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Study of potential inhibition of the estrogen receptor α by cannabinoids using an in silico approach: Agonist vs antagonist mechanism

  • Cristian Rocha-Roa
  • , Eliceo Cortes
  • , Sebastián A. Cuesta
  • , José R. Mora
  • , José L. Paz
  • , Máryury Flores-Sumoza
  • , Edgar A. Márquez*
  • *Corresponding author for this work
  • Universidad de Antioquia
  • Universidad del Quindío
  • Universidad Simón Bolívar
  • Universidad San Francisco de Quito
  • Universidad Nacional Mayor de San Marcos
  • Universidad del Norte

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Breast cancer is the main cancer type with more than 2.2 million cases in 2020, and is the principal cause of death in women; with 685000 deaths in 2020 worldwide. The estrogen receptor is involved at least in 70% of breast cancer diagnoses, and the agonist and antagonist properties of the drug in this receptor play a pivotal role in the control of this illness. This work evaluated the agonist and antagonist mechanisms of 30 cannabinoids by employing molecular docking and dynamic simulations. Compounds with docking scores < −8 kcal/mol were analyzed by molecular dynamic simulation at 300 ns, and relevant insights are given about the protein's structural changes, centered on the helicity in alpha-helices H3, H8, H11, and H12. Cannabicitran was the cannabinoid that presented the best relative binding-free energy (−34.96 kcal/mol), and based on rational modification, we found a new natural-based compound with relative binding-free energy (−44.83 kcal/mol) better than the controls hydroxytamoxifen and acolbifen. Structure modifications that could increase biological activity are suggested.

Original languageEnglish
Article number106403
JournalComputers in Biology and Medicine
Volume152
DOIs
StatePublished - Jan 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Cannabinoids
  • Drug discovery
  • Estrogen receptor alpha
  • Molecular modelling
  • Structure-activity relationship
  • Cannabinoids/pharmacology
  • Humans
  • Molecular Dynamics Simulation
  • Estrogen Receptor alpha/chemistry
  • Female
  • Ligands
  • Molecular Docking Simulation
  • Breast Neoplasms/drug therapy

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