Use of 13C NMR Spectrometric Data To Produce a Predictive Model of Estrogen Receptor Binding Activity
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 an...
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Veröffentlicht in: | Journal of Chemical Information and Computer Sciences 2001-01, Vol.41 (1), p.219-224 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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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ISSN: | 0095-2338 1549-960X |
DOI: | 10.1021/ci0000878 |