Abstract
A qualitative 3D pharmacophore model (a common feature based model or Catalyst HipHop algorithm) was developed for well-known natural product androgen receptor down-regulating agents (ARDAs). The four common chemical features identified included: one hydrophobic group, one ring aromatic group, and two hydrogen bond acceptors. This model served as a template in virtual screening of the Maybridge and NCI databases that resulted in identification of six new ARDAs (EC(50) values 17.5-212 microM). Five of these molecules strongly inhibited the growth of human prostate LNCaP cells. These novel compounds may be used as leads to develop other novel anti-prostate cancer agents.