Evaluation and refinement of the property prediction stage of the targeted QSPR method for 15 constant properties and 80 groups of compounds

Mordechai Shacham, Michael Elly, Inga Paster, Neima Brauner

Research output: Contribution to journalArticlepeer-review

Abstract

The dominant descriptor version of the targeted QSPR method (TQSPR1, [Shacham and Brauner, Chem. Eng. Sci., 66, 2606, 2011]) is used to predict 15 constant properties for 80 groups of compounds in order to assess the range of applicability of the prediction technique and to identify frequent causes of excessive prediction errors.It is demonstrated that the TQSPR1 method can model the majority of the properties within the data uncertainty level for most groups of compounds that were included in this study. It is also shown that the accuracy of the TQSPR1 predictions is comparable or higher than the accuracy of predictions obtained by commonly used group contribution methods. Frequent causes of excessive prediction errors are identified and ways for improvement of the prediction accuracy in such cases are proposed and demonstrated. The results reported and the suggestions for improvements are applicable to other property prediction techniques, as well, and are not limited to the TQSPR1 method.The results of the study enable improving the consistency of the physical property and descriptor databases for increasing the robustness of QSPRs that can be derived for a variety of properties and compounds.

Original languageEnglish
Pages (from-to)186-197
Number of pages12
JournalChemical Engineering Science
Volume97
DOIs
StatePublished - 8 Jun 2013

Keywords

  • Computational chemistry
  • Mathematical modeling
  • Parameter identification
  • Property prediction
  • QSPR
  • Systems engineering

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