Computational design of allosteric pathways reprograms ligand-selective GPCR signaling.
Biorxiv : the Preprint Server for Biology
|September 2, 2025
Summary
This study introduces a computational method to predict how G-protein-coupled receptor (GPCR) sequence variations affect signaling. Researchers successfully reprogrammed GPCRs, offering new avenues for drug discovery and personalized medicine.
Area of Science:
- Biochemistry and Molecular Biology
- Computational Biology
- Pharmacology
Background:
- G-protein-coupled receptors (GPCRs) are crucial signaling proteins and major drug targets.
- Predicting how receptor sequence and ligand interactions influence GPCR signaling remains a significant challenge in drug discovery.
Purpose of the Study:
- To develop a computational approach for inferring and designing GPCR responses to various ligands.
- To investigate the impact of receptor sequence variations on ligand-induced signaling.
Main Methods:
- Utilized a computational protein structure and dynamics approach.
- Engineered 32 variants of dopamine D1 and D2 receptors.
- Analyzed the effects of sequence variations on ligand potency and efficacy.
Main Results:
- Successfully reprogrammed agonist-induced signal transductions in GPCR variants.
- Observed that subtle sequence variations profoundly impacted ligand potency and efficacy.
- Demonstrated strong agreement between computational predictions and experimental outcomes.
Conclusions:
- The developed computational method provides a rational framework for predicting sequence-dependent, ligand-selective GPCR signaling.
- This approach has significant implications for pharmacogenomics, enhancing drug selectivity, and de novo receptor design.
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