Journal Highlight: Rigorous 3-dimensional spectral data activity relationship approach modeling strategy for ToxCast estrogen receptor data classification, validation, and feature extraction

Skip to Navigation

Ezine

  • Published: Oct 10, 2016
  • Author: separationsNOW
  • Channels: Laboratory Informatics
thumbnail image: Journal Highlight: Rigorous 3-dimensional spectral data activity relationship approach modeling strategy for ToxCast estrogen receptor data classification, validation, and feature extraction
The estrogenic potential of 1528 compounds from the ToxCast database has been modelled by a 3-dimensional spectral data activity relationship approach, allowing identification of structural features essential for estrogenicity.

Rigorous 3-dimensional spectral data activity relationship approach modeling strategy for ToxCast estrogen receptor data classification, validation, and feature extraction

Environmental Toxicology and Chemistry, 2016, online
Svetoslav H. Slavov and Richard D. Beger

Abstract: The estrogenic potential (expressed as a score composite of 18 high throughput screening bioassays) of 1528 compounds from the ToxCast database was modeled by a 3-dimensional spectral data activity relationship approach (3D-SDAR). Due to a lack of 17O nuclear magnetic resonance (NMR) simulation software, the most informative carbon–carbon 3D-SDAR fingerprints were augmented with indicator variables representing oxygen atoms from carbonyl and carboxamide, ester, sulfonyl, nitro, aliphatic hydroxyl, and phenolic hydroxyl groups. To evaluate the true predictive performance of the authors’ model the United States Environmental Protection Agency provided them with a blind test set consisting of 2008 compounds. Of these, 543 had available literature data—their binding affinity served to estimate the external classification accuracy of the developed model: predictive accuracy of 0.62, sensitivity of 0.71, and specificity of 0.53 were obtained. Compared with alternative modeling techniques, the authors’ model displayed very little reduction in performance between the modeling and the prediction set. A 3D-SDAR mapping technique allowed identification of structural features essential for estrogenicity: 1) the presence of a phenolic OH group or cyclohexenone, 2) a second aromatic or phenolic ring at a distance of 6 Å to 8 Å from the oxygen of the first phenol ring, 3) the presence of a methyl group approximately 6 Å away from the centroid of a phenol ring, and 4) a carbonyl group in close proximity (∼4 Å measured to the centroid) to 1 of the phenol rings.

  • This paper is free to view for all users registered on separationsNOW.com until the end of December 2016.
    After this time, you can purchase it using Pay-Per-View on Wiley Online Library.

Follow us on Twitter!

Social Links

Share This Links

Bookmark and Share

Microsites

Suppliers Selection
Societies Selection

Banner Ad

Click here to see
all job opportunities

Copyright Information

Interested in spectroscopy? Visit our sister site spectroscopyNOW.com

Copyright © 2017 John Wiley & Sons, Inc. All Rights Reserved