What question did this study set out to answer?

The aim is to identify potential inhibitors of the ecdysone receptor in Bemisia tabaci using in silico methods.

February 28, 2026Open Access

A Hierarchical In Silico Screening of Streptomyces-Derived Natural Products to Identify Novel Inhibitors of the Bemisia tabaci Ecdysone Receptor (EcR)

Key Points

The aim is to identify potential inhibitors of the ecdysone receptor in Bemisia tabaci using in silico methods.
Conducted hierarchical virtual screening on 6,524 Streptomyces-derived compounds.
Utilized molecular docking and ADMET filtering for initial compound evaluation.
Performed 100 ns molecular dynamics simulations to study binding stability.
Calculated binding free energies using MM/GBSA methods and applied principal component analysis.
Identified Solphenazine E and an Acetamide derivative as stable EcR inhibitors through MD simulations.
Both compounds showed strong binding energies of −56.05 and −55.38 kcal/mol, respectively.
16α-hydroxyestrone, despite a favorable ADMET profile, was disqualified for its weak binding stability.

Abstract

The whitefly Bemisia tabaci is a devastating global agricultural pest that has developed growing resistance to conventional insecticides. Targeting the insect-specific ecdysone receptor (EcR) offers a promising strategy for developing selective and sustainable pesticides. This study employed a rigorous hierarchical virtual screening workflow on 6,524 Streptomyces-derived natural compounds, integrating molecular docking, ADMET filtering, extensive 100 ns molecular dynamics (MD) simulations, MM/GBSA binding free energy calculations, and principal component analysis (PCA). Our analysis revealed a critical disconnect between initial docking scores and long-term dynamic stability: compounds with high docking affinities often proved unstable in simulation, while two compounds, Solphenazine E and an Acetamide derivative emerged as stable binders based on MD simulations and predicted interaction patterns. Both maintained persistent hydrogen bonding with the critical residue ARG97, exhibited robust RMSD profiles comparable to the co-crystal control, and demonstrated strong binding free energies (ΔG = −56.05 and −55.38 kcal/mol, respectively). In contrast, while 16α-hydroxyestrone displayed the most favorable ADMET safety profile (non-mutagenic, non-hepatotoxic), its weak binding energy (ΔG = −37.86 kcal/mol), high ligand mobility (RMSD >3 Å after 40 ns), and intermittent ARG97 interactions disqualified it as a primary candidate despite its lower predicted human toxicity. This study demonstrates that Solphenazine E and the Acetamide derivative are dynamically stable, computationally predicted insecticide-selective EcR inhibitors, and identifies them as the most promising natural product leads for targeted pest control of B. tabaci. Our findings underscore the necessity of multi-tiered computational validation and demonstrate that ADMET favorability, while important for human safety, must be weighed against binding stability and efficacy for insecticidal application. Future development should focus on experimental validation of these stable binders, with formulation and exposure control strategies to mitigate any off-target hepatotoxicity concerns.

A Hierarchical In Silico Screening of Streptomyces-Derived Natural Products to Identify Novel Inhibitors of the Bemisia tabaci Ecdysone Receptor (EcR)

Key Points

Abstract

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