Modeling Androgen Receptor Flexibility: A Binding Mode Hypothesis of CYP17 Inhibitors/Antiandrogens for Prostate Cancer Therapy

Prostate Cancer (PCa), a leading cause of cancer death worldwide (www.cancer.gov), is a complex malignancy where a spectrum of targets leads to a diversity of PCa forms. A widely pursued therapeutic target is the Androgen Receptor (AR). As a Steroid Hormone Receptor, AR serves as activator of transcription upon binding to androgens and plays a central role in the development of PCa. AR is a structurally flexible protein, and conformational plasticity of residues in the binding-pocket is a key to its ability to accommodate ligands from various chemical classes. Besides direct modulation of AR activity by antagonists, inhibition of cytochrome CYP17 (17α-hydroxylase/17,20-lyase), essential in androgen biosynthesis, has widely been considered an effective strategy against PCa. Interestingly, Handratta et al. (2005) discovered new, potent inhibitors of CYP17 (C-17 steroid derivatives) with pure AR antagonistic properties. Although the antiandrogenic activity of their lead compound (VN/124-1) has been experimentally proven both <i>in vitro</i> and <i>in vivo,</i> no structural data are currently available to elucidate the molecular determinants responsible for these desirable dual inhibitory properties. We implemented a Structure-based Drug Design (SBDD) approach to generate a valuable hypothesis as to the binding modes of steroidal CYP17 inhibitors/antiandrogens against the AR. To deal with the plasticity of residues buried in the Ligand Binding Domain (LBD), we developed a flexible-receptor Docking protocol based on Induced-Fit (IFD) methodology (www.schrodinger.com/). Our results constitute an ideal starting point for the rational design of next-generation analogues of CYP17 inhibitors/antiandrogens as well as an attractive tool to suggest novel chemical classes of AR antagonists