables methods were compared to choose molecular descriptors for the construction of a model by the PLS method. Both GA-PLS and SR-PLS methods resulted in accurate prediction, with more accurate results obtained by the GA-PLS model. The respective root mean square error of the prediction set obtained by the GA-PLS and SR-PLS models were 0.082 and 0.1302.

Original languageEnglish (US)
Pages (from-to)1739-1744
Number of pages6
JournalMolecular Physics
Volume107
Issue number17
DOIs
Publication statusPublished - Oct 1 2009

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Keywords

  • Chlorinated organic compounds
  • Genetic algorithm-partial least squares
  • Half-wave reduction potential
  • Quantitative structure-property relationship
  • Stepwise regression-partial least squares

ASJC Scopus subject areas

  • Biophysics
  • Molecular Biology
  • Condensed Matter Physics
  • Physical and Theoretical Chemistry

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