Computational identification of insecticide candidates targeting vitellogenin receptor in Bemisia tabaci using docking and ADMET analysis

Bemisia tabaci (whitefly) is a major agricultural pest responsible for significant crop losses worldwide, primarily due to its high reproductive capacity and resistance to conventional insecticides. The vitellogenin receptor (VgR), a key protein involved in yolk uptake during oocyte development, represents a promising molecular target for disrupting insect reproduction. In this study, a structure-based in silico workflow was employed to identify potential small-molecule inhibitors of the VgR of B. tabaci. The three-dimensional structure of VgR was obtained using AlphaFold and functionally annotated, identifying the β-propeller domain as the primary ligand-binding region. A library of bioactive compounds, including known insecticides and plant-derived flavonoids, was screened using molecular docking. The top-ranking compounds were further evaluated using in silico ADMET and toxicity prediction tools. Docking analysis revealed that afidopyropen exhibited the highest binding affinity (−9.2 kcal/mol), while several flavonoids, including quercetin (−8.8 kcal/mol), isorhamnetin (−8.7 kcal/mol), and genkwanin (−8.4 kcal/mol), showed comparable interaction strengths. Toxicity profiling, incorporating predicted acute oral LD₅₀ values, indicated that genkwanin (LD₅₀ ≈ 3,919 mg/kg) and isorhamnetin (LD₅₀ ≈ 5,000 mg/kg) possessed relatively favorable safety profiles with low acute toxicity (toxicity class 5). In contrast, afidopyropen (LD₅₀ > 2,000 mg/kg) and quercetin (LD₅₀ ≈ 159 mg/kg) showed multiple predicted organ toxicities, with quercetin indicating higher acute toxicity (toxicity class 3). Among all candidates, genkwanin demonstrated the most balanced profile, combining strong binding affinity with lower predicted acute toxicity and fewer organ-specific risks. Overall, this study highlights the vitellogenin receptor as a viable target for reproductive interference in B. tabaci and identifies genkwanin as a promising lead compound for further experimental validation. The findings support the use of integrated in silico screening strategies in the rational development of safer, more sustainable insect control agents.