Use of 13C NMR Spectrometric Data To Produce a Predictive Model of Estrogen Receptor Binding Activity

Richard D. Beger,* James P. Freeman, Jackson O. Lay, Jr., Jon G. Wilkes, and Dwight W. Miller
Division of Chemistry, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 72079
J. Chem. Inf. Comput. Sci., 2001, 41 (1), pp 219–224
DOI: 10.1021/ci0000878
Publication Date (Web): December 19, 2000
Copyright © 2001 American Chemical Society
*

 To whom correspondence should be addressed. Phone:  870 543-7080. FAX:  870 543-7686. E-mail:  rbeger@nctr.fda.gov.

Abstract

We have developed a spectroscopic data−activity relationship (SDAR) model based on 13C NMR spectral data for 30 estrogenic chemicals whose relative binding affinities (RBA) are available for the alpha (ERα) and beta (ERβ) estrogen receptors. The SDAR models segregated the 30 compounds into strong and medium binding affinities. The SDAR model gave a leave-one-out (LOO) cross-validation of 90%. Two compounds that were classified incorrectly in the SDAR model were in the transition zone between classifications. Real and predicted 13C NMR chemical shifts were used with test compounds to evaluate the predictive behavior of the SDAR model. The 13C NMR SDAR model using predicted 13C NMR data for the test compounds provides a rapid, reliable, and simple way to screen whether a compound binds to the estrogen receptors.

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History

  • Published In Issue January 22, 2001
  • Received July 5, 2000

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