Computational studies to predict or explain G protein coupled receptor polypharmacology

Area of Science:

• Pharmacology
• Structural Biology
• Computational Chemistry

Background:

• G protein-coupled receptors (GPCRs) represent a vast superfamily, making them key targets for polypharmacology.
• Advances in structural biology and computational methods enable detailed investigation of GPCR ligand interactions.
• Understanding off-target effects is crucial for drug development and therapeutic efficacy.

Purpose of the Study:

• To investigate GPCR polypharmacology using molecular modeling and structural data.
• To explore off-target binding of adenosine derivatives at diverse GPCRs.
• To elucidate the structural basis for unanticipated ligand-receptor interactions.

Main Methods:

• Structure-based molecular modeling utilizing available X-ray GPCR structures.
• Screening of sterically constrained adenosine derivatives for binding at various receptors.
• Analysis of ligand-receptor interactions, focusing on conserved residues like TM3 Asp.

Main Results:

• Adenosine derivatives exhibited unanticipated off-target binding, notably at biogenic amine receptors.
• Molecular modeling provided a consistent explanation for these interactions.
• A conserved aspartate residue in transmembrane helix 3 plays a dual role, acting as a counterion for biogenic amines and forming hydrogen bonds with adenosine.

Conclusions:

• Molecular modeling combined with structural data is a powerful approach for studying GPCR polypharmacology.
• The identified mechanism of recognition highlights the plasticity of GPCR binding sites.
• This systematic approach can be extended to other GPCRs and ligand families.