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

Authors :
Shuo Jin
Kun Qian
Lin He
Zan Zhang
Source :
Insects, Vol 14, Iss 6, p 560 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

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.

Details

Language :
English
ISSN :
20754450
Volume :
14
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Insects
Publication Type :
Academic Journal
Accession number :
edsdoj.234918201a2446688a6b799d4e608d9e
Document Type :
article
Full Text :
https://doi.org/10.3390/insects14060560