Additive SMILES-based optimal descriptors in QSAR modelling bee toxicity: Using rare SMILES attributes to define the applicability domain

A. A. Toropov, E. Benfenati

Research output: Contribution to journalArticle

Abstract

The additive SMILES-based optimal descriptors have been used for modelling the bee toxicity. The influence of relative prevalence of the SMILES attributes in a training and test sets to the models for bee toxicity has been analysed. Avoiding the use of rare attributes improves statistical characteristics of the model on the external test set. The possibility of using the probability of the presence of SMILES attributes in training and test sets for rational definition of the applicability domain is discussed.

Original languageEnglish
Pages (from-to)4801-4809
Number of pages9
JournalBioorganic and Medicinal Chemistry
Volume16
Issue number9
DOIs
Publication statusPublished - May 1 2008

Keywords

  • Applicability domain
  • QSAR
  • SMILES
  • Toxicity towards bee

ASJC Scopus subject areas

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

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