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SAR QSAR Environ Res ; 18(7-8): 711-27, 2007.
Article in English | MEDLINE | ID: mdl-18038369

ABSTRACT

The estrogen receptor-beta subtype (ERbeta) is an attractive drug target for the development of novel therapeutic agents for hormone replacement therapy. Hologram quantitative structure-activity relationships (HQSAR) were conducted on a series of 6-phenylnaphthalene and 2-phenylquinoline derivatives, employing values of ERbeta binding affinity. A training set of 65 compounds served to derive the models. The best statistical HQSAR model (q(2) = 0.73 and r(2) = 0.91) was generated using atoms, bonds, connections and donor and acceptor as fragment distinction parameters, and fragment size default (4-7) with hologram length of 199. The model was used to predict the binding affinity of an external test set of 16 compounds, and the predicted values were in good agreement with the experimental results. The final HQSAR model and the information obtained from 2D contribution maps should be useful for the design of novel ERbeta modulators having improved affinity.


Subject(s)
Computational Biology/methods , Estrogen Receptor beta/agonists , Estrogen Receptor beta/antagonists & inhibitors , Pharmacology/methods , Selective Estrogen Receptor Modulators/chemistry , Selective Estrogen Receptor Modulators/pharmacology , Computer Simulation , Protein Binding , Quantitative Structure-Activity Relationship
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