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Estrogenicity of alkylphenolic compounds: A 3‐D structure—activity evaluation of gene activation
Author(s) -
Schmieder Patricia K.,
Aptula Aynur O.,
Routledge Edwin J.,
Sumpter John P.,
Mekenyan Ovanes G.
Publication year - 2000
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.5620190705
Subject(s) - steric effects , chemistry , estrogen receptor , reactivity (psychology) , homo/lumo , population , molecule , stereochemistry , computational chemistry , biology , genetics , organic chemistry , medicine , alternative medicine , demography , pathology , cancer , breast cancer , sociology
A structure–activity relationship evaluation of alkylphenol activation of a human estrogen receptor (hER) reporter gene construct was done using the Common Reactivity Pattern approach. Energetically reasonable conformer distributions for selected steric and electronic chemical descriptors were presented and analyzed. Comparisons of descriptor distributions across active and nonactive chemicals allowed determination of a common reactivity pattern for hER activation. Chemicals capable of hER binding and gene transcription have high density of O–C{sp 3 }distances, from 6.2 to 6.5 Å; maximum distances between atoms in the molecule, ranging from 9.9 to 10.1 Å; and a population density on the lowest unoccupied molecular orbital for O‐atoms from 0.09 to 0.12 AU. Alkylphenols that were nonactive in the recombinant yeast cell assay lacked these stereoelectronic requirements, presumably precluding receptor occupancy or necessary estrogen response element interaction. Derived reactivity patterns were successfully coded into decision trees used to screen additional alkylphenols for potential hER activation. Successful structure–activity relationship modeling and prediction of gene activation for 26 of 29 alkylphenols is an additional step in the elucidation of chemical steric and electronic three‐dimensional parameters that predict which xenobiotics are likely to be estrogenic and demonstrates a valuable tool for screening and prioritization of chemicals for further testing.