A generalizable definition of chemical similarity for read-across

Matteo Floris, Alberto Manganaro, Orazio Nicolotti, Ricardo Medda, Giuseppe Felice Mangiatordi, Emilio Benfenati

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results: This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions: Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain.

Original languageEnglish
Article number39
JournalJournal of Cheminformatics
Volume6
Issue number1
DOIs
Publication statusPublished - Oct 18 2014

Keywords

  • Applicability domain
  • Chemical similarity
  • QSAR
  • Read-across

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Library and Information Sciences

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