Structural insights into subtype-specific agonist recognition by sphingosine-1-phosphate receptors
Abstract
Sphingosine-1-phosphate (S1P), a key metabolite of sphingolipids, plays crucial roles in a wide range of physiological and pathological processes. S1P primarily exerts its functions by binding to G protein-coupled sphingosine-1-phosphate receptors (S1PRs), which comprise five subtypes (S1PR1-5) in humans, thereby activating these receptors and their downstream signaling pathways. Understanding the molecular determinants that govern agonist selectivity among different S1PR subtypes is vital for the rational and precise development of targeted therapeutic agents. Here, four cryo-electron microscopy structures of agonist-bound S1PR1-Gi1 complexes are reported. Through an integrated approach combining structural analysis, molecular dynamics simulations, and pharmacological assays, the molecular basis for the selectivity of CYM5442, HY-X-1011, Ponesimod, and SAR247799 toward S1PR1 over S1PR2-S1PR5 is uncovered. Nonconserved residues within the ligand-binding pocket and at the Gi1-protein interface contribute to S1PR1 selectivity by these agonists. A distinct agonist binding orientation toward transmembrane helices 5-7, combined with branched substituents that increase the agonist's molecular width, results in steric clashes with residues in S1PR3. Additionally, branched moieties located at the tail portions of the agonist restrict its deep insertion into the binding pocket of both S1PR3 and S1PR5. These structural features collectively enhance its selectivity for S1PR1 over S1PR3…
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Quantum dots: synthesis, bioapplications, and toxicity
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- A Guide to In Silico Drug Design
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.