Characterization of the Anopheles gambiae octopamine receptor and discovery of potential agonists and antagonists using a combined computational-experimental approach.

Background: Octopamine receptors (OARs) perform key functions in the biological pathways of primarily invertebrates, making this class of G-protein coupled receptors (GPCRs) a potentially good target for insecticides. However, the lack of structural and experimental data for this insect-essential GPCR family has promoted the development of homology models that are good representations of their biological equivalents for in silico screening of small molecules.

Methods: Two Anopheles gambiae OARs were cloned, analysed and functionally characterized using a heterologous cell reporter system. Four antagonist- and four agonist-binding homology models were generated and virtually screened by docking against compounds obtained from the ZINC database. Resulting compounds from the virtual screen were tested experimentally using an in vitro reporter assay and in a mosquito larvicide bioassay.

Results: Six An. gambiae OAR/tyramine receptor genes were identified. Phylogenetic analysis revealed that the OAR (AGAP000045) that encodes two open reading frames is an α-adrenergic-like receptor. Both splice variants signal through cAMP and calcium. Mutagenesis analysis revealed that D100 in the TM3 region and S206 and S210 in the TM5 region are important to the activation of the GPCR. Some 2,150 compounds from the virtual screen were structurally analysed and 70 compounds were experimentally tested against AgOAR45B expressed in the GloResponse™CRE-luc2P HEK293 reporter cell line, revealing 21 antagonists, 17 weak antagonists, 2 agonists, and 5 weak agonists.

Conclusion: Reported here is the functional characterization of two An. gambiae OARs and the discovery of new OAR agonists and antagonists based on virtual screening and molecular dynamics simulations. Four compounds were identified that had activity in a mosquito larva bioassay, three of which are imidazole derivatives. This combined computational and experimental approach is appropriate for the discovery of new and effective insecticides.