Zographos, S. E. | Search bioRxiv

bioRxiv2026

AgamOBP4-targeted drug repurposing identifies novel mosquito repellent scaffolds

Odorant-binding proteins (OBPs) play central roles in insect chemoreception and represent attractive molecular targets for the discovery of novel behavior-modifying compounds. We report two crystal structures of Anopheles gambiae OBP4: one complexed with the fluorescent probe N-phenyl-1-naphthylamine and a second containing two indole molecules simultaneously bound within the ligand-binding cavity. Structural comparison revealed two binding subsites accommodating the aromatic moieties of 1-NPN or two indole molecules, while identifying Thr58 and Thr70 as key residues in ligand recognition. A structure-based virtual screening campaign was performed against a volatility-filtered library from DrugBank, FooDB, BioNet, and natural-volatiles datasets. Twenty-three ligands were selected for fluorescence competitive binding assays, identifying four AgamOBP4 binders with micromolar affinities (Ki = 2.4-21.8 M). Among them were benzoyl peroxide, an active anti-acne ingredient, Avex-73 (blarcamesine), a clinical-stage drug candidate, and 2-phenylethyl benzoate, a food- and fragrance-associated ester. Additional candidates include O,p'-DDE, a metabolite of the insecticide DDT, and fluorene, a polycyclic aromatic hydrocarbon detected in foods as environmental or processing-derived contaminants. Seven selected compounds were subsequently evaluated against Aedes albopictus in in-vivo behavioral assays, with benzoyl peroxide displaying the highest repellency (RI = 81.8% at 0.2 mg cm-2). AI-based protein-ligand modeling provided insights into ligand recognition and suggested relationships among binding mode, binding affinity, and bioactivity. Collectively, these findings establish the structural basis of ligand recognition by AgamOBP4, highlight the potential of drug-repurposing and food-derived chemical space as sources of next-generation mosquito repellents, and open new opportunities for the development of OBP4-based biosensors for food-quality and environmental monitoring applications.

biochemistry↗

bioRxiv2024

Natural volatiles causing inhibition of mosquito biting behaviors: development of a virtual screening platform predicting antagonists of ORco function for accelerated discovery

Insect olfactory receptors are heteromeric ligand-gated cation channels composed of an obligatory receptor subunit, ORco, and one of many variable subunits, ORx, in as yet undefined molar ratios. When expressed alone ex vivo, ORco forms homotetrameric channels gated by ORco-specific ligands acting as channel agonists. Using an insect cell-based system as a functional platform for expressing mosquito odorant receptors ex vivo, we identified small molecules of natural origin acting as specific ORco channel antagonists, orthosteric or allosteric relative to a postulated ORco agonist binding site, and causing severe inhibition of olfactory function in mosquitoes. In the present communication, we are reporting on the compilation of common structural features of such orthosteric antagonists and development of a ligand-based pharmacophore whose properties are deemed necessary for binding to the agonist binding site and inhibition of ORcos biological function. In silico screening of an available collection of natural volatile compounds with this pharmacophore resulted in identification of several ORco antagonist hits. Cell-based functional screening of the same compound collection resulted in the identification of several compounds acting as orthosteric and allosteric antagonists of ORco channel function ex vivo and inducing anosmic behaviors to Aedes albopictus mosquitoes in vivo. Comparison of the in silico screening results with those of the functional assays revealed that the pharmacophore predicted correctly 7 out of the 8 confirmed orthosteric antagonists and none of the allosteric ones. Because the pharmacophore screen also produced additional hits that did not cause inhibition of the ORco channel function, we generated a Support Vector Machine (SVM) model based on two descriptors of all pharmacophore hits. Training of the SVM on the ex vivo validated compound collection resulted in the selection of the confirmed orthosteric antagonists with a very low cross-validation out-of-sample misclassification rate. Employment of the combined pharmacophore-SVM platform for in silico screening of a larger collection of olfaction-relevant volatiles produced several new hits. Functional validation of randomly selected hits and rejected compounds from this screen confirmed the power of this virtual screening platform as convenient tool for identifying novel vector control agents. To the best of our knowledge, this study is the first one that combines a pharmacophore with a SVM model for identification of AgamORco antagonists and specifically orthosteric ones.

molecular biology↗