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 in vitro and in vivo, 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.
Written by:
Gianti E, Zauhar RJ. Are you the author?
Department of Chemistry & Biochemistry, University of the Sciences , 600 S. 43rd Street, Philadelphia, Pennsylvania 19104, United States.
Reference: J Chem Inf Model. 2012 Oct 22;52(10):2670-83.
doi: 10.1021/ci3002342
PubMed Abstract
PMID: 22924551
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