Prediction of partitioning properties for environmental pollutants using mathematical structural descriptors

Subhash C Basak, Denise Mills

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Predictive models, based solely on molecular structure, were developed for three environmentally-related partitioning properties: Water solubility, soil/sediment partition coefficient, and octanol/water partition coefficient. Data for a diverse set of 136 chemicals were taken from the literature, and include aromatic and aliphatic compounds, as well as herbicides, pesticides, and polycyclic aromatic hydrocarbons. The hierarchical QSAR (HiQSAR) approach to model building was employed, in which increasingly more computer-resource intensive classes of structural descriptors are used only when the simpler and more easily calculable descriptors do not provide adequate models. The results indicate that the simple topostructural (TS) and topochemical (TC) descriptors provide the best models, and that, in many cases, these structurebased models are superior to those based on properties.

Original languageEnglish (US)
Pages (from-to)60-76
Number of pages17
JournalArkivoc
Volume2005
Issue number2
StatePublished - Mar 2 2005

Keywords

  • Environmental pollutants
  • Hierarchical QSAR
  • Octanol/water partition coefficient
  • Ridge regression
  • Soil/sediment partition coefficient
  • Water solubility

Fingerprint Dive into the research topics of 'Prediction of partitioning properties for environmental pollutants using mathematical structural descriptors'. Together they form a unique fingerprint.

Cite this