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

被引:12
作者
Ai, N
DeLisle, RK
Yu, SJ
Welsh, WJ
机构
[1] Univ Med & Dent New Jersey, Robert Wood Johnson Med Sch, Dept Pharmacol, Piscataway, NJ 08854 USA
[2] Pharmacoepia Inc, Princeton, NJ 08543 USA
关键词
D O I
10.1021/tx034168k
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
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 to 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.
引用
收藏
页码:1652 / 1660
页数:9
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