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Ligands of Therapeutic Utility for the Liver X Receptors

Rajesh Komati1, Dominick Spadoni2, Shilong Zheng3

  • 1Department of Chemistry and RCMI Cancer Research Center, Xavier University of Louisiana, New Orleans, LA 70125, USA. rkomati@xula.edu.

Molecules (Basel, Switzerland)
|January 10, 2017
PubMed

Insights

Liver X receptors (LXRs) are key targets for diseases linked to lipid metabolism. This review summarizes LXR ligands and proposes molecular modeling for designing specific LXRβ ligands to minimize side effects.

Area of Science:

  • Biochemistry
  • Pharmacology
  • Medicinal Chemistry

Background:

  • Liver X receptors (LXRs) are crucial regulators of lipid metabolism.
  • Dysregulated lipid metabolism is implicated in various diseases, including metabolic disorders, neurological conditions, and cancers.
  • LXRs are recognized as promising therapeutic targets for these pathologies.

Purpose of the Study:

  • To review endogenous, natural, and synthetic ligands targeting Liver X receptors (LXRs).
  • To explore molecular modeling strategies for designing more specific LXRβ ligands.
  • To address challenges in minimizing undesirable lipid metabolism effects associated with LXR activation.

Main Methods:

  • Literature review of known LXR ligands.
  • Analysis of ligand-protein interactions using molecular modeling.
  • Examination of amino acid residue interactions within the LXRβ ligand-binding domain.

Main Results:

  • Identification and categorization of diverse LXR ligands.
  • Insights into the molecular basis of ligand binding to LXRβ.
  • Considerations for structure-based drug design of selective LXR modulators.

Conclusions:

  • LXRs represent a significant therapeutic avenue for a range of diseases.
  • Developing selective LXRβ ligands through rational design is crucial for optimizing therapeutic outcomes.
  • Molecular modeling offers a valuable approach to enhance ligand specificity and reduce off-target effects.
Keywords:
Alzheimer’s diseaseLXRαLXRβ specific ligandsatherosclerosiscancerdiabetesinteraction energylipid metabolismliver X receptorsmolecular modeling

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