Exploring the binding mode and thermodynamics of inverse agonists against estrogen-related receptor alpha

Konda Reddy Karnati1, Yixuan Wang1, Yongli Du2

  • 1Department of Chemistry and Forensic Science, Albany State University Albany GA 31705 USA yixuan.wang@asurams.edu.

RSC Advances
|May 2, 2022
PubMed

Insights

Estrogen-related receptor alpha (ERRα) inverse agonists show promise for breast cancer therapy. Molecular dynamics simulations reveal key binding interactions and identify critical "hot spot" residues for drug development.

Area of Science:

  • Molecular biology
  • Structural biology
  • Pharmacology

Background:

  • Estrogen-related receptor alpha (ERRα) is a validated target for breast cancer treatment.
  • Inverse agonists are a promising therapeutic strategy for regulating ERRα activity.
  • The precise binding mechanisms and key residues involved in ERRα inverse agonism remain unclear.

Purpose of the Study:

  • To elucidate the molecular mechanisms of ERRα inverse agonism.
  • To quantitatively assess the binding affinities of known inverse agonists to ERRα.
  • To identify critical

Main Methods:

  • All-atom molecular dynamics (MD) simulations were performed on complexes of inverse agonists and ERRα.
  • Binding free energies were calculated using the MM-PBSA method.
  • Binding affinities were decomposed per residue to identify hot spot residues.

Main Results:

  • MD simulations revealed that inverse agonists bind within the ERRα ligand binding pocket (LBP), positioning helix H12 in the coactivator groove.
  • Compound 3 and XCT790 exhibited stronger binding to ERRα than compounds 1 and 2, primarily due to van der Waals interactions.
  • Common hot spot residues for effective binding across multiple inverse agonists include Leu324, Phe328, Phe382, Leu398, Phe495, and Leu500.

Conclusions:

  • The study provides detailed insights into the binding modes of ERRα inverse agonists.
  • Key residues and interactions essential for potent ERRα inhibition were identified.
  • These findings are crucial for the rational design of novel breast cancer therapeutics targeting ERRα.

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