Molecular basis of agonist docking in a human GPR103 homology model by site‐directed mutagenesis and structure–activity relationship studies

2014 
Background and Purpose The neuropeptide 26RFa and its cognate receptor GPR103 are involved in the control of food intake and bone mineralization. Here, we have tested, experimentally, the predicted ligand-receptor interactions by site-directed mutagenesis of GPR103 and designed point-substituted 26RFa analogues. Experimental Approach Using the X-ray structure of the β2-adrenoceptor, a 3-D molecular model of GPR103 has been built. The bioactive C-terminal octapeptide 26RFa(19–26), KGGFSFRF-NH2, was docked in this GPR103 model and the ligand-receptor complex was submitted to energy minimization. Key Results In the most stable complex, the Phe-Arg-Phe-NH2 part was oriented inside the receptor cavity, whereas the N-terminal Lys residue remained outside. A strong intermolecular interaction was predicted between the Arg25 residue of 26RFa and the Gln125 residue located in the third transmembrane helix of GPR103. To confirm this interaction experimentally, we tested the ability of 26RFa and Arg-modified 26RFa analogues to activate the wild-type and the Q125A mutant receptors transiently expressed in CHO cells. 26RFa (10−6 M) enhanced [Ca2+]i in wild-type GPR103-transfected cells, but failed to increase [Ca2+]i in Q125A mutant receptor-expressing cells. Moreover, asymmetric dimethylation of the side chain of arginine led to a 26RFa analogue, [ADMA25]26RFa(20–26), that was unable to activate the wild-type GPR103, but antagonized 26RFa-evoked [Ca2+]i increase. Conclusion and Implications Altogether, these data provide strong evidence for a functional interaction between the Arg25 residue of 26RFa and the Gln125 residue of GPR103 upon ligand-receptor activation, which can be exploited for the rational design of potent GPR103 agonists and antagonists.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    58
    References
    11
    Citations
    NaN
    KQI
    []