### 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 (E_{1/2}) 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 language | English (US) |
---|---|

Pages (from-to) | 1739-1744 |

Number of pages | 6 |

Journal | Molecular Physics |

Volume | 107 |

Issue number | 17 |

DOIs | |

State | Published - 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

### Cite this

*Molecular Physics*,

*107*(17), 1739-1744. https://doi.org/10.1080/00268970903042266

**QSPR models for prediction of half wave potentials of some chlorinated organic compounds using SR-PLS and GA-PLS methods.** / Goudarzi, Nasser; Goodarzi, Mohammad; Hosseini, M. Mohammad; Nekooei, M.

Research output: Contribution to journal › Article

*Molecular Physics*, vol. 107, no. 17, pp. 1739-1744. https://doi.org/10.1080/00268970903042266

}

TY - JOUR

T1 - QSPR models for prediction of half wave potentials of some chlorinated organic compounds using SR-PLS and GA-PLS methods

AU - Goudarzi, Nasser

AU - Goodarzi, Mohammad

AU - Hosseini, M. Mohammad

AU - Nekooei, M.

PY - 2009/10/1

Y1 - 2009/10/1

N2 - 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.

AB - 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.

KW - Chlorinated organic compounds

KW - Genetic algorithm-partial least squares

KW - Half-wave reduction potential

KW - Quantitative structure-property relationship

KW - Stepwise regression-partial least squares

UR - http://www.scopus.com/inward/record.url?scp=68949107951&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=68949107951&partnerID=8YFLogxK

U2 - 10.1080/00268970903042266

DO - 10.1080/00268970903042266

M3 - Article

AN - SCOPUS:68949107951

VL - 107

SP - 1739

EP - 1744

JO - Molecular Physics

JF - Molecular Physics

SN - 0026-8976

IS - 17

ER -