iORandLigandDB: A Website for Three-Dimensional Structure Prediction of Insect Odorant Receptors and Docking with Odorants

Simple Summary Smell is an important sense for insects. The olfactory sense of insects is involved in their feeding, mating, egg-laying, predation avoidance, and communication behaviors. The use of insect-specific odorants to control insect behavior is an important control method. Here, we built iORandLigandDB, a platform for the batch prediction of insect-specific odorants based on artificial intelligence technology. The 3D structure of existing ORs in insects and the docking data with relevant odorants can be retrieved from the database. The use of insect-specific odorants to control the behavior of insects has always been a hot spot in research on green control strategies of insects. However, it is generally time-consuming and laborious to explore insect-specific odorants with traditional reverse chemical ecology methods. Here, an insect odorant receptor (OR) and ligand database website (iORandLigandDB) was developed for the specific exploration of insect-specific odorants by using deep learning algorithms. The website provides a range of specific odorants before molecular biology experiments as well as the properties of ORs in closely related insects. At present, the existing three-dimensional structures of ORs in insects and the docking data with related odorants can be retrieved from the database and further analyzed.

Automated summary

In this study, a platform based on artificial intelligence technology was built for the batch prediction of insect-specific odorants, and a website called iORandLigandDB was developed for researchers to explore insect-specific odorants. The website provides access to the three-dimensional structures of existing odorant receptors (ORs) in insects and their docking data with related odorants. This research is important for understanding and controlling insect behavior.