Abstract
The glucagon-like peptide 1 receptor (GLP1R) is a G protein-coupled receptor (GPCR) involved in insulin synthesis and regulation; therefore, it is an important drug target for treatment of diabetes. However, GLP1R is a member of the class B1 family of GPCRs for which there are no experimental structures. To provide a structural basis for drug design and to probe class B GPCR activation, we predicted the transmembrane (TM)bundle structure of GLP1R bound to the peptide Exendin-4 (Exe4; a GLP1R agonist on the market for treating diabetes) using the MembStruk method for scanning TM bundle conformations. We used protein-protein docking methods to combine theTMbundle with the X-ray crystal structure of the 143-aa N terminus coupled to the Exe4 peptide. This complex was subjected to 28 ns of full-solvent, full-lipid molecular dynamics. We find 14 strong polar interactions of Exe4 with GLP1R, of which 8 interactions are in the TM bundle (2 interactions confirmed by mutation studies) and 6 interactions involve the N terminus (3 interactions found in the crystal structure).We also find 10 important hydrophobic interactions, of which 4 interactions are in the TM bundle (2 interactions confirmed by mutation studies) and 6 interactions are in the N terminus (6 interactions present in the crystal structure). Thus, our predicted structure agrees with available mutagenesis studies. We suggest a number of mutation experiments to further validate our predicted structure. The structure should be useful for guiding drug design and can provide a structural basis for understanding ligand binding and receptor activation of GLP1R and other class B1 GPCRs.
| Original language | English |
|---|---|
| Pages (from-to) | 19988-19993 |
| Number of pages | 6 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Volume | 109 |
| Issue number | 49 |
| DOIs | |
| Publication status | Published - 4 Dec 2012 |
| Externally published | Yes |
Keywords
- Incretin receptors
- Peptide hormones
- Protein structure prediction