Structure-based virtual screening discovers potent and selective adenosine A₁ receptor antagonists

Area of Science:

• Medicinal Chemistry
• Pharmacology
• Computational Drug Discovery

Background:

• G protein-coupled receptors (GPCRs) are crucial drug targets.
• Developing subtype-selective ligands is vital for targeted therapies and minimizing side effects.
• Adenosine receptors (A1R and A2AR) are closely related GPCRs, making subtype selectivity challenging.

Purpose of the Study:

• To apply a structure-based virtual screening approach for designing subtype-selective ligands targeting A1 adenosine receptors (A1R) and A2A adenosine receptors (A2AR).
• To identify novel A1R-selective antagonists with improved potency and selectivity.

Main Methods:

• Utilized molecular docking to screen a library of 4.6 million compounds against A1R and A2AR crystal structures.
• Focused on exploiting a non-conserved subpocket in the A1R binding site for selectivity.
• Designed and synthesized analogs of identified hit compounds to optimize potency and selectivity.

Main Results:

• Predicted 20 potential A1R-selective ligands from the virtual screen.
• Seven compounds demonstrated micromolar antagonism of A1R, with some showing slight subtype selectivity.
• Optimized analogs achieved nanomolar potency and up to 76-fold selectivity for A1R over A2AR.

Conclusions:

• Structure-based virtual screening is a powerful strategy for discovering subtype-selective GPCR ligands.
• The identified A1R antagonists represent promising leads for developing safer therapeutics.
• This approach can accelerate the drug discovery process for GPCR targets.