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  • 标题:A generalizable definition of chemical similarity for read-across
  • 本地全文:下载
  • 作者:Matteo Floris ; Alberto Manganaro ; Orazio Nicolotti
  • 期刊名称:Journal of Cheminformatics
  • 印刷版ISSN:1758-2946
  • 电子版ISSN:1758-2946
  • 出版年度:2014
  • 卷号:6
  • 期号:1
  • 页码:39
  • DOI:10.1186/s13321-014-0039-1
  • 语种:English
  • 出版社:BioMed Central
  • 摘要: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. 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. 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.
  • 关键词:Chemical similarity ; Read-across ; Applicability domain ; QSAR
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