QSPR study of partition coefficient (Ko/w) of some organic compounds using radial basic function-partial least square (RBF-PLS)

Nasser Goudarzi, Mohammad Goodarzi

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

In this work, we introduce a new method ability radial basic function-partial least square (RBFPLS) with high accuracy and precision in QSPR studies. Three quantitative structure-propertty relationship (QSPR) methods have been compared for the prediction of n-octanol-water partition coefficients (Ko/w) of some organic compounds. The multiple linear regressions (MLR), partial least square (PLS) and radial basis function-partial least squares (RBF-PLS) models were employed to construct linear and nonlinear models to predict of Ko/w. The theoretical descriptors that calculated by Dragon and Gaussian 98 were explored by stepwise regressions, encoding different aspects of the topological, geometrical and electronic molecular structures. The root means square error of prediction (RMSEP) for training and prediction sets by MLR, PLS and RBF-PLS models were 0.4022, 0.4128, 0.3050, 0.3564, 0.0364 and 0.0533, respectively. Also, the relative standard error of prediction (RSEP) for training and prediction sets by MLR, PLS and RBF-PLS models were 13.24, 13.60, 10.04, 11.74, 1.197 and 1.757 respectively. The resultant data explained that RBFPLS produced better results than PLS and MLR.

Original languageEnglish (US)
Pages (from-to)1776-1783
Number of pages8
JournalJournal of the Brazilian Chemical Society
Volume21
Issue number9
DOIs
StatePublished - 2010

Keywords

  • MLR
  • N-octanol-water partition coefficients
  • PLS
  • Quantitative structure-activity relationship
  • RBF-PLS

ASJC Scopus subject areas

  • Chemistry(all)

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