New Insecticide Designed to Target Ecdysone Receptors of Bemisia tabaci

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Publikace nespadá pod Ústav výpočetní techniky, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.
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BERA Krishnendu HRITZ Jozef BRÁZDA Václav KUMAR Rajesh

Rok publikování 2025
Druh Článek v odborném periodiku
Časopis / Zdroj ACS Agricultural Science and Technology
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www https://doi.org/10.1021/acsagscitech.5c00066
Doi http://dx.doi.org/10.1021/acsagscitech.5c00066
Klíčová slova Insecticide; molecular docking; molecular dynamicssimulation; principal component analysis; MM/GBSA; umbrella sampling
Popis Bemisia tabaci is a highly destructive pest that affects many crops worldwide. Its feeding behavior on phloem sap and secretion of honeydew on leaves leads to the accumulation of mold, which impairs photosynthesis and fruit quality. Additionally, it transmits more than 100 plant viruses, which interfere with plant growth and reduce crop productivity. In this work, we targeted the ecdysone receptor (EcR) of B. tabaci, as it is involved in metamorphosis, cell differentiation, and reproduction processes. The EcR sequence was retrieved from the UniProt database (A0A142K0N3), and multiple sequence alignment (MSA) revealed that the ligand-binding domain is conserved among other plant-destroying pests and insects. The EcR structure of B. tabaci (PDB ID: 1Z5X) was used for high-throughput virtual screening with 32,552 secondary metabolites, retrieved from the NPAtlas 2.0 database using iDock 2.2.3. The top 40 metabolites were selected based on their predicted binding energy by iDock 2.2.3 and redocked using AutoDock Vina 1.1.2. The complexes of the top four compounds with EcR were selected for molecular dynamics simulation (total simulation time: 0.5 mu s) and compared with the apo-EcR structure. Additionally, umbrella sampling simulations were performed for 1.64 mu s. The insecticide-like properties and toxicity of the four metabolites were compared with conventional pesticides such as ponasterone A. Our computational predictions suggest that NPA008492, NPA006374, NPA012964, and NPA012752 are potential lead molecules and promising candidates for experimental validation.
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