Computational Characterization and Prediction of Estrogen Receptor Coactivator Binding Site Inhibitors

Abstract

In an effort to treat breast cancer, selective estrogen receptor modulators (SERMs) have been used to modulate the estrogen-signaling pathway with mixed results [1]. A classic example of a SERM is tamoxifen. When used as a therapeutic for a limited time, tamoxifen is effective in disrupting the estrogen-signaling pathway. Unfortunately, with prolonged use, breast tumor cells become resistant to tamoxifen and are able to use the bioactivated metabolite of tamoxifen to interact with co-activators that activate the estrogen-signaling pathway, reversing its original role [1]. An alternative therapeutic approach is to target the binding site of the co-activator protein. Recent studies have shown that some small molecules may bind in sites (e.g. co-activator site) other than the estradiol binding site [2] and still disrupt the estrogen-signaling pathway. By binding in the co-activator site while estradiol is bound in the estrogen receptor (ER) ligand binding domain (LBD), these small molecules act as co-activator binding inhibitors (CBIs) because the co-activator proteins can no longer bind; thus, gene transcription is inhibited. Potentially, these CBIs can act as a new therapeutics against environmental or natural agonists of ERalpha. Quantitative structure-activity relationship (QSAR) studies have been used to develop therapeutics that will compete and bind in the estradiol binding site of the ERalpha LBD [3-5]. Because these studies have focused on the estradiol binding site, new potential ER disruptors that bind in the co-activator site have been missed. Our proposal focuses on developing a new computational approach to predict therapeutically useful ERalpha disruptors by investigating CBIs binding to the co-activator site in conjunction with estrogenic compounds bound in the estradiol site

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2005
Accession Number
ADA446323

Entities

People

  • Brian J. Bennion
  • Felice Lightstone
  • Kris Kulp
  • Monique Cosman

Organizations

  • University of California

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Amines
  • Bioassay
  • Biochemistry
  • Breast Cancer
  • Cell Line
  • Cell Physiological Processes
  • Chemical Compounds
  • Chemical Synthesis
  • Chemistry
  • Computational Chemistry
  • Crystal Structure
  • Department Of Defense
  • Dynamics
  • Molecular Dynamics
  • Neoplasms
  • Simulations
  • Small Molecules

Fields of Study

  • Biology
  • Chemistry

Readers

  • Breast cancer cell signaling and growth regulation.