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Chem Res Toxicol. 2003 Dec;16(12):1652-60.

Computational models for predicting the binding affinities of ligands for the wild-type androgen receptor and a mutated variant associated with human prostate cancer.

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Department of Pharmacology, University of Medicine & Dentistry of New Jersey, Robert Wood Johnson Medical School, 675 Hoes Lane, Piscataway, New Jersey 08854, USA.


In the present study, values of the binding energy (BE) were calculated for the rat androgen receptor on a data set of 25 steroidal and nonsteroidal compounds for which published values of the observed binding affinity (K(i)) are available. A correlation between BE and pK(i) was evident (r(2) = 0.50) for the entire data set and became more pronounced when the steroids and nonsteroids were plotted separately (r(2) congruent with 0.76). Including BE as an additional descriptor to supplement the default steric-electrostatic descriptors in comparative molecular field analysis dramatically improved the predictive ability of the resulting three-dimensional quantitative structure-activity relationship models. We also demonstrate that the observed loss in ligand specificity between the wild-type (wt) AR and the T877A mutant AR associated with androgen-independent prostate cancer is reflected in decreased BE values (i.e., higher binding affinity) for the antiandrogen pharmaceutical hydroxyflutamide and for several nonandrogenic endogenous steroids, most notably cortisol, corticosterone, 17beta-estradiol, progesterone, and 17alpha-hydroxyprogesterone.

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