Investigating the mechanisms of bioconcentration through QSAR classification trees

Francesca Grisoni, Viviana Consonni, Marco Vighi, Sara Villa, Roberto Todeschini

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Scopus)

Abstract

This paper proposes a scheme to predict whether a compound (1) is mainly stored within lipid tissues, (2) has additional storage sites (e.g., proteins), or (3) is metabolized/eliminated with a reduced bioconcentration. The approach is based on two validated QSAR (Quantitative Structure-Activity Relationship) trees, whose salient features are: (a) descriptor interpretability and (b) simplicity. Trees were developed for 779 organic compounds, the TGD approach was used to quantify the lipid-driven bioconcentration, and a refined machine-learning optimization procedure was applied. We focused on molecular descriptor interpretation, which allowed us to gather new mechanistic insights into the bioconcentration mechanisms.

Original languageEnglish
Pages (from-to)198-205
Number of pages8
JournalEnvironment International
Volume88
DOIs
Publication statusPublished - 1 Mar 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 Elsevier Ltd.

Keywords

  • BCF
  • Bioconcentration
  • CART
  • Mechanisms
  • Molecular descriptors
  • QSAR

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