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Modeling androgen receptor flexibility: a binding mode hypothesis of CYP17 inhibitors/antiandrogens for prostate
Eleonora Gianti1, Randy J Zauhar
1Department of Chemistry & Biochemistry, University of the Sciences, 600 S. 43rd Street, Philadelphia, Pennsylvania 19104, USA.
Abstract:
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.
Insights
Researchers used structure-based drug design to hypothesize binding modes for dual CYP17 inhibitors and androgen receptor (AR) antagonists. This work aids in developing new prostate cancer therapies targeting both androgen biosynthesis and AR activity.
Area of Science:
- Biochemistry
- Molecular Biology
- Drug Discovery
Background:
- Prostate cancer (PCa) is a leading cause of cancer death, with the Androgen Receptor (AR) as a key therapeutic target.
- Inhibiting androgen biosynthesis via cytochrome CYP17 is a validated PCa strategy.
- Novel steroidal CYP17 inhibitors with AR antagonistic properties have been identified, but their structural basis is unknown.
Purpose of the Study:
- To elucidate the molecular determinants of dual CYP17 inhibition and AR antagonism using structure-based drug design.
- To hypothesize the binding modes of steroidal CYP17 inhibitors/antiandrogens against the AR.
- To provide a foundation for designing next-generation PCa therapeutics.
Main Methods:
- Employed a Structure-based Drug Design (SBDD) approach.
- Developed a flexible-receptor Docking protocol utilizing Induced-Fit (IFD) methodology to address receptor plasticity.
- Modeled interactions within the AR Ligand Binding Domain (LBD).
Main Results:
- Generated a hypothesis for the binding modes of steroidal CYP17 inhibitors/antiandrogens to the AR.
- Identified potential molecular determinants for the dual inhibitory properties.
- The computational approach successfully accounted for AR's conformational flexibility.
Conclusions:
- The study provides crucial insights into the mechanism of dual CYP17 inhibitors and AR antagonists.
- Results serve as a starting point for rational drug design of novel PCa therapies.
- The developed IFD protocol is a valuable tool for discovering new AR antagonists.
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